Create _relaxed tests for newly added tests -- generated tests

New tests were added to V1_0 and V1_1 specs, but they did not have a
"_relaxed" test in V1_1.

This CL generates the CTS and VTS tests as a followup CL.

Bug: 76434855
Test: mma
Test: NeuralNetworksTest_static
Test: VtsHalNeuralnetworksV1_0TargetTest
Test: VtsHalNeuralnetworksV1_1TargetTest
Change-Id: Id3703db7091583de19e22b82eab75e88da785428

153 files changed, 8313 insertions, 5 deletions

diff --git a/nn/runtime/test/generated/all_generated_V1_1_vts_tests.cpp b/nn/runtime/test/generated/all_generated_V1_1_vts_tests.cpp
index adbbf847f..d84b46052 100644
--- a/nn/runtime/test/generated/all_generated_V1_1_vts_tests.cpp
+++ b/nn/runtime/test/generated/all_generated_V1_1_vts_tests.cpp
@@ -76,6 +76,21 @@ TEST_F(NeuralnetworksHidlTest, avg_pool_float_4_relaxed) {
                              avg_pool_float_4_relaxed::examples);
 }
 
+namespace avg_pool_float_5_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated avg_pool_float_5_relaxed test
+#include "examples/avg_pool_float_5_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/avg_pool_float_5_relaxed.model.cpp"
+} // namespace avg_pool_float_5_relaxed
+TEST_F(NeuralnetworksHidlTest, avg_pool_float_5_relaxed) {
+    generated_tests::Execute(device,
+                             avg_pool_float_5_relaxed::createTestModel,
+                             avg_pool_float_5_relaxed::is_ignored,
+                             avg_pool_float_5_relaxed::examples);
+}
+
 namespace batch_to_space_float_1 {
 std::vector<MixedTypedExample> examples = {
 // Generated batch_to_space_float_1 test
@@ -91,6 +106,21 @@ TEST_F(NeuralnetworksHidlTest, batch_to_space_float_1) {
                              batch_to_space_float_1::examples);
 }
 
+namespace batch_to_space_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated batch_to_space_float_1_relaxed test
+#include "examples/batch_to_space_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/batch_to_space_float_1_relaxed.model.cpp"
+} // namespace batch_to_space_float_1_relaxed
+TEST_F(NeuralnetworksHidlTest, batch_to_space_float_1_relaxed) {
+    generated_tests::Execute(device,
+                             batch_to_space_float_1_relaxed::createTestModel,
+                             batch_to_space_float_1_relaxed::is_ignored,
+                             batch_to_space_float_1_relaxed::examples);
+}
+
 namespace batch_to_space {
 std::vector<MixedTypedExample> examples = {
 // Generated batch_to_space test
@@ -121,6 +151,21 @@ TEST_F(NeuralnetworksHidlTest, batch_to_space_quant8_1) {
                              batch_to_space_quant8_1::examples);
 }
 
+namespace batch_to_space_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated batch_to_space_relaxed test
+#include "examples/batch_to_space_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/batch_to_space_relaxed.model.cpp"
+} // namespace batch_to_space_relaxed
+TEST_F(NeuralnetworksHidlTest, batch_to_space_relaxed) {
+    generated_tests::Execute(device,
+                             batch_to_space_relaxed::createTestModel,
+                             batch_to_space_relaxed::is_ignored,
+                             batch_to_space_relaxed::examples);
+}
+
 namespace concat_float_1_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated concat_float_1_relaxed test
@@ -226,6 +271,21 @@ TEST_F(NeuralnetworksHidlTest, conv_3_h3_w2_VALID_relaxed) {
                              conv_3_h3_w2_VALID_relaxed::examples);
 }
 
+namespace conv_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_float_2_relaxed test
+#include "examples/conv_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/conv_float_2_relaxed.model.cpp"
+} // namespace conv_float_2_relaxed
+TEST_F(NeuralnetworksHidlTest, conv_float_2_relaxed) {
+    generated_tests::Execute(device,
+                             conv_float_2_relaxed::createTestModel,
+                             conv_float_2_relaxed::is_ignored,
+                             conv_float_2_relaxed::examples);
+}
+
 namespace conv_float_channels_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated conv_float_channels_relaxed test
@@ -361,6 +421,51 @@ TEST_F(NeuralnetworksHidlTest, depth_to_space_float_3_relaxed) {
                              depth_to_space_float_3_relaxed::examples);
 }
 
+namespace depthwise_conv2d_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depthwise_conv2d_float_2_relaxed test
+#include "examples/depthwise_conv2d_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/depthwise_conv2d_float_2_relaxed.model.cpp"
+} // namespace depthwise_conv2d_float_2_relaxed
+TEST_F(NeuralnetworksHidlTest, depthwise_conv2d_float_2_relaxed) {
+    generated_tests::Execute(device,
+                             depthwise_conv2d_float_2_relaxed::createTestModel,
+                             depthwise_conv2d_float_2_relaxed::is_ignored,
+                             depthwise_conv2d_float_2_relaxed::examples);
+}
+
+namespace depthwise_conv2d_float_large_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depthwise_conv2d_float_large_2_relaxed test
+#include "examples/depthwise_conv2d_float_large_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/depthwise_conv2d_float_large_2_relaxed.model.cpp"
+} // namespace depthwise_conv2d_float_large_2_relaxed
+TEST_F(NeuralnetworksHidlTest, depthwise_conv2d_float_large_2_relaxed) {
+    generated_tests::Execute(device,
+                             depthwise_conv2d_float_large_2_relaxed::createTestModel,
+                             depthwise_conv2d_float_large_2_relaxed::is_ignored,
+                             depthwise_conv2d_float_large_2_relaxed::examples);
+}
+
+namespace depthwise_conv2d_float_large_2_weights_as_inputs_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depthwise_conv2d_float_large_2_weights_as_inputs_relaxed test
+#include "examples/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.model.cpp"
+} // namespace depthwise_conv2d_float_large_2_weights_as_inputs_relaxed
+TEST_F(NeuralnetworksHidlTest, depthwise_conv2d_float_large_2_weights_as_inputs_relaxed) {
+    generated_tests::Execute(device,
+                             depthwise_conv2d_float_large_2_weights_as_inputs_relaxed::createTestModel,
+                             depthwise_conv2d_float_large_2_weights_as_inputs_relaxed::is_ignored,
+                             depthwise_conv2d_float_large_2_weights_as_inputs_relaxed::examples);
+}
+
 namespace depthwise_conv2d_float_large_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated depthwise_conv2d_float_large_relaxed test
@@ -391,6 +496,36 @@ TEST_F(NeuralnetworksHidlTest, depthwise_conv2d_float_large_weights_as_inputs_re
                              depthwise_conv2d_float_large_weights_as_inputs_relaxed::examples);
 }
 
+namespace depthwise_conv2d_float_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depthwise_conv2d_float_relaxed test
+#include "examples/depthwise_conv2d_float_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/depthwise_conv2d_float_relaxed.model.cpp"
+} // namespace depthwise_conv2d_float_relaxed
+TEST_F(NeuralnetworksHidlTest, depthwise_conv2d_float_relaxed) {
+    generated_tests::Execute(device,
+                             depthwise_conv2d_float_relaxed::createTestModel,
+                             depthwise_conv2d_float_relaxed::is_ignored,
+                             depthwise_conv2d_float_relaxed::examples);
+}
+
+namespace depthwise_conv2d_float_weights_as_inputs_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depthwise_conv2d_float_weights_as_inputs_relaxed test
+#include "examples/depthwise_conv2d_float_weights_as_inputs_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/depthwise_conv2d_float_weights_as_inputs_relaxed.model.cpp"
+} // namespace depthwise_conv2d_float_weights_as_inputs_relaxed
+TEST_F(NeuralnetworksHidlTest, depthwise_conv2d_float_weights_as_inputs_relaxed) {
+    generated_tests::Execute(device,
+                             depthwise_conv2d_float_weights_as_inputs_relaxed::createTestModel,
+                             depthwise_conv2d_float_weights_as_inputs_relaxed::is_ignored,
+                             depthwise_conv2d_float_weights_as_inputs_relaxed::examples);
+}
+
 namespace depthwise_conv_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated depthwise_conv_relaxed test
@@ -406,6 +541,21 @@ TEST_F(NeuralnetworksHidlTest, depthwise_conv_relaxed) {
                              depthwise_conv_relaxed::examples);
 }
 
+namespace dequantize_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated dequantize_relaxed test
+#include "examples/dequantize_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/dequantize_relaxed.model.cpp"
+} // namespace dequantize_relaxed
+TEST_F(NeuralnetworksHidlTest, dequantize_relaxed) {
+    generated_tests::Execute(device,
+                             dequantize_relaxed::createTestModel,
+                             dequantize_relaxed::is_ignored,
+                             dequantize_relaxed::examples);
+}
+
 namespace div_broadcast_float {
 std::vector<MixedTypedExample> examples = {
 // Generated div_broadcast_float test
@@ -421,6 +571,21 @@ TEST_F(NeuralnetworksHidlTest, div_broadcast_float) {
                              div_broadcast_float::examples);
 }
 
+namespace div_broadcast_float_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated div_broadcast_float_relaxed test
+#include "examples/div_broadcast_float_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/div_broadcast_float_relaxed.model.cpp"
+} // namespace div_broadcast_float_relaxed
+TEST_F(NeuralnetworksHidlTest, div_broadcast_float_relaxed) {
+    generated_tests::Execute(device,
+                             div_broadcast_float_relaxed::createTestModel,
+                             div_broadcast_float_relaxed::is_ignored,
+                             div_broadcast_float_relaxed::examples);
+}
+
 namespace div {
 std::vector<MixedTypedExample> examples = {
 // Generated div test
@@ -436,6 +601,21 @@ TEST_F(NeuralnetworksHidlTest, div) {
                              div::examples);
 }
 
+namespace div_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated div_relaxed test
+#include "examples/div_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/div_relaxed.model.cpp"
+} // namespace div_relaxed
+TEST_F(NeuralnetworksHidlTest, div_relaxed) {
+    generated_tests::Execute(device,
+                             div_relaxed::createTestModel,
+                             div_relaxed::is_ignored,
+                             div_relaxed::examples);
+}
+
 namespace embedding_lookup_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated embedding_lookup_relaxed test
@@ -466,6 +646,21 @@ TEST_F(NeuralnetworksHidlTest, floor_relaxed) {
                              floor_relaxed::examples);
 }
 
+namespace fully_connected_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated fully_connected_float_2_relaxed test
+#include "examples/fully_connected_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/fully_connected_float_2_relaxed.model.cpp"
+} // namespace fully_connected_float_2_relaxed
+TEST_F(NeuralnetworksHidlTest, fully_connected_float_2_relaxed) {
+    generated_tests::Execute(device,
+                             fully_connected_float_2_relaxed::createTestModel,
+                             fully_connected_float_2_relaxed::is_ignored,
+                             fully_connected_float_2_relaxed::examples);
+}
+
 namespace fully_connected_float_4d_simple {
 std::vector<MixedTypedExample> examples = {
 // Generated fully_connected_float_4d_simple test
@@ -481,6 +676,51 @@ TEST_F(NeuralnetworksHidlTest, fully_connected_float_4d_simple) {
                              fully_connected_float_4d_simple::examples);
 }
 
+namespace fully_connected_float_4d_simple_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated fully_connected_float_4d_simple_relaxed test
+#include "examples/fully_connected_float_4d_simple_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/fully_connected_float_4d_simple_relaxed.model.cpp"
+} // namespace fully_connected_float_4d_simple_relaxed
+TEST_F(NeuralnetworksHidlTest, fully_connected_float_4d_simple_relaxed) {
+    generated_tests::Execute(device,
+                             fully_connected_float_4d_simple_relaxed::createTestModel,
+                             fully_connected_float_4d_simple_relaxed::is_ignored,
+                             fully_connected_float_4d_simple_relaxed::examples);
+}
+
+namespace fully_connected_float_large_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated fully_connected_float_large_relaxed test
+#include "examples/fully_connected_float_large_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/fully_connected_float_large_relaxed.model.cpp"
+} // namespace fully_connected_float_large_relaxed
+TEST_F(NeuralnetworksHidlTest, fully_connected_float_large_relaxed) {
+    generated_tests::Execute(device,
+                             fully_connected_float_large_relaxed::createTestModel,
+                             fully_connected_float_large_relaxed::is_ignored,
+                             fully_connected_float_large_relaxed::examples);
+}
+
+namespace fully_connected_float_large_weights_as_inputs_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated fully_connected_float_large_weights_as_inputs_relaxed test
+#include "examples/fully_connected_float_large_weights_as_inputs_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/fully_connected_float_large_weights_as_inputs_relaxed.model.cpp"
+} // namespace fully_connected_float_large_weights_as_inputs_relaxed
+TEST_F(NeuralnetworksHidlTest, fully_connected_float_large_weights_as_inputs_relaxed) {
+    generated_tests::Execute(device,
+                             fully_connected_float_large_weights_as_inputs_relaxed::createTestModel,
+                             fully_connected_float_large_weights_as_inputs_relaxed::is_ignored,
+                             fully_connected_float_large_weights_as_inputs_relaxed::examples);
+}
+
 namespace fully_connected_float_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated fully_connected_float_relaxed test
@@ -526,6 +766,21 @@ TEST_F(NeuralnetworksHidlTest, hashtable_lookup_float_relaxed) {
                              hashtable_lookup_float_relaxed::examples);
 }
 
+namespace l2_normalization_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated l2_normalization_2_relaxed test
+#include "examples/l2_normalization_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/l2_normalization_2_relaxed.model.cpp"
+} // namespace l2_normalization_2_relaxed
+TEST_F(NeuralnetworksHidlTest, l2_normalization_2_relaxed) {
+    generated_tests::Execute(device,
+                             l2_normalization_2_relaxed::createTestModel,
+                             l2_normalization_2_relaxed::is_ignored,
+                             l2_normalization_2_relaxed::examples);
+}
+
 namespace l2_normalization_large_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated l2_normalization_large_relaxed test
@@ -556,6 +811,36 @@ TEST_F(NeuralnetworksHidlTest, l2_normalization_relaxed) {
                              l2_normalization_relaxed::examples);
 }
 
+namespace l2_pool_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated l2_pool_float_2_relaxed test
+#include "examples/l2_pool_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/l2_pool_float_2_relaxed.model.cpp"
+} // namespace l2_pool_float_2_relaxed
+TEST_F(NeuralnetworksHidlTest, l2_pool_float_2_relaxed) {
+    generated_tests::Execute(device,
+                             l2_pool_float_2_relaxed::createTestModel,
+                             l2_pool_float_2_relaxed::is_ignored,
+                             l2_pool_float_2_relaxed::examples);
+}
+
+namespace l2_pool_float_large_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated l2_pool_float_large_relaxed test
+#include "examples/l2_pool_float_large_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/l2_pool_float_large_relaxed.model.cpp"
+} // namespace l2_pool_float_large_relaxed
+TEST_F(NeuralnetworksHidlTest, l2_pool_float_large_relaxed) {
+    generated_tests::Execute(device,
+                             l2_pool_float_large_relaxed::createTestModel,
+                             l2_pool_float_large_relaxed::is_ignored,
+                             l2_pool_float_large_relaxed::examples);
+}
+
 namespace l2_pool_float_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated l2_pool_float_relaxed test
@@ -901,6 +1186,21 @@ TEST_F(NeuralnetworksHidlTest, max_pool_float_3_relaxed) {
                              max_pool_float_3_relaxed::examples);
 }
 
+namespace max_pool_float_4_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated max_pool_float_4_relaxed test
+#include "examples/max_pool_float_4_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/max_pool_float_4_relaxed.model.cpp"
+} // namespace max_pool_float_4_relaxed
+TEST_F(NeuralnetworksHidlTest, max_pool_float_4_relaxed) {
+    generated_tests::Execute(device,
+                             max_pool_float_4_relaxed::createTestModel,
+                             max_pool_float_4_relaxed::is_ignored,
+                             max_pool_float_4_relaxed::examples);
+}
+
 namespace mean_float_1 {
 std::vector<MixedTypedExample> examples = {
 // Generated mean_float_1 test
@@ -916,6 +1216,21 @@ TEST_F(NeuralnetworksHidlTest, mean_float_1) {
                              mean_float_1::examples);
 }
 
+namespace mean_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated mean_float_1_relaxed test
+#include "examples/mean_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/mean_float_1_relaxed.model.cpp"
+} // namespace mean_float_1_relaxed
+TEST_F(NeuralnetworksHidlTest, mean_float_1_relaxed) {
+    generated_tests::Execute(device,
+                             mean_float_1_relaxed::createTestModel,
+                             mean_float_1_relaxed::is_ignored,
+                             mean_float_1_relaxed::examples);
+}
+
 namespace mean_float_2 {
 std::vector<MixedTypedExample> examples = {
 // Generated mean_float_2 test
@@ -931,6 +1246,21 @@ TEST_F(NeuralnetworksHidlTest, mean_float_2) {
                              mean_float_2::examples);
 }
 
+namespace mean_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated mean_float_2_relaxed test
+#include "examples/mean_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/mean_float_2_relaxed.model.cpp"
+} // namespace mean_float_2_relaxed
+TEST_F(NeuralnetworksHidlTest, mean_float_2_relaxed) {
+    generated_tests::Execute(device,
+                             mean_float_2_relaxed::createTestModel,
+                             mean_float_2_relaxed::is_ignored,
+                             mean_float_2_relaxed::examples);
+}
+
 namespace mean {
 std::vector<MixedTypedExample> examples = {
 // Generated mean test
@@ -976,6 +1306,21 @@ TEST_F(NeuralnetworksHidlTest, mean_quant8_2) {
                              mean_quant8_2::examples);
 }
 
+namespace mean_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated mean_relaxed test
+#include "examples/mean_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/mean_relaxed.model.cpp"
+} // namespace mean_relaxed
+TEST_F(NeuralnetworksHidlTest, mean_relaxed) {
+    generated_tests::Execute(device,
+                             mean_relaxed::createTestModel,
+                             mean_relaxed::is_ignored,
+                             mean_relaxed::examples);
+}
+
 namespace mobilenet_224_gender_basic_fixed_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated mobilenet_224_gender_basic_fixed_relaxed test
@@ -1036,6 +1381,21 @@ TEST_F(NeuralnetworksHidlTest, pad_float_1) {
                              pad_float_1::examples);
 }
 
+namespace pad_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated pad_float_1_relaxed test
+#include "examples/pad_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/pad_float_1_relaxed.model.cpp"
+} // namespace pad_float_1_relaxed
+TEST_F(NeuralnetworksHidlTest, pad_float_1_relaxed) {
+    generated_tests::Execute(device,
+                             pad_float_1_relaxed::createTestModel,
+                             pad_float_1_relaxed::is_ignored,
+                             pad_float_1_relaxed::examples);
+}
+
 namespace pad {
 std::vector<MixedTypedExample> examples = {
 // Generated pad test
@@ -1051,6 +1411,21 @@ TEST_F(NeuralnetworksHidlTest, pad) {
                              pad::examples);
 }
 
+namespace pad_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated pad_relaxed test
+#include "examples/pad_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/pad_relaxed.model.cpp"
+} // namespace pad_relaxed
+TEST_F(NeuralnetworksHidlTest, pad_relaxed) {
+    generated_tests::Execute(device,
+                             pad_relaxed::createTestModel,
+                             pad_relaxed::is_ignored,
+                             pad_relaxed::examples);
+}
+
 namespace relu1_float_1_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated relu1_float_1_relaxed test
@@ -1126,6 +1501,21 @@ TEST_F(NeuralnetworksHidlTest, relu_float_1_relaxed) {
                              relu_float_1_relaxed::examples);
 }
 
+namespace relu_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated relu_float_2_relaxed test
+#include "examples/relu_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/relu_float_2_relaxed.model.cpp"
+} // namespace relu_float_2_relaxed
+TEST_F(NeuralnetworksHidlTest, relu_float_2_relaxed) {
+    generated_tests::Execute(device,
+                             relu_float_2_relaxed::createTestModel,
+                             relu_float_2_relaxed::is_ignored,
+                             relu_float_2_relaxed::examples);
+}
+
 namespace reshape_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated reshape_relaxed test
@@ -1156,6 +1546,21 @@ TEST_F(NeuralnetworksHidlTest, reshape_weights_as_inputs_relaxed) {
                              reshape_weights_as_inputs_relaxed::examples);
 }
 
+namespace resize_bilinear_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated resize_bilinear_2_relaxed test
+#include "examples/resize_bilinear_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/resize_bilinear_2_relaxed.model.cpp"
+} // namespace resize_bilinear_2_relaxed
+TEST_F(NeuralnetworksHidlTest, resize_bilinear_2_relaxed) {
+    generated_tests::Execute(device,
+                             resize_bilinear_2_relaxed::createTestModel,
+                             resize_bilinear_2_relaxed::is_ignored,
+                             resize_bilinear_2_relaxed::examples);
+}
+
 namespace resize_bilinear_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated resize_bilinear_relaxed test
@@ -1246,6 +1651,21 @@ TEST_F(NeuralnetworksHidlTest, space_to_batch_float_1) {
                              space_to_batch_float_1::examples);
 }
 
+namespace space_to_batch_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated space_to_batch_float_1_relaxed test
+#include "examples/space_to_batch_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/space_to_batch_float_1_relaxed.model.cpp"
+} // namespace space_to_batch_float_1_relaxed
+TEST_F(NeuralnetworksHidlTest, space_to_batch_float_1_relaxed) {
+    generated_tests::Execute(device,
+                             space_to_batch_float_1_relaxed::createTestModel,
+                             space_to_batch_float_1_relaxed::is_ignored,
+                             space_to_batch_float_1_relaxed::examples);
+}
+
 namespace space_to_batch_float_2 {
 std::vector<MixedTypedExample> examples = {
 // Generated space_to_batch_float_2 test
@@ -1261,6 +1681,21 @@ TEST_F(NeuralnetworksHidlTest, space_to_batch_float_2) {
                              space_to_batch_float_2::examples);
 }
 
+namespace space_to_batch_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated space_to_batch_float_2_relaxed test
+#include "examples/space_to_batch_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/space_to_batch_float_2_relaxed.model.cpp"
+} // namespace space_to_batch_float_2_relaxed
+TEST_F(NeuralnetworksHidlTest, space_to_batch_float_2_relaxed) {
+    generated_tests::Execute(device,
+                             space_to_batch_float_2_relaxed::createTestModel,
+                             space_to_batch_float_2_relaxed::is_ignored,
+                             space_to_batch_float_2_relaxed::examples);
+}
+
 namespace space_to_batch_float_3 {
 std::vector<MixedTypedExample> examples = {
 // Generated space_to_batch_float_3 test
@@ -1276,6 +1711,21 @@ TEST_F(NeuralnetworksHidlTest, space_to_batch_float_3) {
                              space_to_batch_float_3::examples);
 }
 
+namespace space_to_batch_float_3_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated space_to_batch_float_3_relaxed test
+#include "examples/space_to_batch_float_3_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/space_to_batch_float_3_relaxed.model.cpp"
+} // namespace space_to_batch_float_3_relaxed
+TEST_F(NeuralnetworksHidlTest, space_to_batch_float_3_relaxed) {
+    generated_tests::Execute(device,
+                             space_to_batch_float_3_relaxed::createTestModel,
+                             space_to_batch_float_3_relaxed::is_ignored,
+                             space_to_batch_float_3_relaxed::examples);
+}
+
 namespace space_to_batch {
 std::vector<MixedTypedExample> examples = {
 // Generated space_to_batch test
@@ -1336,6 +1786,21 @@ TEST_F(NeuralnetworksHidlTest, space_to_batch_quant8_3) {
                              space_to_batch_quant8_3::examples);
 }
 
+namespace space_to_batch_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated space_to_batch_relaxed test
+#include "examples/space_to_batch_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/space_to_batch_relaxed.model.cpp"
+} // namespace space_to_batch_relaxed
+TEST_F(NeuralnetworksHidlTest, space_to_batch_relaxed) {
+    generated_tests::Execute(device,
+                             space_to_batch_relaxed::createTestModel,
+                             space_to_batch_relaxed::is_ignored,
+                             space_to_batch_relaxed::examples);
+}
+
 namespace space_to_depth_float_1_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated space_to_depth_float_1_relaxed test
@@ -1396,6 +1861,21 @@ TEST_F(NeuralnetworksHidlTest, squeeze_float_1) {
                              squeeze_float_1::examples);
 }
 
+namespace squeeze_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated squeeze_float_1_relaxed test
+#include "examples/squeeze_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/squeeze_float_1_relaxed.model.cpp"
+} // namespace squeeze_float_1_relaxed
+TEST_F(NeuralnetworksHidlTest, squeeze_float_1_relaxed) {
+    generated_tests::Execute(device,
+                             squeeze_float_1_relaxed::createTestModel,
+                             squeeze_float_1_relaxed::is_ignored,
+                             squeeze_float_1_relaxed::examples);
+}
+
 namespace squeeze {
 std::vector<MixedTypedExample> examples = {
 // Generated squeeze test
@@ -1426,6 +1906,21 @@ TEST_F(NeuralnetworksHidlTest, squeeze_quant8_1) {
                              squeeze_quant8_1::examples);
 }
 
+namespace squeeze_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated squeeze_relaxed test
+#include "examples/squeeze_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/squeeze_relaxed.model.cpp"
+} // namespace squeeze_relaxed
+TEST_F(NeuralnetworksHidlTest, squeeze_relaxed) {
+    generated_tests::Execute(device,
+                             squeeze_relaxed::createTestModel,
+                             squeeze_relaxed::is_ignored,
+                             squeeze_relaxed::examples);
+}
+
 namespace strided_slice_float_10 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_10 test
@@ -1441,6 +1936,21 @@ TEST_F(NeuralnetworksHidlTest, strided_slice_float_10) {
                              strided_slice_float_10::examples);
 }
 
+namespace strided_slice_float_10_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_10_relaxed test
+#include "examples/strided_slice_float_10_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/strided_slice_float_10_relaxed.model.cpp"
+} // namespace strided_slice_float_10_relaxed
+TEST_F(NeuralnetworksHidlTest, strided_slice_float_10_relaxed) {
+    generated_tests::Execute(device,
+                             strided_slice_float_10_relaxed::createTestModel,
+                             strided_slice_float_10_relaxed::is_ignored,
+                             strided_slice_float_10_relaxed::examples);
+}
+
 namespace strided_slice_float_11 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_11 test
@@ -1456,6 +1966,21 @@ TEST_F(NeuralnetworksHidlTest, strided_slice_float_11) {
                              strided_slice_float_11::examples);
 }
 
+namespace strided_slice_float_11_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_11_relaxed test
+#include "examples/strided_slice_float_11_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/strided_slice_float_11_relaxed.model.cpp"
+} // namespace strided_slice_float_11_relaxed
+TEST_F(NeuralnetworksHidlTest, strided_slice_float_11_relaxed) {
+    generated_tests::Execute(device,
+                             strided_slice_float_11_relaxed::createTestModel,
+                             strided_slice_float_11_relaxed::is_ignored,
+                             strided_slice_float_11_relaxed::examples);
+}
+
 namespace strided_slice_float_1 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_1 test
@@ -1471,6 +1996,21 @@ TEST_F(NeuralnetworksHidlTest, strided_slice_float_1) {
                              strided_slice_float_1::examples);
 }
 
+namespace strided_slice_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_1_relaxed test
+#include "examples/strided_slice_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/strided_slice_float_1_relaxed.model.cpp"
+} // namespace strided_slice_float_1_relaxed
+TEST_F(NeuralnetworksHidlTest, strided_slice_float_1_relaxed) {
+    generated_tests::Execute(device,
+                             strided_slice_float_1_relaxed::createTestModel,
+                             strided_slice_float_1_relaxed::is_ignored,
+                             strided_slice_float_1_relaxed::examples);
+}
+
 namespace strided_slice_float_2 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_2 test
@@ -1486,6 +2026,21 @@ TEST_F(NeuralnetworksHidlTest, strided_slice_float_2) {
                              strided_slice_float_2::examples);
 }
 
+namespace strided_slice_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_2_relaxed test
+#include "examples/strided_slice_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/strided_slice_float_2_relaxed.model.cpp"
+} // namespace strided_slice_float_2_relaxed
+TEST_F(NeuralnetworksHidlTest, strided_slice_float_2_relaxed) {
+    generated_tests::Execute(device,
+                             strided_slice_float_2_relaxed::createTestModel,
+                             strided_slice_float_2_relaxed::is_ignored,
+                             strided_slice_float_2_relaxed::examples);
+}
+
 namespace strided_slice_float_3 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_3 test
@@ -1501,6 +2056,21 @@ TEST_F(NeuralnetworksHidlTest, strided_slice_float_3) {
                              strided_slice_float_3::examples);
 }
 
+namespace strided_slice_float_3_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_3_relaxed test
+#include "examples/strided_slice_float_3_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/strided_slice_float_3_relaxed.model.cpp"
+} // namespace strided_slice_float_3_relaxed
+TEST_F(NeuralnetworksHidlTest, strided_slice_float_3_relaxed) {
+    generated_tests::Execute(device,
+                             strided_slice_float_3_relaxed::createTestModel,
+                             strided_slice_float_3_relaxed::is_ignored,
+                             strided_slice_float_3_relaxed::examples);
+}
+
 namespace strided_slice_float_4 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_4 test
@@ -1516,6 +2086,21 @@ TEST_F(NeuralnetworksHidlTest, strided_slice_float_4) {
                              strided_slice_float_4::examples);
 }
 
+namespace strided_slice_float_4_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_4_relaxed test
+#include "examples/strided_slice_float_4_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/strided_slice_float_4_relaxed.model.cpp"
+} // namespace strided_slice_float_4_relaxed
+TEST_F(NeuralnetworksHidlTest, strided_slice_float_4_relaxed) {
+    generated_tests::Execute(device,
+                             strided_slice_float_4_relaxed::createTestModel,
+                             strided_slice_float_4_relaxed::is_ignored,
+                             strided_slice_float_4_relaxed::examples);
+}
+
 namespace strided_slice_float_5 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_5 test
@@ -1531,6 +2116,21 @@ TEST_F(NeuralnetworksHidlTest, strided_slice_float_5) {
                              strided_slice_float_5::examples);
 }
 
+namespace strided_slice_float_5_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_5_relaxed test
+#include "examples/strided_slice_float_5_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/strided_slice_float_5_relaxed.model.cpp"
+} // namespace strided_slice_float_5_relaxed
+TEST_F(NeuralnetworksHidlTest, strided_slice_float_5_relaxed) {
+    generated_tests::Execute(device,
+                             strided_slice_float_5_relaxed::createTestModel,
+                             strided_slice_float_5_relaxed::is_ignored,
+                             strided_slice_float_5_relaxed::examples);
+}
+
 namespace strided_slice_float_6 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_6 test
@@ -1546,6 +2146,21 @@ TEST_F(NeuralnetworksHidlTest, strided_slice_float_6) {
                              strided_slice_float_6::examples);
 }
 
+namespace strided_slice_float_6_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_6_relaxed test
+#include "examples/strided_slice_float_6_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/strided_slice_float_6_relaxed.model.cpp"
+} // namespace strided_slice_float_6_relaxed
+TEST_F(NeuralnetworksHidlTest, strided_slice_float_6_relaxed) {
+    generated_tests::Execute(device,
+                             strided_slice_float_6_relaxed::createTestModel,
+                             strided_slice_float_6_relaxed::is_ignored,
+                             strided_slice_float_6_relaxed::examples);
+}
+
 namespace strided_slice_float_7 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_7 test
@@ -1561,6 +2176,21 @@ TEST_F(NeuralnetworksHidlTest, strided_slice_float_7) {
                              strided_slice_float_7::examples);
 }
 
+namespace strided_slice_float_7_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_7_relaxed test
+#include "examples/strided_slice_float_7_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/strided_slice_float_7_relaxed.model.cpp"
+} // namespace strided_slice_float_7_relaxed
+TEST_F(NeuralnetworksHidlTest, strided_slice_float_7_relaxed) {
+    generated_tests::Execute(device,
+                             strided_slice_float_7_relaxed::createTestModel,
+                             strided_slice_float_7_relaxed::is_ignored,
+                             strided_slice_float_7_relaxed::examples);
+}
+
 namespace strided_slice_float_8 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_8 test
@@ -1576,6 +2206,21 @@ TEST_F(NeuralnetworksHidlTest, strided_slice_float_8) {
                              strided_slice_float_8::examples);
 }
 
+namespace strided_slice_float_8_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_8_relaxed test
+#include "examples/strided_slice_float_8_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/strided_slice_float_8_relaxed.model.cpp"
+} // namespace strided_slice_float_8_relaxed
+TEST_F(NeuralnetworksHidlTest, strided_slice_float_8_relaxed) {
+    generated_tests::Execute(device,
+                             strided_slice_float_8_relaxed::createTestModel,
+                             strided_slice_float_8_relaxed::is_ignored,
+                             strided_slice_float_8_relaxed::examples);
+}
+
 namespace strided_slice_float_9 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_9 test
@@ -1591,6 +2236,21 @@ TEST_F(NeuralnetworksHidlTest, strided_slice_float_9) {
                              strided_slice_float_9::examples);
 }
 
+namespace strided_slice_float_9_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_9_relaxed test
+#include "examples/strided_slice_float_9_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/strided_slice_float_9_relaxed.model.cpp"
+} // namespace strided_slice_float_9_relaxed
+TEST_F(NeuralnetworksHidlTest, strided_slice_float_9_relaxed) {
+    generated_tests::Execute(device,
+                             strided_slice_float_9_relaxed::createTestModel,
+                             strided_slice_float_9_relaxed::is_ignored,
+                             strided_slice_float_9_relaxed::examples);
+}
+
 namespace strided_slice {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice test
@@ -1771,6 +2431,21 @@ TEST_F(NeuralnetworksHidlTest, strided_slice_quant8_9) {
                              strided_slice_quant8_9::examples);
 }
 
+namespace strided_slice_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_relaxed test
+#include "examples/strided_slice_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/strided_slice_relaxed.model.cpp"
+} // namespace strided_slice_relaxed
+TEST_F(NeuralnetworksHidlTest, strided_slice_relaxed) {
+    generated_tests::Execute(device,
+                             strided_slice_relaxed::createTestModel,
+                             strided_slice_relaxed::is_ignored,
+                             strided_slice_relaxed::examples);
+}
+
 namespace sub_broadcast_float {
 std::vector<MixedTypedExample> examples = {
 // Generated sub_broadcast_float test
@@ -1786,6 +2461,21 @@ TEST_F(NeuralnetworksHidlTest, sub_broadcast_float) {
                              sub_broadcast_float::examples);
 }
 
+namespace sub_broadcast_float_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated sub_broadcast_float_relaxed test
+#include "examples/sub_broadcast_float_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/sub_broadcast_float_relaxed.model.cpp"
+} // namespace sub_broadcast_float_relaxed
+TEST_F(NeuralnetworksHidlTest, sub_broadcast_float_relaxed) {
+    generated_tests::Execute(device,
+                             sub_broadcast_float_relaxed::createTestModel,
+                             sub_broadcast_float_relaxed::is_ignored,
+                             sub_broadcast_float_relaxed::examples);
+}
+
 namespace sub {
 std::vector<MixedTypedExample> examples = {
 // Generated sub test
@@ -1801,6 +2491,21 @@ TEST_F(NeuralnetworksHidlTest, sub) {
                              sub::examples);
 }
 
+namespace sub_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated sub_relaxed test
+#include "examples/sub_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/sub_relaxed.model.cpp"
+} // namespace sub_relaxed
+TEST_F(NeuralnetworksHidlTest, sub_relaxed) {
+    generated_tests::Execute(device,
+                             sub_relaxed::createTestModel,
+                             sub_relaxed::is_ignored,
+                             sub_relaxed::examples);
+}
+
 namespace svdf2_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated svdf2_relaxed test
@@ -1876,6 +2581,21 @@ TEST_F(NeuralnetworksHidlTest, transpose_float_1) {
                              transpose_float_1::examples);
 }
 
+namespace transpose_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated transpose_float_1_relaxed test
+#include "examples/transpose_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/transpose_float_1_relaxed.model.cpp"
+} // namespace transpose_float_1_relaxed
+TEST_F(NeuralnetworksHidlTest, transpose_float_1_relaxed) {
+    generated_tests::Execute(device,
+                             transpose_float_1_relaxed::createTestModel,
+                             transpose_float_1_relaxed::is_ignored,
+                             transpose_float_1_relaxed::examples);
+}
+
 namespace transpose {
 std::vector<MixedTypedExample> examples = {
 // Generated transpose test
@@ -1905,3 +2625,18 @@ TEST_F(NeuralnetworksHidlTest, transpose_quant8_1) {
                              transpose_quant8_1::is_ignored,
                              transpose_quant8_1::examples);
 }
+
+namespace transpose_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated transpose_relaxed test
+#include "examples/transpose_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "vts_models/transpose_relaxed.model.cpp"
+} // namespace transpose_relaxed
+TEST_F(NeuralnetworksHidlTest, transpose_relaxed) {
+    generated_tests::Execute(device,
+                             transpose_relaxed::createTestModel,
+                             transpose_relaxed::is_ignored,
+                             transpose_relaxed::examples);
+}
diff --git a/nn/runtime/test/generated/all_generated_tests.cpp b/nn/runtime/test/generated/all_generated_tests.cpp
index 240f9193d..1a20a5ac2 100644
--- a/nn/runtime/test/generated/all_generated_tests.cpp
+++ b/nn/runtime/test/generated/all_generated_tests.cpp
@@ -2115,6 +2115,20 @@ TEST_F(GeneratedTests, avg_pool_float_4_relaxed) {
             avg_pool_float_4_relaxed::examples);
 }
 
+namespace avg_pool_float_5_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated avg_pool_float_5_relaxed test
+#include "generated/examples/avg_pool_float_5_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/avg_pool_float_5_relaxed.model.cpp"
+} // namespace avg_pool_float_5_relaxed
+TEST_F(GeneratedTests, avg_pool_float_5_relaxed) {
+    execute(avg_pool_float_5_relaxed::CreateModel,
+            avg_pool_float_5_relaxed::is_ignored,
+            avg_pool_float_5_relaxed::examples);
+}
+
 namespace batch_to_space_float_1 {
 std::vector<MixedTypedExample> examples = {
 // Generated batch_to_space_float_1 test
@@ -2129,6 +2143,20 @@ TEST_F(GeneratedTests, batch_to_space_float_1) {
             batch_to_space_float_1::examples);
 }
 
+namespace batch_to_space_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated batch_to_space_float_1_relaxed test
+#include "generated/examples/batch_to_space_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/batch_to_space_float_1_relaxed.model.cpp"
+} // namespace batch_to_space_float_1_relaxed
+TEST_F(GeneratedTests, batch_to_space_float_1_relaxed) {
+    execute(batch_to_space_float_1_relaxed::CreateModel,
+            batch_to_space_float_1_relaxed::is_ignored,
+            batch_to_space_float_1_relaxed::examples);
+}
+
 namespace batch_to_space {
 std::vector<MixedTypedExample> examples = {
 // Generated batch_to_space test
@@ -2157,6 +2185,20 @@ TEST_F(GeneratedTests, batch_to_space_quant8_1) {
             batch_to_space_quant8_1::examples);
 }
 
+namespace batch_to_space_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated batch_to_space_relaxed test
+#include "generated/examples/batch_to_space_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/batch_to_space_relaxed.model.cpp"
+} // namespace batch_to_space_relaxed
+TEST_F(GeneratedTests, batch_to_space_relaxed) {
+    execute(batch_to_space_relaxed::CreateModel,
+            batch_to_space_relaxed::is_ignored,
+            batch_to_space_relaxed::examples);
+}
+
 namespace concat_float_1_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated concat_float_1_relaxed test
@@ -2255,6 +2297,20 @@ TEST_F(GeneratedTests, conv_3_h3_w2_VALID_relaxed) {
             conv_3_h3_w2_VALID_relaxed::examples);
 }
 
+namespace conv_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated conv_float_2_relaxed test
+#include "generated/examples/conv_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/conv_float_2_relaxed.model.cpp"
+} // namespace conv_float_2_relaxed
+TEST_F(GeneratedTests, conv_float_2_relaxed) {
+    execute(conv_float_2_relaxed::CreateModel,
+            conv_float_2_relaxed::is_ignored,
+            conv_float_2_relaxed::examples);
+}
+
 namespace conv_float_channels_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated conv_float_channels_relaxed test
@@ -2381,6 +2437,48 @@ TEST_F(GeneratedTests, depth_to_space_float_3_relaxed) {
             depth_to_space_float_3_relaxed::examples);
 }
 
+namespace depthwise_conv2d_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depthwise_conv2d_float_2_relaxed test
+#include "generated/examples/depthwise_conv2d_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/depthwise_conv2d_float_2_relaxed.model.cpp"
+} // namespace depthwise_conv2d_float_2_relaxed
+TEST_F(GeneratedTests, depthwise_conv2d_float_2_relaxed) {
+    execute(depthwise_conv2d_float_2_relaxed::CreateModel,
+            depthwise_conv2d_float_2_relaxed::is_ignored,
+            depthwise_conv2d_float_2_relaxed::examples);
+}
+
+namespace depthwise_conv2d_float_large_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depthwise_conv2d_float_large_2_relaxed test
+#include "generated/examples/depthwise_conv2d_float_large_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/depthwise_conv2d_float_large_2_relaxed.model.cpp"
+} // namespace depthwise_conv2d_float_large_2_relaxed
+TEST_F(GeneratedTests, depthwise_conv2d_float_large_2_relaxed) {
+    execute(depthwise_conv2d_float_large_2_relaxed::CreateModel,
+            depthwise_conv2d_float_large_2_relaxed::is_ignored,
+            depthwise_conv2d_float_large_2_relaxed::examples);
+}
+
+namespace depthwise_conv2d_float_large_2_weights_as_inputs_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depthwise_conv2d_float_large_2_weights_as_inputs_relaxed test
+#include "generated/examples/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.model.cpp"
+} // namespace depthwise_conv2d_float_large_2_weights_as_inputs_relaxed
+TEST_F(GeneratedTests, depthwise_conv2d_float_large_2_weights_as_inputs_relaxed) {
+    execute(depthwise_conv2d_float_large_2_weights_as_inputs_relaxed::CreateModel,
+            depthwise_conv2d_float_large_2_weights_as_inputs_relaxed::is_ignored,
+            depthwise_conv2d_float_large_2_weights_as_inputs_relaxed::examples);
+}
+
 namespace depthwise_conv2d_float_large_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated depthwise_conv2d_float_large_relaxed test
@@ -2409,6 +2507,34 @@ TEST_F(GeneratedTests, depthwise_conv2d_float_large_weights_as_inputs_relaxed) {
             depthwise_conv2d_float_large_weights_as_inputs_relaxed::examples);
 }
 
+namespace depthwise_conv2d_float_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depthwise_conv2d_float_relaxed test
+#include "generated/examples/depthwise_conv2d_float_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/depthwise_conv2d_float_relaxed.model.cpp"
+} // namespace depthwise_conv2d_float_relaxed
+TEST_F(GeneratedTests, depthwise_conv2d_float_relaxed) {
+    execute(depthwise_conv2d_float_relaxed::CreateModel,
+            depthwise_conv2d_float_relaxed::is_ignored,
+            depthwise_conv2d_float_relaxed::examples);
+}
+
+namespace depthwise_conv2d_float_weights_as_inputs_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated depthwise_conv2d_float_weights_as_inputs_relaxed test
+#include "generated/examples/depthwise_conv2d_float_weights_as_inputs_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/depthwise_conv2d_float_weights_as_inputs_relaxed.model.cpp"
+} // namespace depthwise_conv2d_float_weights_as_inputs_relaxed
+TEST_F(GeneratedTests, depthwise_conv2d_float_weights_as_inputs_relaxed) {
+    execute(depthwise_conv2d_float_weights_as_inputs_relaxed::CreateModel,
+            depthwise_conv2d_float_weights_as_inputs_relaxed::is_ignored,
+            depthwise_conv2d_float_weights_as_inputs_relaxed::examples);
+}
+
 namespace depthwise_conv_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated depthwise_conv_relaxed test
@@ -2423,6 +2549,20 @@ TEST_F(GeneratedTests, depthwise_conv_relaxed) {
             depthwise_conv_relaxed::examples);
 }
 
+namespace dequantize_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated dequantize_relaxed test
+#include "generated/examples/dequantize_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/dequantize_relaxed.model.cpp"
+} // namespace dequantize_relaxed
+TEST_F(GeneratedTests, dequantize_relaxed) {
+    execute(dequantize_relaxed::CreateModel,
+            dequantize_relaxed::is_ignored,
+            dequantize_relaxed::examples);
+}
+
 namespace div_broadcast_float {
 std::vector<MixedTypedExample> examples = {
 // Generated div_broadcast_float test
@@ -2437,6 +2577,20 @@ TEST_F(GeneratedTests, div_broadcast_float) {
             div_broadcast_float::examples);
 }
 
+namespace div_broadcast_float_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated div_broadcast_float_relaxed test
+#include "generated/examples/div_broadcast_float_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/div_broadcast_float_relaxed.model.cpp"
+} // namespace div_broadcast_float_relaxed
+TEST_F(GeneratedTests, div_broadcast_float_relaxed) {
+    execute(div_broadcast_float_relaxed::CreateModel,
+            div_broadcast_float_relaxed::is_ignored,
+            div_broadcast_float_relaxed::examples);
+}
+
 namespace div {
 std::vector<MixedTypedExample> examples = {
 // Generated div test
@@ -2451,6 +2605,20 @@ TEST_F(GeneratedTests, div) {
             div::examples);
 }
 
+namespace div_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated div_relaxed test
+#include "generated/examples/div_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/div_relaxed.model.cpp"
+} // namespace div_relaxed
+TEST_F(GeneratedTests, div_relaxed) {
+    execute(div_relaxed::CreateModel,
+            div_relaxed::is_ignored,
+            div_relaxed::examples);
+}
+
 namespace embedding_lookup_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated embedding_lookup_relaxed test
@@ -2479,6 +2647,20 @@ TEST_F(GeneratedTests, floor_relaxed) {
             floor_relaxed::examples);
 }
 
+namespace fully_connected_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated fully_connected_float_2_relaxed test
+#include "generated/examples/fully_connected_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/fully_connected_float_2_relaxed.model.cpp"
+} // namespace fully_connected_float_2_relaxed
+TEST_F(GeneratedTests, fully_connected_float_2_relaxed) {
+    execute(fully_connected_float_2_relaxed::CreateModel,
+            fully_connected_float_2_relaxed::is_ignored,
+            fully_connected_float_2_relaxed::examples);
+}
+
 namespace fully_connected_float_4d_simple {
 std::vector<MixedTypedExample> examples = {
 // Generated fully_connected_float_4d_simple test
@@ -2493,6 +2675,48 @@ TEST_F(GeneratedTests, fully_connected_float_4d_simple) {
             fully_connected_float_4d_simple::examples);
 }
 
+namespace fully_connected_float_4d_simple_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated fully_connected_float_4d_simple_relaxed test
+#include "generated/examples/fully_connected_float_4d_simple_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/fully_connected_float_4d_simple_relaxed.model.cpp"
+} // namespace fully_connected_float_4d_simple_relaxed
+TEST_F(GeneratedTests, fully_connected_float_4d_simple_relaxed) {
+    execute(fully_connected_float_4d_simple_relaxed::CreateModel,
+            fully_connected_float_4d_simple_relaxed::is_ignored,
+            fully_connected_float_4d_simple_relaxed::examples);
+}
+
+namespace fully_connected_float_large_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated fully_connected_float_large_relaxed test
+#include "generated/examples/fully_connected_float_large_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/fully_connected_float_large_relaxed.model.cpp"
+} // namespace fully_connected_float_large_relaxed
+TEST_F(GeneratedTests, fully_connected_float_large_relaxed) {
+    execute(fully_connected_float_large_relaxed::CreateModel,
+            fully_connected_float_large_relaxed::is_ignored,
+            fully_connected_float_large_relaxed::examples);
+}
+
+namespace fully_connected_float_large_weights_as_inputs_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated fully_connected_float_large_weights_as_inputs_relaxed test
+#include "generated/examples/fully_connected_float_large_weights_as_inputs_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/fully_connected_float_large_weights_as_inputs_relaxed.model.cpp"
+} // namespace fully_connected_float_large_weights_as_inputs_relaxed
+TEST_F(GeneratedTests, fully_connected_float_large_weights_as_inputs_relaxed) {
+    execute(fully_connected_float_large_weights_as_inputs_relaxed::CreateModel,
+            fully_connected_float_large_weights_as_inputs_relaxed::is_ignored,
+            fully_connected_float_large_weights_as_inputs_relaxed::examples);
+}
+
 namespace fully_connected_float_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated fully_connected_float_relaxed test
@@ -2535,6 +2759,20 @@ TEST_F(GeneratedTests, hashtable_lookup_float_relaxed) {
             hashtable_lookup_float_relaxed::examples);
 }
 
+namespace l2_normalization_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated l2_normalization_2_relaxed test
+#include "generated/examples/l2_normalization_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/l2_normalization_2_relaxed.model.cpp"
+} // namespace l2_normalization_2_relaxed
+TEST_F(GeneratedTests, l2_normalization_2_relaxed) {
+    execute(l2_normalization_2_relaxed::CreateModel,
+            l2_normalization_2_relaxed::is_ignored,
+            l2_normalization_2_relaxed::examples);
+}
+
 namespace l2_normalization_large_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated l2_normalization_large_relaxed test
@@ -2563,6 +2801,34 @@ TEST_F(GeneratedTests, l2_normalization_relaxed) {
             l2_normalization_relaxed::examples);
 }
 
+namespace l2_pool_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated l2_pool_float_2_relaxed test
+#include "generated/examples/l2_pool_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/l2_pool_float_2_relaxed.model.cpp"
+} // namespace l2_pool_float_2_relaxed
+TEST_F(GeneratedTests, l2_pool_float_2_relaxed) {
+    execute(l2_pool_float_2_relaxed::CreateModel,
+            l2_pool_float_2_relaxed::is_ignored,
+            l2_pool_float_2_relaxed::examples);
+}
+
+namespace l2_pool_float_large_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated l2_pool_float_large_relaxed test
+#include "generated/examples/l2_pool_float_large_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/l2_pool_float_large_relaxed.model.cpp"
+} // namespace l2_pool_float_large_relaxed
+TEST_F(GeneratedTests, l2_pool_float_large_relaxed) {
+    execute(l2_pool_float_large_relaxed::CreateModel,
+            l2_pool_float_large_relaxed::is_ignored,
+            l2_pool_float_large_relaxed::examples);
+}
+
 namespace l2_pool_float_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated l2_pool_float_relaxed test
@@ -2885,6 +3151,20 @@ TEST_F(GeneratedTests, max_pool_float_3_relaxed) {
             max_pool_float_3_relaxed::examples);
 }
 
+namespace max_pool_float_4_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated max_pool_float_4_relaxed test
+#include "generated/examples/max_pool_float_4_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/max_pool_float_4_relaxed.model.cpp"
+} // namespace max_pool_float_4_relaxed
+TEST_F(GeneratedTests, max_pool_float_4_relaxed) {
+    execute(max_pool_float_4_relaxed::CreateModel,
+            max_pool_float_4_relaxed::is_ignored,
+            max_pool_float_4_relaxed::examples);
+}
+
 namespace mean_float_1 {
 std::vector<MixedTypedExample> examples = {
 // Generated mean_float_1 test
@@ -2899,6 +3179,20 @@ TEST_F(GeneratedTests, mean_float_1) {
             mean_float_1::examples);
 }
 
+namespace mean_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated mean_float_1_relaxed test
+#include "generated/examples/mean_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/mean_float_1_relaxed.model.cpp"
+} // namespace mean_float_1_relaxed
+TEST_F(GeneratedTests, mean_float_1_relaxed) {
+    execute(mean_float_1_relaxed::CreateModel,
+            mean_float_1_relaxed::is_ignored,
+            mean_float_1_relaxed::examples);
+}
+
 namespace mean_float_2 {
 std::vector<MixedTypedExample> examples = {
 // Generated mean_float_2 test
@@ -2913,6 +3207,20 @@ TEST_F(GeneratedTests, mean_float_2) {
             mean_float_2::examples);
 }
 
+namespace mean_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated mean_float_2_relaxed test
+#include "generated/examples/mean_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/mean_float_2_relaxed.model.cpp"
+} // namespace mean_float_2_relaxed
+TEST_F(GeneratedTests, mean_float_2_relaxed) {
+    execute(mean_float_2_relaxed::CreateModel,
+            mean_float_2_relaxed::is_ignored,
+            mean_float_2_relaxed::examples);
+}
+
 namespace mean {
 std::vector<MixedTypedExample> examples = {
 // Generated mean test
@@ -2955,6 +3263,20 @@ TEST_F(GeneratedTests, mean_quant8_2) {
             mean_quant8_2::examples);
 }
 
+namespace mean_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated mean_relaxed test
+#include "generated/examples/mean_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/mean_relaxed.model.cpp"
+} // namespace mean_relaxed
+TEST_F(GeneratedTests, mean_relaxed) {
+    execute(mean_relaxed::CreateModel,
+            mean_relaxed::is_ignored,
+            mean_relaxed::examples);
+}
+
 namespace mobilenet_224_gender_basic_fixed_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated mobilenet_224_gender_basic_fixed_relaxed test
@@ -3011,6 +3333,20 @@ TEST_F(GeneratedTests, pad_float_1) {
             pad_float_1::examples);
 }
 
+namespace pad_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated pad_float_1_relaxed test
+#include "generated/examples/pad_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/pad_float_1_relaxed.model.cpp"
+} // namespace pad_float_1_relaxed
+TEST_F(GeneratedTests, pad_float_1_relaxed) {
+    execute(pad_float_1_relaxed::CreateModel,
+            pad_float_1_relaxed::is_ignored,
+            pad_float_1_relaxed::examples);
+}
+
 namespace pad {
 std::vector<MixedTypedExample> examples = {
 // Generated pad test
@@ -3025,6 +3361,20 @@ TEST_F(GeneratedTests, pad) {
             pad::examples);
 }
 
+namespace pad_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated pad_relaxed test
+#include "generated/examples/pad_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/pad_relaxed.model.cpp"
+} // namespace pad_relaxed
+TEST_F(GeneratedTests, pad_relaxed) {
+    execute(pad_relaxed::CreateModel,
+            pad_relaxed::is_ignored,
+            pad_relaxed::examples);
+}
+
 namespace relu1_float_1_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated relu1_float_1_relaxed test
@@ -3095,6 +3445,20 @@ TEST_F(GeneratedTests, relu_float_1_relaxed) {
             relu_float_1_relaxed::examples);
 }
 
+namespace relu_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated relu_float_2_relaxed test
+#include "generated/examples/relu_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/relu_float_2_relaxed.model.cpp"
+} // namespace relu_float_2_relaxed
+TEST_F(GeneratedTests, relu_float_2_relaxed) {
+    execute(relu_float_2_relaxed::CreateModel,
+            relu_float_2_relaxed::is_ignored,
+            relu_float_2_relaxed::examples);
+}
+
 namespace reshape_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated reshape_relaxed test
@@ -3123,6 +3487,20 @@ TEST_F(GeneratedTests, reshape_weights_as_inputs_relaxed) {
             reshape_weights_as_inputs_relaxed::examples);
 }
 
+namespace resize_bilinear_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated resize_bilinear_2_relaxed test
+#include "generated/examples/resize_bilinear_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/resize_bilinear_2_relaxed.model.cpp"
+} // namespace resize_bilinear_2_relaxed
+TEST_F(GeneratedTests, resize_bilinear_2_relaxed) {
+    execute(resize_bilinear_2_relaxed::CreateModel,
+            resize_bilinear_2_relaxed::is_ignored,
+            resize_bilinear_2_relaxed::examples);
+}
+
 namespace resize_bilinear_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated resize_bilinear_relaxed test
@@ -3207,6 +3585,20 @@ TEST_F(GeneratedTests, space_to_batch_float_1) {
             space_to_batch_float_1::examples);
 }
 
+namespace space_to_batch_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated space_to_batch_float_1_relaxed test
+#include "generated/examples/space_to_batch_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/space_to_batch_float_1_relaxed.model.cpp"
+} // namespace space_to_batch_float_1_relaxed
+TEST_F(GeneratedTests, space_to_batch_float_1_relaxed) {
+    execute(space_to_batch_float_1_relaxed::CreateModel,
+            space_to_batch_float_1_relaxed::is_ignored,
+            space_to_batch_float_1_relaxed::examples);
+}
+
 namespace space_to_batch_float_2 {
 std::vector<MixedTypedExample> examples = {
 // Generated space_to_batch_float_2 test
@@ -3221,6 +3613,20 @@ TEST_F(GeneratedTests, space_to_batch_float_2) {
             space_to_batch_float_2::examples);
 }
 
+namespace space_to_batch_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated space_to_batch_float_2_relaxed test
+#include "generated/examples/space_to_batch_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/space_to_batch_float_2_relaxed.model.cpp"
+} // namespace space_to_batch_float_2_relaxed
+TEST_F(GeneratedTests, space_to_batch_float_2_relaxed) {
+    execute(space_to_batch_float_2_relaxed::CreateModel,
+            space_to_batch_float_2_relaxed::is_ignored,
+            space_to_batch_float_2_relaxed::examples);
+}
+
 namespace space_to_batch_float_3 {
 std::vector<MixedTypedExample> examples = {
 // Generated space_to_batch_float_3 test
@@ -3235,6 +3641,20 @@ TEST_F(GeneratedTests, space_to_batch_float_3) {
             space_to_batch_float_3::examples);
 }
 
+namespace space_to_batch_float_3_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated space_to_batch_float_3_relaxed test
+#include "generated/examples/space_to_batch_float_3_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/space_to_batch_float_3_relaxed.model.cpp"
+} // namespace space_to_batch_float_3_relaxed
+TEST_F(GeneratedTests, space_to_batch_float_3_relaxed) {
+    execute(space_to_batch_float_3_relaxed::CreateModel,
+            space_to_batch_float_3_relaxed::is_ignored,
+            space_to_batch_float_3_relaxed::examples);
+}
+
 namespace space_to_batch {
 std::vector<MixedTypedExample> examples = {
 // Generated space_to_batch test
@@ -3291,6 +3711,20 @@ TEST_F(GeneratedTests, space_to_batch_quant8_3) {
             space_to_batch_quant8_3::examples);
 }
 
+namespace space_to_batch_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated space_to_batch_relaxed test
+#include "generated/examples/space_to_batch_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/space_to_batch_relaxed.model.cpp"
+} // namespace space_to_batch_relaxed
+TEST_F(GeneratedTests, space_to_batch_relaxed) {
+    execute(space_to_batch_relaxed::CreateModel,
+            space_to_batch_relaxed::is_ignored,
+            space_to_batch_relaxed::examples);
+}
+
 namespace space_to_depth_float_1_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated space_to_depth_float_1_relaxed test
@@ -3347,6 +3781,20 @@ TEST_F(GeneratedTests, squeeze_float_1) {
             squeeze_float_1::examples);
 }
 
+namespace squeeze_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated squeeze_float_1_relaxed test
+#include "generated/examples/squeeze_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/squeeze_float_1_relaxed.model.cpp"
+} // namespace squeeze_float_1_relaxed
+TEST_F(GeneratedTests, squeeze_float_1_relaxed) {
+    execute(squeeze_float_1_relaxed::CreateModel,
+            squeeze_float_1_relaxed::is_ignored,
+            squeeze_float_1_relaxed::examples);
+}
+
 namespace squeeze {
 std::vector<MixedTypedExample> examples = {
 // Generated squeeze test
@@ -3375,6 +3823,20 @@ TEST_F(GeneratedTests, squeeze_quant8_1) {
             squeeze_quant8_1::examples);
 }
 
+namespace squeeze_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated squeeze_relaxed test
+#include "generated/examples/squeeze_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/squeeze_relaxed.model.cpp"
+} // namespace squeeze_relaxed
+TEST_F(GeneratedTests, squeeze_relaxed) {
+    execute(squeeze_relaxed::CreateModel,
+            squeeze_relaxed::is_ignored,
+            squeeze_relaxed::examples);
+}
+
 namespace strided_slice_float_10 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_10 test
@@ -3389,6 +3851,20 @@ TEST_F(GeneratedTests, strided_slice_float_10) {
             strided_slice_float_10::examples);
 }
 
+namespace strided_slice_float_10_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_10_relaxed test
+#include "generated/examples/strided_slice_float_10_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/strided_slice_float_10_relaxed.model.cpp"
+} // namespace strided_slice_float_10_relaxed
+TEST_F(GeneratedTests, strided_slice_float_10_relaxed) {
+    execute(strided_slice_float_10_relaxed::CreateModel,
+            strided_slice_float_10_relaxed::is_ignored,
+            strided_slice_float_10_relaxed::examples);
+}
+
 namespace strided_slice_float_11 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_11 test
@@ -3403,6 +3879,20 @@ TEST_F(GeneratedTests, strided_slice_float_11) {
             strided_slice_float_11::examples);
 }
 
+namespace strided_slice_float_11_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_11_relaxed test
+#include "generated/examples/strided_slice_float_11_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/strided_slice_float_11_relaxed.model.cpp"
+} // namespace strided_slice_float_11_relaxed
+TEST_F(GeneratedTests, strided_slice_float_11_relaxed) {
+    execute(strided_slice_float_11_relaxed::CreateModel,
+            strided_slice_float_11_relaxed::is_ignored,
+            strided_slice_float_11_relaxed::examples);
+}
+
 namespace strided_slice_float_1 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_1 test
@@ -3417,6 +3907,20 @@ TEST_F(GeneratedTests, strided_slice_float_1) {
             strided_slice_float_1::examples);
 }
 
+namespace strided_slice_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_1_relaxed test
+#include "generated/examples/strided_slice_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/strided_slice_float_1_relaxed.model.cpp"
+} // namespace strided_slice_float_1_relaxed
+TEST_F(GeneratedTests, strided_slice_float_1_relaxed) {
+    execute(strided_slice_float_1_relaxed::CreateModel,
+            strided_slice_float_1_relaxed::is_ignored,
+            strided_slice_float_1_relaxed::examples);
+}
+
 namespace strided_slice_float_2 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_2 test
@@ -3431,6 +3935,20 @@ TEST_F(GeneratedTests, strided_slice_float_2) {
             strided_slice_float_2::examples);
 }
 
+namespace strided_slice_float_2_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_2_relaxed test
+#include "generated/examples/strided_slice_float_2_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/strided_slice_float_2_relaxed.model.cpp"
+} // namespace strided_slice_float_2_relaxed
+TEST_F(GeneratedTests, strided_slice_float_2_relaxed) {
+    execute(strided_slice_float_2_relaxed::CreateModel,
+            strided_slice_float_2_relaxed::is_ignored,
+            strided_slice_float_2_relaxed::examples);
+}
+
 namespace strided_slice_float_3 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_3 test
@@ -3445,6 +3963,20 @@ TEST_F(GeneratedTests, strided_slice_float_3) {
             strided_slice_float_3::examples);
 }
 
+namespace strided_slice_float_3_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_3_relaxed test
+#include "generated/examples/strided_slice_float_3_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/strided_slice_float_3_relaxed.model.cpp"
+} // namespace strided_slice_float_3_relaxed
+TEST_F(GeneratedTests, strided_slice_float_3_relaxed) {
+    execute(strided_slice_float_3_relaxed::CreateModel,
+            strided_slice_float_3_relaxed::is_ignored,
+            strided_slice_float_3_relaxed::examples);
+}
+
 namespace strided_slice_float_4 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_4 test
@@ -3459,6 +3991,20 @@ TEST_F(GeneratedTests, strided_slice_float_4) {
             strided_slice_float_4::examples);
 }
 
+namespace strided_slice_float_4_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_4_relaxed test
+#include "generated/examples/strided_slice_float_4_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/strided_slice_float_4_relaxed.model.cpp"
+} // namespace strided_slice_float_4_relaxed
+TEST_F(GeneratedTests, strided_slice_float_4_relaxed) {
+    execute(strided_slice_float_4_relaxed::CreateModel,
+            strided_slice_float_4_relaxed::is_ignored,
+            strided_slice_float_4_relaxed::examples);
+}
+
 namespace strided_slice_float_5 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_5 test
@@ -3473,6 +4019,20 @@ TEST_F(GeneratedTests, strided_slice_float_5) {
             strided_slice_float_5::examples);
 }
 
+namespace strided_slice_float_5_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_5_relaxed test
+#include "generated/examples/strided_slice_float_5_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/strided_slice_float_5_relaxed.model.cpp"
+} // namespace strided_slice_float_5_relaxed
+TEST_F(GeneratedTests, strided_slice_float_5_relaxed) {
+    execute(strided_slice_float_5_relaxed::CreateModel,
+            strided_slice_float_5_relaxed::is_ignored,
+            strided_slice_float_5_relaxed::examples);
+}
+
 namespace strided_slice_float_6 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_6 test
@@ -3487,6 +4047,20 @@ TEST_F(GeneratedTests, strided_slice_float_6) {
             strided_slice_float_6::examples);
 }
 
+namespace strided_slice_float_6_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_6_relaxed test
+#include "generated/examples/strided_slice_float_6_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/strided_slice_float_6_relaxed.model.cpp"
+} // namespace strided_slice_float_6_relaxed
+TEST_F(GeneratedTests, strided_slice_float_6_relaxed) {
+    execute(strided_slice_float_6_relaxed::CreateModel,
+            strided_slice_float_6_relaxed::is_ignored,
+            strided_slice_float_6_relaxed::examples);
+}
+
 namespace strided_slice_float_7 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_7 test
@@ -3501,6 +4075,20 @@ TEST_F(GeneratedTests, strided_slice_float_7) {
             strided_slice_float_7::examples);
 }
 
+namespace strided_slice_float_7_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_7_relaxed test
+#include "generated/examples/strided_slice_float_7_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/strided_slice_float_7_relaxed.model.cpp"
+} // namespace strided_slice_float_7_relaxed
+TEST_F(GeneratedTests, strided_slice_float_7_relaxed) {
+    execute(strided_slice_float_7_relaxed::CreateModel,
+            strided_slice_float_7_relaxed::is_ignored,
+            strided_slice_float_7_relaxed::examples);
+}
+
 namespace strided_slice_float_8 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_8 test
@@ -3515,6 +4103,20 @@ TEST_F(GeneratedTests, strided_slice_float_8) {
             strided_slice_float_8::examples);
 }
 
+namespace strided_slice_float_8_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_8_relaxed test
+#include "generated/examples/strided_slice_float_8_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/strided_slice_float_8_relaxed.model.cpp"
+} // namespace strided_slice_float_8_relaxed
+TEST_F(GeneratedTests, strided_slice_float_8_relaxed) {
+    execute(strided_slice_float_8_relaxed::CreateModel,
+            strided_slice_float_8_relaxed::is_ignored,
+            strided_slice_float_8_relaxed::examples);
+}
+
 namespace strided_slice_float_9 {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice_float_9 test
@@ -3529,6 +4131,20 @@ TEST_F(GeneratedTests, strided_slice_float_9) {
             strided_slice_float_9::examples);
 }
 
+namespace strided_slice_float_9_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_float_9_relaxed test
+#include "generated/examples/strided_slice_float_9_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/strided_slice_float_9_relaxed.model.cpp"
+} // namespace strided_slice_float_9_relaxed
+TEST_F(GeneratedTests, strided_slice_float_9_relaxed) {
+    execute(strided_slice_float_9_relaxed::CreateModel,
+            strided_slice_float_9_relaxed::is_ignored,
+            strided_slice_float_9_relaxed::examples);
+}
+
 namespace strided_slice {
 std::vector<MixedTypedExample> examples = {
 // Generated strided_slice test
@@ -3697,6 +4313,20 @@ TEST_F(GeneratedTests, strided_slice_quant8_9) {
             strided_slice_quant8_9::examples);
 }
 
+namespace strided_slice_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated strided_slice_relaxed test
+#include "generated/examples/strided_slice_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/strided_slice_relaxed.model.cpp"
+} // namespace strided_slice_relaxed
+TEST_F(GeneratedTests, strided_slice_relaxed) {
+    execute(strided_slice_relaxed::CreateModel,
+            strided_slice_relaxed::is_ignored,
+            strided_slice_relaxed::examples);
+}
+
 namespace sub_broadcast_float {
 std::vector<MixedTypedExample> examples = {
 // Generated sub_broadcast_float test
@@ -3711,6 +4341,20 @@ TEST_F(GeneratedTests, sub_broadcast_float) {
             sub_broadcast_float::examples);
 }
 
+namespace sub_broadcast_float_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated sub_broadcast_float_relaxed test
+#include "generated/examples/sub_broadcast_float_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/sub_broadcast_float_relaxed.model.cpp"
+} // namespace sub_broadcast_float_relaxed
+TEST_F(GeneratedTests, sub_broadcast_float_relaxed) {
+    execute(sub_broadcast_float_relaxed::CreateModel,
+            sub_broadcast_float_relaxed::is_ignored,
+            sub_broadcast_float_relaxed::examples);
+}
+
 namespace sub {
 std::vector<MixedTypedExample> examples = {
 // Generated sub test
@@ -3725,6 +4369,20 @@ TEST_F(GeneratedTests, sub) {
             sub::examples);
 }
 
+namespace sub_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated sub_relaxed test
+#include "generated/examples/sub_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/sub_relaxed.model.cpp"
+} // namespace sub_relaxed
+TEST_F(GeneratedTests, sub_relaxed) {
+    execute(sub_relaxed::CreateModel,
+            sub_relaxed::is_ignored,
+            sub_relaxed::examples);
+}
+
 namespace svdf2_relaxed {
 std::vector<MixedTypedExample> examples = {
 // Generated svdf2_relaxed test
@@ -3795,6 +4453,20 @@ TEST_F(GeneratedTests, transpose_float_1) {
             transpose_float_1::examples);
 }
 
+namespace transpose_float_1_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated transpose_float_1_relaxed test
+#include "generated/examples/transpose_float_1_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/transpose_float_1_relaxed.model.cpp"
+} // namespace transpose_float_1_relaxed
+TEST_F(GeneratedTests, transpose_float_1_relaxed) {
+    execute(transpose_float_1_relaxed::CreateModel,
+            transpose_float_1_relaxed::is_ignored,
+            transpose_float_1_relaxed::examples);
+}
+
 namespace transpose {
 std::vector<MixedTypedExample> examples = {
 // Generated transpose test
@@ -3822,3 +4494,17 @@ TEST_F(GeneratedTests, transpose_quant8_1) {
             transpose_quant8_1::is_ignored,
             transpose_quant8_1::examples);
 }
+
+namespace transpose_relaxed {
+std::vector<MixedTypedExample> examples = {
+// Generated transpose_relaxed test
+#include "generated/examples/transpose_relaxed.example.cpp"
+};
+// Generated model constructor
+#include "generated/models/transpose_relaxed.model.cpp"
+} // namespace transpose_relaxed
+TEST_F(GeneratedTests, transpose_relaxed) {
+    execute(transpose_relaxed::CreateModel,
+            transpose_relaxed::is_ignored,
+            transpose_relaxed::examples);
+}
diff --git a/nn/runtime/test/generated/examples/avg_pool_float_5_relaxed.example.cpp b/nn/runtime/test/generated/examples/avg_pool_float_5_relaxed.example.cpp
new file mode 100644
index 000000000..cbc61b75f
--- /dev/null
+++ b/nn/runtime/test/generated/examples/avg_pool_float_5_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: avg_pool_float_5_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 6, 2, 4, 3, 2, 10, 7}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {2.75f, 5.75f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/batch_to_space_float_1_relaxed.example.cpp b/nn/runtime/test/generated/examples/batch_to_space_float_1_relaxed.example.cpp
new file mode 100644
index 000000000..32031d315
--- /dev/null
+++ b/nn/runtime/test/generated/examples/batch_to_space_float_1_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: batch_to_space_float_1_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 5, 2, 6, 9, 13, 10, 14, 3, 7, 4, 8, 11, 15, 12, 16}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/batch_to_space_relaxed.example.cpp b/nn/runtime/test/generated/examples/batch_to_space_relaxed.example.cpp
new file mode 100644
index 000000000..eb1be3252
--- /dev/null
+++ b/nn/runtime/test/generated/examples/batch_to_space_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: batch_to_space_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/conv_float_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/conv_float_2_relaxed.example.cpp
new file mode 100644
index 000000000..c93ca212b
--- /dev/null
+++ b/nn/runtime/test/generated/examples/conv_float_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: conv_float_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 0, 0, 0, 35, 112, 157, 0, 0, 34, 61, 0}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/depthwise_conv2d_float_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/depthwise_conv2d_float_2_relaxed.example.cpp
new file mode 100644
index 000000000..4f108cf3a
--- /dev/null
+++ b/nn/runtime/test/generated/examples/depthwise_conv2d_float_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: depthwise_conv2d_float_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 7, 8, 3, 4, 9, 10, 5, 6, 11, 12}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {71, -34, 99, -20, 91, -26, 127, -4}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/depthwise_conv2d_float_large_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/depthwise_conv2d_float_large_2_relaxed.example.cpp
new file mode 100644
index 000000000..d8c887da9
--- /dev/null
+++ b/nn/runtime/test/generated/examples/depthwise_conv2d_float_large_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: depthwise_conv2d_float_large_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {10, 21, 100, 0, 10, 22, 200, 0, 10, 23, 300, 0, 10, 24, 400, 0}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {600010, 700046, 830000, 900000}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.example.cpp b/nn/runtime/test/generated/examples/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.example.cpp
new file mode 100644
index 000000000..9b6e34286
--- /dev/null
+++ b/nn/runtime/test/generated/examples/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {10, 21, 100, 10, 22, 200, 10, 23, 300, 10, 24, 400}}, {1, {0.25f, 0, 10, 100, 0.25f, 1, 20, 100, 0.25f, 0, 30, 100, 0.25f, 1, 40, 100}}, {2, {600000, 700000, 800000, 900000}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {600010, 700046, 830000, 900000}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/depthwise_conv2d_float_relaxed.example.cpp b/nn/runtime/test/generated/examples/depthwise_conv2d_float_relaxed.example.cpp
new file mode 100644
index 000000000..32a9f64ed
--- /dev/null
+++ b/nn/runtime/test/generated/examples/depthwise_conv2d_float_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: depthwise_conv2d_float_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {10, 21, 10, 22, 10, 23, 10, 24, 10, 25, 10, 26, 10, 27, 10, 28, 10, 29}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {11, 3, 7.2f, 10.6f, 11, 3, 7.4f, 10.9f, 11, 3, 7.8f, 11.5f, 11, 3, 8.0f, 11.8f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/depthwise_conv2d_float_weights_as_inputs_relaxed.example.cpp b/nn/runtime/test/generated/examples/depthwise_conv2d_float_weights_as_inputs_relaxed.example.cpp
new file mode 100644
index 000000000..1b5840df8
--- /dev/null
+++ b/nn/runtime/test/generated/examples/depthwise_conv2d_float_weights_as_inputs_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: depthwise_conv2d_float_weights_as_inputs_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {10, 21, 10, 22, 10, 23, 10, 24, 10, 25, 10, 26, 10, 27, 10, 28, 10, 29}}, {1, {0.25f, 0, 0.2f, 0, 0.25f, 0, 0, 0.3f, 0.25f, 0, 0, 0, 0.25f, 0.1f, 0, 0}}, {2, {1, 2, 3, 4}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {11, 3, 7.2f, 10.6f, 11, 3, 7.4f, 10.9f, 11, 3, 7.8f, 11.5f, 11, 3, 8.0f, 11.8f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/dequantize_relaxed.example.cpp b/nn/runtime/test/generated/examples/dequantize_relaxed.example.cpp
new file mode 100644
index 000000000..d9a624c17
--- /dev/null
+++ b/nn/runtime/test/generated/examples/dequantize_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: dequantize_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {{0, {0, 32, 128, 255}}}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.0f, 32.0f, 128.0f, 255.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/div_broadcast_float_relaxed.example.cpp b/nn/runtime/test/generated/examples/div_broadcast_float_relaxed.example.cpp
new file mode 100644
index 000000000..5e38550b8
--- /dev/null
+++ b/nn/runtime/test/generated/examples/div_broadcast_float_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: div_broadcast_float_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2}}, {1, {1, 1, 2, 2}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 0.5f, 1}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/div_relaxed.example.cpp b/nn/runtime/test/generated/examples/div_relaxed.example.cpp
new file mode 100644
index 000000000..49fc0ddf2
--- /dev/null
+++ b/nn/runtime/test/generated/examples/div_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: div_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {2.0f, -4.0f, 8.0f, -16.0f}}, {1, {2.0f, -2.0f, -4.0f, 4.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, -2.0f, -4.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/fully_connected_float_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/fully_connected_float_2_relaxed.example.cpp
new file mode 100644
index 000000000..e71963a1d
--- /dev/null
+++ b/nn/runtime/test/generated/examples/fully_connected_float_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: fully_connected_float_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.503691f, 0.196961f, 0.521017f, 0.554248f, 0.288678f, 0.792476f, 0.561653f, 0.46223f, 0.650736f, 0.163132f, 0.029658f, 0.411544f, 0.470539f, 0.57239f, 0.538755f, 0.21203f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 0.0732134f, 0, 0, 0, 0.280859f, 0, 0.128927f, 0, 0.0777251f, 0, 0.270268f, 0.271435f, 0.0173503f, 0.335465f, 0.235562f, 0, 0.0745866f, 0, 0.051611f, 0, 0.253876f, 0, 0.0814873f, 0, 0.104104f, 0, 0.248529f, 0.264194f, 0, 0.302973f, 0.166252f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/fully_connected_float_4d_simple_relaxed.example.cpp b/nn/runtime/test/generated/examples/fully_connected_float_4d_simple_relaxed.example.cpp
new file mode 100644
index 000000000..2a1aba7cf
--- /dev/null
+++ b/nn/runtime/test/generated/examples/fully_connected_float_4d_simple_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: fully_connected_float_4d_simple_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4, 5, 6, 7, 8, -9, -10, 1, 2, 3, 4, 5, 6, 7, -8, 9, -10}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {24, 25, 26, 58, 59, 60}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/fully_connected_float_large_relaxed.example.cpp b/nn/runtime/test/generated/examples/fully_connected_float_large_relaxed.example.cpp
new file mode 100644
index 000000000..131bc5fe3
--- /dev/null
+++ b/nn/runtime/test/generated/examples/fully_connected_float_large_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: fully_connected_float_large_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 10, 100, 1000, 10000}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {965432}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/fully_connected_float_large_weights_as_inputs_relaxed.example.cpp b/nn/runtime/test/generated/examples/fully_connected_float_large_weights_as_inputs_relaxed.example.cpp
new file mode 100644
index 000000000..990fd44a2
--- /dev/null
+++ b/nn/runtime/test/generated/examples/fully_connected_float_large_weights_as_inputs_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: fully_connected_float_large_weights_as_inputs_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 10, 100, 1000, 10000}}, {1, {2, 3, 4, 5, 6}}, {2, {900000}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {965432}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/l2_normalization_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/l2_normalization_2_relaxed.example.cpp
new file mode 100644
index 000000000..262ccdd1e
--- /dev/null
+++ b/nn/runtime/test/generated/examples/l2_normalization_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: l2_normalization_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-1.1f, 0.6f, 0.7f, 1.2f, -0.7f, 0.1f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.55f, 0.3f, 0.35f, 0.6f, -0.35f, 0.05f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/l2_pool_float_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/l2_pool_float_2_relaxed.example.cpp
new file mode 100644
index 000000000..fa964c56a
--- /dev/null
+++ b/nn/runtime/test/generated/examples/l2_pool_float_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: l2_pool_float_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 6, 2, 4, 3, 2, 10, 7}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {3.5f, 6.5f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/l2_pool_float_large_relaxed.example.cpp b/nn/runtime/test/generated/examples/l2_pool_float_large_relaxed.example.cpp
new file mode 100644
index 000000000..bae252198
--- /dev/null
+++ b/nn/runtime/test/generated/examples/l2_pool_float_large_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: l2_pool_float_large_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {6.442049503326416f, 7.314369201660156f, 8.215838432312012f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/max_pool_float_4_relaxed.example.cpp b/nn/runtime/test/generated/examples/max_pool_float_4_relaxed.example.cpp
new file mode 100644
index 000000000..f13ab59f6
--- /dev/null
+++ b/nn/runtime/test/generated/examples/max_pool_float_4_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: max_pool_float_4_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 6, 2, 4, 3, 2, 10, 7}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {6, 10}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/mean_float_1_relaxed.example.cpp b/nn/runtime/test/generated/examples/mean_float_1_relaxed.example.cpp
new file mode 100644
index 000000000..91d44215a
--- /dev/null
+++ b/nn/runtime/test/generated/examples/mean_float_1_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: mean_float_1_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {12.0f, 13.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/mean_float_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/mean_float_2_relaxed.example.cpp
new file mode 100644
index 000000000..5a5cfbc69
--- /dev/null
+++ b/nn/runtime/test/generated/examples/mean_float_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: mean_float_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {10.5f, 12.5f, 14.5f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/mean_relaxed.example.cpp b/nn/runtime/test/generated/examples/mean_relaxed.example.cpp
new file mode 100644
index 000000000..43602b8a7
--- /dev/null
+++ b/nn/runtime/test/generated/examples/mean_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: mean_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.5f, 3.5f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/pad_float_1_relaxed.example.cpp b/nn/runtime/test/generated/examples/pad_float_1_relaxed.example.cpp
new file mode 100644
index 000000000..6d1dc6fd8
--- /dev/null
+++ b/nn/runtime/test/generated/examples/pad_float_1_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: pad_float_1_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 1, 2, 3, 0, 0, 0, 0, 4, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/pad_relaxed.example.cpp b/nn/runtime/test/generated/examples/pad_relaxed.example.cpp
new file mode 100644
index 000000000..6ad7c7b2e
--- /dev/null
+++ b/nn/runtime/test/generated/examples/pad_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: pad_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 2.0f, 0.0f, 0.0f, 3.0f, 4.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/relu_float_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/relu_float_2_relaxed.example.cpp
new file mode 100644
index 000000000..1b1ee321f
--- /dev/null
+++ b/nn/runtime/test/generated/examples/relu_float_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: relu_float_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {-0.0f, 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f, 9.0f, -10.0f, 11.0f, -12.0f, 13.0f, -14.0f, 15.0f, -16.0f, 17.0f, -18.0f, 19.0f, -20.0f, 21.0f, -22.0f, 23.0f, -24.0f, 25.0f, -26.0f, 27.0f, -28.0f, 29.0f, -30.0f, 31.0f, -32.0f, 33.0f, -34.0f, 35.0f, -36.0f, 37.0f, -38.0f, 39.0f, -40.0f, 41.0f, -42.0f, 43.0f, -44.0f, 45.0f, -46.0f, 47.0f, -48.0f, 49.0f, -50.0f, 51.0f, -52.0f, 53.0f, -54.0f, 55.0f, -56.0f, 57.0f, -58.0f, 59.0f, -60.0f, 61.0f, -62.0f, 63.0f, -64.0f, 65.0f, -66.0f, 67.0f, -68.0f, 69.0f, -70.0f, 71.0f, -72.0f, 73.0f, -74.0f, 75.0f, -76.0f, 77.0f, -78.0f, 79.0f, -80.0f, 81.0f, -82.0f, 83.0f, -84.0f, 85.0f, -86.0f, 87.0f, -88.0f, 89.0f, -90.0f, 91.0f, -92.0f, 93.0f, -94.0f, 95.0f, -96.0f, 97.0f, -98.0f, 99.0f, -100.0f, 101.0f, -102.0f, 103.0f, -104.0f, 105.0f, -106.0f, 107.0f, -108.0f, 109.0f, -110.0f, 111.0f, -112.0f, 113.0f, -114.0f, 115.0f, -116.0f, 117.0f, -118.0f, 119.0f, -120.0f, 121.0f, -122.0f, 123.0f, -124.0f, 125.0f, -126.0f, 127.0f, -128.0f, 129.0f, -130.0f, 131.0f, -132.0f, 133.0f, -134.0f, 135.0f, -136.0f, 137.0f, -138.0f, 139.0f, -140.0f, 141.0f, -142.0f, 143.0f, -144.0f, 145.0f, -146.0f, 147.0f, -148.0f, 149.0f, -150.0f, 151.0f, -152.0f, 153.0f, -154.0f, 155.0f, -156.0f, 157.0f, -158.0f, 159.0f, -160.0f, 161.0f, -162.0f, 163.0f, -164.0f, 165.0f, -166.0f, 167.0f, -168.0f, 169.0f, -170.0f, 171.0f, -172.0f, 173.0f, -174.0f, 175.0f, -176.0f, 177.0f, -178.0f, 179.0f, -180.0f, 181.0f, -182.0f, 183.0f, -184.0f, 185.0f, -186.0f, 187.0f, -188.0f, 189.0f, -190.0f, 191.0f, -192.0f, 193.0f, -194.0f, 195.0f, -196.0f, 197.0f, -198.0f, 199.0f, -200.0f, 201.0f, -202.0f, 203.0f, -204.0f, 205.0f, -206.0f, 207.0f, -208.0f, 209.0f, -210.0f, 211.0f, -212.0f, 213.0f, -214.0f, 215.0f, -216.0f, 217.0f, -218.0f, 219.0f, -220.0f, 221.0f, -222.0f, 223.0f, -224.0f, 225.0f, -226.0f, 227.0f, -228.0f, 229.0f, -230.0f, 231.0f, -232.0f, 233.0f, -234.0f, 235.0f, -236.0f, 237.0f, -238.0f, 239.0f, -240.0f, 241.0f, -242.0f, 243.0f, -244.0f, 245.0f, -246.0f, 247.0f, -248.0f, 249.0f, -250.0f, 251.0f, -252.0f, 253.0f, -254.0f, 255.0f, -256.0f, 257.0f, -258.0f, 259.0f, -260.0f, 261.0f, -262.0f, 263.0f, -264.0f, 265.0f, -266.0f, 267.0f, -268.0f, 269.0f, -270.0f, 271.0f, -272.0f, 273.0f, -274.0f, 275.0f, -276.0f, 277.0f, -278.0f, 279.0f, -280.0f, 281.0f, -282.0f, 283.0f, -284.0f, 285.0f, -286.0f, 287.0f, -288.0f, 289.0f, -290.0f, 291.0f, -292.0f, 293.0f, -294.0f, 295.0f, -296.0f, 297.0f, -298.0f, 299.0f, -300.0f, 301.0f, -302.0f, 303.0f, -304.0f, 305.0f, -306.0f, 307.0f, -308.0f, 309.0f, -310.0f, 311.0f, -312.0f, 313.0f, -314.0f, 315.0f, -316.0f, 317.0f, -318.0f, 319.0f, -320.0f, 321.0f, -322.0f, 323.0f, -324.0f, 325.0f, -326.0f, 327.0f, -328.0f, 329.0f, -330.0f, 331.0f, -332.0f, 333.0f, -334.0f, 335.0f, -336.0f, 337.0f, -338.0f, 339.0f, -340.0f, 341.0f, -342.0f, 343.0f, -344.0f, 345.0f, -346.0f, 347.0f, -348.0f, 349.0f, -350.0f, 351.0f, -352.0f, 353.0f, -354.0f, 355.0f, -356.0f, 357.0f, -358.0f, 359.0f, -360.0f, 361.0f, -362.0f, 363.0f, -364.0f, 365.0f, -366.0f, 367.0f, -368.0f, 369.0f, -370.0f, 371.0f, -372.0f, 373.0f, -374.0f, 375.0f, -376.0f, 377.0f, -378.0f, 379.0f, -380.0f, 381.0f, -382.0f, 383.0f, -384.0f, 385.0f, -386.0f, 387.0f, -388.0f, 389.0f, -390.0f, 391.0f, -392.0f, 393.0f, -394.0f, 395.0f, -396.0f, 397.0f, -398.0f, 399.0f, -400.0f, 401.0f, -402.0f, 403.0f, -404.0f, 405.0f, -406.0f, 407.0f, -408.0f, 409.0f, -410.0f, 411.0f, -412.0f, 413.0f, -414.0f, 415.0f, -416.0f, 417.0f, -418.0f, 419.0f, -420.0f, 421.0f, -422.0f, 423.0f, -424.0f, 425.0f, -426.0f, 427.0f, -428.0f, 429.0f, -430.0f, 431.0f, -432.0f, 433.0f, -434.0f, 435.0f, -436.0f, 437.0f, -438.0f, 439.0f, -440.0f, 441.0f, -442.0f, 443.0f, -444.0f, 445.0f, -446.0f, 447.0f, -448.0f, 449.0f, -450.0f, 451.0f, -452.0f, 453.0f, -454.0f, 455.0f, -456.0f, 457.0f, -458.0f, 459.0f, -460.0f, 461.0f, -462.0f, 463.0f, -464.0f, 465.0f, -466.0f, 467.0f, -468.0f, 469.0f, -470.0f, 471.0f, -472.0f, 473.0f, -474.0f, 475.0f, -476.0f, 477.0f, -478.0f, 479.0f, 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-948.0f, 949.0f, -950.0f, 951.0f, -952.0f, 953.0f, -954.0f, 955.0f, -956.0f, 957.0f, -958.0f, 959.0f, -960.0f, 961.0f, -962.0f, 963.0f, -964.0f, 965.0f, -966.0f, 967.0f, -968.0f, 969.0f, -970.0f, 971.0f, -972.0f, 973.0f, -974.0f, 975.0f, -976.0f, 977.0f, -978.0f, 979.0f, -980.0f, 981.0f, -982.0f, 983.0f, -984.0f, 985.0f, -986.0f, 987.0f, -988.0f, 989.0f, -990.0f, 991.0f, -992.0f, 993.0f, -994.0f, 995.0f, -996.0f, 997.0f, -998.0f, 999.0f, -1000.0f, 1001.0f, -1002.0f, 1003.0f, -1004.0f, 1005.0f, -1006.0f, 1007.0f, -1008.0f, 1009.0f, -1010.0f, 1011.0f, -1012.0f, 1013.0f, -1014.0f, 1015.0f, -1016.0f, 1017.0f, -1018.0f, 1019.0f, -1020.0f, 1021.0f, -1022.0f, 1023.0f, -1024.0f, 1025.0f, -1026.0f, 1027.0f, -1028.0f, 1029.0f, -1030.0f, 1031.0f, -1032.0f, 1033.0f, -1034.0f, 1035.0f, -1036.0f, 1037.0f, -1038.0f, 1039.0f, -1040.0f, 1041.0f, -1042.0f, 1043.0f, -1044.0f, 1045.0f, -1046.0f, 1047.0f, -1048.0f, 1049.0f, -1050.0f, 1051.0f, -1052.0f, 1053.0f, -1054.0f, 1055.0f, -1056.0f, 1057.0f, 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-9878.0f, 9879.0f, -9880.0f, 9881.0f, -9882.0f, 9883.0f, -9884.0f, 9885.0f, -9886.0f, 9887.0f, -9888.0f, 9889.0f, -9890.0f, 9891.0f, -9892.0f, 9893.0f, -9894.0f, 9895.0f, -9896.0f, 9897.0f, -9898.0f, 9899.0f, -9900.0f, 9901.0f, -9902.0f, 9903.0f, -9904.0f, 9905.0f, -9906.0f, 9907.0f, -9908.0f, 9909.0f, -9910.0f, 9911.0f, -9912.0f, 9913.0f, -9914.0f, 9915.0f, -9916.0f, 9917.0f, -9918.0f, 9919.0f, -9920.0f, 9921.0f, -9922.0f, 9923.0f, -9924.0f, 9925.0f, -9926.0f, 9927.0f, -9928.0f, 9929.0f, -9930.0f, 9931.0f, -9932.0f, 9933.0f, -9934.0f, 9935.0f, -9936.0f, 9937.0f, -9938.0f, 9939.0f, -9940.0f, 9941.0f, -9942.0f, 9943.0f, -9944.0f, 9945.0f, -9946.0f, 9947.0f, -9948.0f, 9949.0f, -9950.0f, 9951.0f, -9952.0f, 9953.0f, -9954.0f, 9955.0f, -9956.0f, 9957.0f, -9958.0f, 9959.0f, -9960.0f, 9961.0f, -9962.0f, 9963.0f, -9964.0f, 9965.0f, -9966.0f, 9967.0f, -9968.0f, 9969.0f, -9970.0f, 9971.0f, -9972.0f, 9973.0f, -9974.0f, 9975.0f, -9976.0f, 9977.0f, -9978.0f, 9979.0f, -9980.0f, 9981.0f, -9982.0f, 9983.0f, -9984.0f, 9985.0f, -9986.0f, 9987.0f, -9988.0f, 9989.0f, -9990.0f, 9991.0f, -9992.0f, 9993.0f, -9994.0f, 9995.0f, -9996.0f, 9997.0f, -9998.0f, 9999.0f, -10000.0f, 10001.0f, -10002.0f, 10003.0f, -10004.0f, 10005.0f, -10006.0f, 10007.0f, -10008.0f, 10009.0f, -10010.0f, 10011.0f, -10012.0f, 10013.0f, -10014.0f, 10015.0f, -10016.0f, 10017.0f, -10018.0f, 10019.0f, -10020.0f, 10021.0f, -10022.0f, 10023.0f, -10024.0f, 10025.0f, -10026.0f, 10027.0f, -10028.0f, 10029.0f, -10030.0f, 10031.0f, -10032.0f, 10033.0f, -10034.0f, 10035.0f, -10036.0f, 10037.0f, -10038.0f, 10039.0f, -10040.0f, 10041.0f, -10042.0f, 10043.0f, -10044.0f, 10045.0f, -10046.0f, 10047.0f, -10048.0f, 10049.0f, -10050.0f, 10051.0f, -10052.0f, 10053.0f, -10054.0f, 10055.0f, -10056.0f, 10057.0f, -10058.0f, 10059.0f, -10060.0f, 10061.0f, -10062.0f, 10063.0f, -10064.0f, 10065.0f, -10066.0f, 10067.0f, -10068.0f, 10069.0f, -10070.0f, 10071.0f, -10072.0f, 10073.0f, -10074.0f, 10075.0f, -10076.0f, 10077.0f, -10078.0f, 10079.0f, -10080.0f, 10081.0f, -10082.0f, 10083.0f, -10084.0f, 10085.0f, -10086.0f, 10087.0f, -10088.0f, 10089.0f, -10090.0f, 10091.0f, -10092.0f, 10093.0f, -10094.0f, 10095.0f, -10096.0f, 10097.0f, -10098.0f, 10099.0f, -10100.0f, 10101.0f, -10102.0f, 10103.0f, -10104.0f, 10105.0f, -10106.0f, 10107.0f, -10108.0f, 10109.0f, -10110.0f, 10111.0f, -10112.0f, 10113.0f, -10114.0f, 10115.0f, -10116.0f, 10117.0f, -10118.0f, 10119.0f, -10120.0f, 10121.0f, -10122.0f, 10123.0f, -10124.0f, 10125.0f, -10126.0f, 10127.0f, -10128.0f, 10129.0f, -10130.0f, 10131.0f, -10132.0f, 10133.0f, -10134.0f, 10135.0f, -10136.0f, 10137.0f, -10138.0f, 10139.0f, -10140.0f, 10141.0f, -10142.0f, 10143.0f, -10144.0f, 10145.0f, -10146.0f, 10147.0f, -10148.0f, 10149.0f, -10150.0f, 10151.0f, -10152.0f, 10153.0f, -10154.0f, 10155.0f, -10156.0f, 10157.0f, -10158.0f, 10159.0f, -10160.0f, 10161.0f, -10162.0f, 10163.0f, -10164.0f, 10165.0f, -10166.0f, 10167.0f, -10168.0f, 10169.0f, -10170.0f, 10171.0f, -10172.0f, 10173.0f, -10174.0f, 10175.0f, -10176.0f, 10177.0f, -10178.0f, 10179.0f, -10180.0f, 10181.0f, -10182.0f, 10183.0f, -10184.0f, 10185.0f, -10186.0f, 10187.0f, -10188.0f, 10189.0f, -10190.0f, 10191.0f, -10192.0f, 10193.0f, -10194.0f, 10195.0f, -10196.0f, 10197.0f, -10198.0f, 10199.0f, -10200.0f, 10201.0f, -10202.0f, 10203.0f, -10204.0f, 10205.0f, -10206.0f, 10207.0f, -10208.0f, 10209.0f, -10210.0f, 10211.0f, -10212.0f, 10213.0f, -10214.0f, 10215.0f, -10216.0f, 10217.0f, -10218.0f, 10219.0f, -10220.0f, 10221.0f, -10222.0f, 10223.0f, -10224.0f, 10225.0f, -10226.0f, 10227.0f, -10228.0f, 10229.0f, -10230.0f, 10231.0f, -10232.0f, 10233.0f, -10234.0f, 10235.0f, -10236.0f, 10237.0f, -10238.0f, 10239.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 1, 0, 3, 0, 5, 0, 7, 0, 9, 0, 11, 0, 13, 0, 15, 0, 17, 0, 19, 0, 21, 0, 23, 0, 25, 0, 27, 0, 29, 0, 31, 0, 33, 0, 35, 0, 37, 0, 39, 0, 41, 0, 43, 0, 45, 0, 47, 0, 49, 0, 51, 0, 53, 0, 55, 0, 57, 0, 59, 0, 61, 0, 63, 0, 65, 0, 67, 0, 69, 0, 71, 0, 73, 0, 75, 0, 77, 0, 79, 0, 81, 0, 83, 0, 85, 0, 87, 0, 89, 0, 91, 0, 93, 0, 95, 0, 97, 0, 99, 0, 101, 0, 103, 0, 105, 0, 107, 0, 109, 0, 111, 0, 113, 0, 115, 0, 117, 0, 119, 0, 121, 0, 123, 0, 125, 0, 127, 0, 129, 0, 131, 0, 133, 0, 135, 0, 137, 0, 139, 0, 141, 0, 143, 0, 145, 0, 147, 0, 149, 0, 151, 0, 153, 0, 155, 0, 157, 0, 159, 0, 161, 0, 163, 0, 165, 0, 167, 0, 169, 0, 171, 0, 173, 0, 175, 0, 177, 0, 179, 0, 181, 0, 183, 0, 185, 0, 187, 0, 189, 0, 191, 0, 193, 0, 195, 0, 197, 0, 199, 0, 201, 0, 203, 0, 205, 0, 207, 0, 209, 0, 211, 0, 213, 0, 215, 0, 217, 0, 219, 0, 221, 0, 223, 0, 225, 0, 227, 0, 229, 0, 231, 0, 233, 0, 235, 0, 237, 0, 239, 0, 241, 0, 243, 0, 245, 0, 247, 0, 249, 0, 251, 0, 253, 0, 255, 0, 257, 0, 259, 0, 261, 0, 263, 0, 265, 0, 267, 0, 269, 0, 271, 0, 273, 0, 275, 0, 277, 0, 279, 0, 281, 0, 283, 0, 285, 0, 287, 0, 289, 0, 291, 0, 293, 0, 295, 0, 297, 0, 299, 0, 301, 0, 303, 0, 305, 0, 307, 0, 309, 0, 311, 0, 313, 0, 315, 0, 317, 0, 319, 0, 321, 0, 323, 0, 325, 0, 327, 0, 329, 0, 331, 0, 333, 0, 335, 0, 337, 0, 339, 0, 341, 0, 343, 0, 345, 0, 347, 0, 349, 0, 351, 0, 353, 0, 355, 0, 357, 0, 359, 0, 361, 0, 363, 0, 365, 0, 367, 0, 369, 0, 371, 0, 373, 0, 375, 0, 377, 0, 379, 0, 381, 0, 383, 0, 385, 0, 387, 0, 389, 0, 391, 0, 393, 0, 395, 0, 397, 0, 399, 0, 401, 0, 403, 0, 405, 0, 407, 0, 409, 0, 411, 0, 413, 0, 415, 0, 417, 0, 419, 0, 421, 0, 423, 0, 425, 0, 427, 0, 429, 0, 431, 0, 433, 0, 435, 0, 437, 0, 439, 0, 441, 0, 443, 0, 445, 0, 447, 0, 449, 0, 451, 0, 453, 0, 455, 0, 457, 0, 459, 0, 461, 0, 463, 0, 465, 0, 467, 0, 469, 0, 471, 0, 473, 0, 475, 0, 477, 0, 479, 0, 481, 0, 483, 0, 485, 0, 487, 0, 489, 0, 491, 0, 493, 0, 495, 0, 497, 0, 499, 0, 501, 0, 503, 0, 505, 0, 507, 0, 509, 0, 511, 0, 513, 0, 515, 0, 517, 0, 519, 0, 521, 0, 523, 0, 525, 0, 527, 0, 529, 0, 531, 0, 533, 0, 535, 0, 537, 0, 539, 0, 541, 0, 543, 0, 545, 0, 547, 0, 549, 0, 551, 0, 553, 0, 555, 0, 557, 0, 559, 0, 561, 0, 563, 0, 565, 0, 567, 0, 569, 0, 571, 0, 573, 0, 575, 0, 577, 0, 579, 0, 581, 0, 583, 0, 585, 0, 587, 0, 589, 0, 591, 0, 593, 0, 595, 0, 597, 0, 599, 0, 601, 0, 603, 0, 605, 0, 607, 0, 609, 0, 611, 0, 613, 0, 615, 0, 617, 0, 619, 0, 621, 0, 623, 0, 625, 0, 627, 0, 629, 0, 631, 0, 633, 0, 635, 0, 637, 0, 639, 0, 641, 0, 643, 0, 645, 0, 647, 0, 649, 0, 651, 0, 653, 0, 655, 0, 657, 0, 659, 0, 661, 0, 663, 0, 665, 0, 667, 0, 669, 0, 671, 0, 673, 0, 675, 0, 677, 0, 679, 0, 681, 0, 683, 0, 685, 0, 687, 0, 689, 0, 691, 0, 693, 0, 695, 0, 697, 0, 699, 0, 701, 0, 703, 0, 705, 0, 707, 0, 709, 0, 711, 0, 713, 0, 715, 0, 717, 0, 719, 0, 721, 0, 723, 0, 725, 0, 727, 0, 729, 0, 731, 0, 733, 0, 735, 0, 737, 0, 739, 0, 741, 0, 743, 0, 745, 0, 747, 0, 749, 0, 751, 0, 753, 0, 755, 0, 757, 0, 759, 0, 761, 0, 763, 0, 765, 0, 767, 0, 769, 0, 771, 0, 773, 0, 775, 0, 777, 0, 779, 0, 781, 0, 783, 0, 785, 0, 787, 0, 789, 0, 791, 0, 793, 0, 795, 0, 797, 0, 799, 0, 801, 0, 803, 0, 805, 0, 807, 0, 809, 0, 811, 0, 813, 0, 815, 0, 817, 0, 819, 0, 821, 0, 823, 0, 825, 0, 827, 0, 829, 0, 831, 0, 833, 0, 835, 0, 837, 0, 839, 0, 841, 0, 843, 0, 845, 0, 847, 0, 849, 0, 851, 0, 853, 0, 855, 0, 857, 0, 859, 0, 861, 0, 863, 0, 865, 0, 867, 0, 869, 0, 871, 0, 873, 0, 875, 0, 877, 0, 879, 0, 881, 0, 883, 0, 885, 0, 887, 0, 889, 0, 891, 0, 893, 0, 895, 0, 897, 0, 899, 0, 901, 0, 903, 0, 905, 0, 907, 0, 909, 0, 911, 0, 913, 0, 915, 0, 917, 0, 919, 0, 921, 0, 923, 0, 925, 0, 927, 0, 929, 0, 931, 0, 933, 0, 935, 0, 937, 0, 939, 0, 941, 0, 943, 0, 945, 0, 947, 0, 949, 0, 951, 0, 953, 0, 955, 0, 957, 0, 959, 0, 961, 0, 963, 0, 965, 0, 967, 0, 969, 0, 971, 0, 973, 0, 975, 0, 977, 0, 979, 0, 981, 0, 983, 0, 985, 0, 987, 0, 989, 0, 991, 0, 993, 0, 995, 0, 997, 0, 999, 0, 1001, 0, 1003, 0, 1005, 0, 1007, 0, 1009, 0, 1011, 0, 1013, 0, 1015, 0, 1017, 0, 1019, 0, 1021, 0, 1023, 0, 1025, 0, 1027, 0, 1029, 0, 1031, 0, 1033, 0, 1035, 0, 1037, 0, 1039, 0, 1041, 0, 1043, 0, 1045, 0, 1047, 0, 1049, 0, 1051, 0, 1053, 0, 1055, 0, 1057, 0, 1059, 0, 1061, 0, 1063, 0, 1065, 0, 1067, 0, 1069, 0, 1071, 0, 1073, 0, 1075, 0, 1077, 0, 1079, 0, 1081, 0, 1083, 0, 1085, 0, 1087, 0, 1089, 0, 1091, 0, 1093, 0, 1095, 0, 1097, 0, 1099, 0, 1101, 0, 1103, 0, 1105, 0, 1107, 0, 1109, 0, 1111, 0, 1113, 0, 1115, 0, 1117, 0, 1119, 0, 1121, 0, 1123, 0, 1125, 0, 1127, 0, 1129, 0, 1131, 0, 1133, 0, 1135, 0, 1137, 0, 1139, 0, 1141, 0, 1143, 0, 1145, 0, 1147, 0, 1149, 0, 1151, 0, 1153, 0, 1155, 0, 1157, 0, 1159, 0, 1161, 0, 1163, 0, 1165, 0, 1167, 0, 1169, 0, 1171, 0, 1173, 0, 1175, 0, 1177, 0, 1179, 0, 1181, 0, 1183, 0, 1185, 0, 1187, 0, 1189, 0, 1191, 0, 1193, 0, 1195, 0, 1197, 0, 1199, 0, 1201, 0, 1203, 0, 1205, 0, 1207, 0, 1209, 0, 1211, 0, 1213, 0, 1215, 0, 1217, 0, 1219, 0, 1221, 0, 1223, 0, 1225, 0, 1227, 0, 1229, 0, 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9667, 0, 9669, 0, 9671, 0, 9673, 0, 9675, 0, 9677, 0, 9679, 0, 9681, 0, 9683, 0, 9685, 0, 9687, 0, 9689, 0, 9691, 0, 9693, 0, 9695, 0, 9697, 0, 9699, 0, 9701, 0, 9703, 0, 9705, 0, 9707, 0, 9709, 0, 9711, 0, 9713, 0, 9715, 0, 9717, 0, 9719, 0, 9721, 0, 9723, 0, 9725, 0, 9727, 0, 9729, 0, 9731, 0, 9733, 0, 9735, 0, 9737, 0, 9739, 0, 9741, 0, 9743, 0, 9745, 0, 9747, 0, 9749, 0, 9751, 0, 9753, 0, 9755, 0, 9757, 0, 9759, 0, 9761, 0, 9763, 0, 9765, 0, 9767, 0, 9769, 0, 9771, 0, 9773, 0, 9775, 0, 9777, 0, 9779, 0, 9781, 0, 9783, 0, 9785, 0, 9787, 0, 9789, 0, 9791, 0, 9793, 0, 9795, 0, 9797, 0, 9799, 0, 9801, 0, 9803, 0, 9805, 0, 9807, 0, 9809, 0, 9811, 0, 9813, 0, 9815, 0, 9817, 0, 9819, 0, 9821, 0, 9823, 0, 9825, 0, 9827, 0, 9829, 0, 9831, 0, 9833, 0, 9835, 0, 9837, 0, 9839, 0, 9841, 0, 9843, 0, 9845, 0, 9847, 0, 9849, 0, 9851, 0, 9853, 0, 9855, 0, 9857, 0, 9859, 0, 9861, 0, 9863, 0, 9865, 0, 9867, 0, 9869, 0, 9871, 0, 9873, 0, 9875, 0, 9877, 0, 9879, 0, 9881, 0, 9883, 0, 9885, 0, 9887, 0, 9889, 0, 9891, 0, 9893, 0, 9895, 0, 9897, 0, 9899, 0, 9901, 0, 9903, 0, 9905, 0, 9907, 0, 9909, 0, 9911, 0, 9913, 0, 9915, 0, 9917, 0, 9919, 0, 9921, 0, 9923, 0, 9925, 0, 9927, 0, 9929, 0, 9931, 0, 9933, 0, 9935, 0, 9937, 0, 9939, 0, 9941, 0, 9943, 0, 9945, 0, 9947, 0, 9949, 0, 9951, 0, 9953, 0, 9955, 0, 9957, 0, 9959, 0, 9961, 0, 9963, 0, 9965, 0, 9967, 0, 9969, 0, 9971, 0, 9973, 0, 9975, 0, 9977, 0, 9979, 0, 9981, 0, 9983, 0, 9985, 0, 9987, 0, 9989, 0, 9991, 0, 9993, 0, 9995, 0, 9997, 0, 9999, 0, 10001, 0, 10003, 0, 10005, 0, 10007, 0, 10009, 0, 10011, 0, 10013, 0, 10015, 0, 10017, 0, 10019, 0, 10021, 0, 10023, 0, 10025, 0, 10027, 0, 10029, 0, 10031, 0, 10033, 0, 10035, 0, 10037, 0, 10039, 0, 10041, 0, 10043, 0, 10045, 0, 10047, 0, 10049, 0, 10051, 0, 10053, 0, 10055, 0, 10057, 0, 10059, 0, 10061, 0, 10063, 0, 10065, 0, 10067, 0, 10069, 0, 10071, 0, 10073, 0, 10075, 0, 10077, 0, 10079, 0, 10081, 0, 10083, 0, 10085, 0, 10087, 0, 10089, 0, 10091, 0, 10093, 0, 10095, 0, 10097, 0, 10099, 0, 10101, 0, 10103, 0, 10105, 0, 10107, 0, 10109, 0, 10111, 0, 10113, 0, 10115, 0, 10117, 0, 10119, 0, 10121, 0, 10123, 0, 10125, 0, 10127, 0, 10129, 0, 10131, 0, 10133, 0, 10135, 0, 10137, 0, 10139, 0, 10141, 0, 10143, 0, 10145, 0, 10147, 0, 10149, 0, 10151, 0, 10153, 0, 10155, 0, 10157, 0, 10159, 0, 10161, 0, 10163, 0, 10165, 0, 10167, 0, 10169, 0, 10171, 0, 10173, 0, 10175, 0, 10177, 0, 10179, 0, 10181, 0, 10183, 0, 10185, 0, 10187, 0, 10189, 0, 10191, 0, 10193, 0, 10195, 0, 10197, 0, 10199, 0, 10201, 0, 10203, 0, 10205, 0, 10207, 0, 10209, 0, 10211, 0, 10213, 0, 10215, 0, 10217, 0, 10219, 0, 10221, 0, 10223, 0, 10225, 0, 10227, 0, 10229, 0, 10231, 0, 10233, 0, 10235, 0, 10237, 0, 10239}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/resize_bilinear_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/resize_bilinear_2_relaxed.example.cpp
new file mode 100644
index 000000000..2139411aa
--- /dev/null
+++ b/nn/runtime/test/generated/examples/resize_bilinear_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: resize_bilinear_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {3, 4, 6, 10, 9, 10, 12, 16}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {3, 4, 5, 8, 6, 10, 7, 8, 9, 12, 10, 14, 9, 10, 11, 14, 12, 16}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/space_to_batch_float_1_relaxed.example.cpp b/nn/runtime/test/generated/examples/space_to_batch_float_1_relaxed.example.cpp
new file mode 100644
index 000000000..aab8779a9
--- /dev/null
+++ b/nn/runtime/test/generated/examples/space_to_batch_float_1_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: space_to_batch_float_1_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 3, 9, 11, 2, 4, 10, 12, 5, 7, 13, 15, 6, 8, 14, 16}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/space_to_batch_float_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/space_to_batch_float_2_relaxed.example.cpp
new file mode 100644
index 000000000..9c4f649f0
--- /dev/null
+++ b/nn/runtime/test/generated/examples/space_to_batch_float_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: space_to_batch_float_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 0, 0, 5, 0, 0, 0, 6, 0, 1, 0, 7, 0, 2, 0, 8, 0, 3, 0, 9, 0, 4, 0, 10}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/space_to_batch_float_3_relaxed.example.cpp b/nn/runtime/test/generated/examples/space_to_batch_float_3_relaxed.example.cpp
new file mode 100644
index 000000000..6fa614b1c
--- /dev/null
+++ b/nn/runtime/test/generated/examples/space_to_batch_float_3_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: space_to_batch_float_3_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4, 5, 6, 7, 8}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 1, 0, 0, 0, 7, 0, 0, 0, 2, 0, 0, 0, 8, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/space_to_batch_relaxed.example.cpp b/nn/runtime/test/generated/examples/space_to_batch_relaxed.example.cpp
new file mode 100644
index 000000000..aad722fcc
--- /dev/null
+++ b/nn/runtime/test/generated/examples/space_to_batch_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: space_to_batch_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/squeeze_float_1_relaxed.example.cpp b/nn/runtime/test/generated/examples/squeeze_float_1_relaxed.example.cpp
new file mode 100644
index 000000000..135d04e31
--- /dev/null
+++ b/nn/runtime/test/generated/examples/squeeze_float_1_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: squeeze_float_1_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/squeeze_relaxed.example.cpp b/nn/runtime/test/generated/examples/squeeze_relaxed.example.cpp
new file mode 100644
index 000000000..b73e0058f
--- /dev/null
+++ b/nn/runtime/test/generated/examples/squeeze_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: squeeze_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/strided_slice_float_10_relaxed.example.cpp b/nn/runtime/test/generated/examples/strided_slice_float_10_relaxed.example.cpp
new file mode 100644
index 000000000..6db5d97b0
--- /dev/null
+++ b/nn/runtime/test/generated/examples/strided_slice_float_10_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: strided_slice_float_10_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4, 5, 6}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {4, 5, 6}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/strided_slice_float_11_relaxed.example.cpp b/nn/runtime/test/generated/examples/strided_slice_float_11_relaxed.example.cpp
new file mode 100644
index 000000000..9780e412e
--- /dev/null
+++ b/nn/runtime/test/generated/examples/strided_slice_float_11_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: strided_slice_float_11_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4, 5, 6}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/strided_slice_float_1_relaxed.example.cpp b/nn/runtime/test/generated/examples/strided_slice_float_1_relaxed.example.cpp
new file mode 100644
index 000000000..79324898e
--- /dev/null
+++ b/nn/runtime/test/generated/examples/strided_slice_float_1_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: strided_slice_float_1_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {2, 3}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/strided_slice_float_2_relaxed.example.cpp b/nn/runtime/test/generated/examples/strided_slice_float_2_relaxed.example.cpp
new file mode 100644
index 000000000..fd1e19aed
--- /dev/null
+++ b/nn/runtime/test/generated/examples/strided_slice_float_2_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: strided_slice_float_2_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {2, 3}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/strided_slice_float_3_relaxed.example.cpp b/nn/runtime/test/generated/examples/strided_slice_float_3_relaxed.example.cpp
new file mode 100644
index 000000000..3328aa6f2
--- /dev/null
+++ b/nn/runtime/test/generated/examples/strided_slice_float_3_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: strided_slice_float_3_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/strided_slice_float_4_relaxed.example.cpp b/nn/runtime/test/generated/examples/strided_slice_float_4_relaxed.example.cpp
new file mode 100644
index 000000000..bd455137e
--- /dev/null
+++ b/nn/runtime/test/generated/examples/strided_slice_float_4_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: strided_slice_float_4_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {2}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/strided_slice_float_5_relaxed.example.cpp b/nn/runtime/test/generated/examples/strided_slice_float_5_relaxed.example.cpp
new file mode 100644
index 000000000..3ceaedb7f
--- /dev/null
+++ b/nn/runtime/test/generated/examples/strided_slice_float_5_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: strided_slice_float_5_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/strided_slice_float_6_relaxed.example.cpp b/nn/runtime/test/generated/examples/strided_slice_float_6_relaxed.example.cpp
new file mode 100644
index 000000000..4ad87ee99
--- /dev/null
+++ b/nn/runtime/test/generated/examples/strided_slice_float_6_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: strided_slice_float_6_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {2, 3, 4}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/strided_slice_float_7_relaxed.example.cpp b/nn/runtime/test/generated/examples/strided_slice_float_7_relaxed.example.cpp
new file mode 100644
index 000000000..cd2d40ce4
--- /dev/null
+++ b/nn/runtime/test/generated/examples/strided_slice_float_7_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: strided_slice_float_7_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {3, 2, 1}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/strided_slice_float_8_relaxed.example.cpp b/nn/runtime/test/generated/examples/strided_slice_float_8_relaxed.example.cpp
new file mode 100644
index 000000000..bab6a744a
--- /dev/null
+++ b/nn/runtime/test/generated/examples/strided_slice_float_8_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: strided_slice_float_8_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4, 5, 6}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {6, 5, 4}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/strided_slice_float_9_relaxed.example.cpp b/nn/runtime/test/generated/examples/strided_slice_float_9_relaxed.example.cpp
new file mode 100644
index 000000000..4c3b80ea5
--- /dev/null
+++ b/nn/runtime/test/generated/examples/strided_slice_float_9_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: strided_slice_float_9_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 3, 4, 5, 6}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2, 4, 5}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/strided_slice_relaxed.example.cpp b/nn/runtime/test/generated/examples/strided_slice_relaxed.example.cpp
new file mode 100644
index 000000000..b6054ea7f
--- /dev/null
+++ b/nn/runtime/test/generated/examples/strided_slice_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: strided_slice_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 3.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/sub_broadcast_float_relaxed.example.cpp b/nn/runtime/test/generated/examples/sub_broadcast_float_relaxed.example.cpp
new file mode 100644
index 000000000..762d7c3cc
--- /dev/null
+++ b/nn/runtime/test/generated/examples/sub_broadcast_float_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: sub_broadcast_float_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1, 2}}, {1, {1, 2, 3, 4}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 0, -2, -2}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/sub_relaxed.example.cpp b/nn/runtime/test/generated/examples/sub_relaxed.example.cpp
new file mode 100644
index 000000000..f1575f129
--- /dev/null
+++ b/nn/runtime/test/generated/examples/sub_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: sub_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {2.0f, -4.0f, 8.0f, -16.0f}}, {1, {2.0f, -2.0f, -4.0f, 4.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0.0f, -2.0f, 12.0f, -20.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/transpose_float_1_relaxed.example.cpp b/nn/runtime/test/generated/examples/transpose_float_1_relaxed.example.cpp
new file mode 100644
index 000000000..38412fd3b
--- /dev/null
+++ b/nn/runtime/test/generated/examples/transpose_float_1_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: transpose_float_1_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {0, 1, 2, 3, 4, 20, 21, 22, 23, 24, 40, 41, 42, 43, 44, 60, 61, 62, 63, 64, 80, 81, 82, 83, 84, 100, 101, 102, 103, 104, 5, 6, 7, 8, 9, 25, 26, 27, 28, 29, 45, 46, 47, 48, 49, 65, 66, 67, 68, 69, 85, 86, 87, 88, 89, 105, 106, 107, 108, 109, 10, 11, 12, 13, 14, 30, 31, 32, 33, 34, 50, 51, 52, 53, 54, 70, 71, 72, 73, 74, 90, 91, 92, 93, 94, 110, 111, 112, 113, 114, 15, 16, 17, 18, 19, 35, 36, 37, 38, 39, 55, 56, 57, 58, 59, 75, 76, 77, 78, 79, 95, 96, 97, 98, 99, 115, 116, 117, 118, 119}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/examples/transpose_relaxed.example.cpp b/nn/runtime/test/generated/examples/transpose_relaxed.example.cpp
new file mode 100644
index 000000000..b4da88feb
--- /dev/null
+++ b/nn/runtime/test/generated/examples/transpose_relaxed.example.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: transpose_relaxed.mod.py). Do not edit
+// Begin of an example
+{
+//Input(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 2.0f, 3.0f, 4.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+},
+//Output(s)
+{ // See tools/test_generator/include/TestHarness.h:MixedTyped
+  // int -> FLOAT32 map
+  {{0, {1.0f, 3.0f, 2.0f, 4.0f}}},
+  // int -> INT32 map
+  {},
+  // int -> QUANT8_ASYMM map
+  {}
+}
+}, // End of an example
diff --git a/nn/runtime/test/generated/models/avg_pool_float_5_relaxed.model.cpp b/nn/runtime/test/generated/models/avg_pool_float_5_relaxed.model.cpp
new file mode 100644
index 000000000..0002efd89
--- /dev/null
+++ b/nn/runtime/test/generated/models/avg_pool_float_5_relaxed.model.cpp
@@ -0,0 +1,32 @@
+// Generated file (from: avg_pool_float_5_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 1, 2, 1});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 4, 1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto cons2 = model->addOperand(&type1);
+  auto pad_same = model->addOperand(&type1);
+  auto act_none = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t cons2_init[] = {2};
+  model->setOperandValue(cons2, cons2_init, sizeof(int32_t) * 1);
+  static int32_t pad_same_init[] = {1};
+  model->setOperandValue(pad_same, pad_same_init, sizeof(int32_t) * 1);
+  static int32_t act_none_init[] = {0};
+  model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_AVERAGE_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/batch_to_space_float_1_relaxed.model.cpp b/nn/runtime/test/generated/models/batch_to_space_float_1_relaxed.model.cpp
new file mode 100644
index 000000000..c53f0a04c
--- /dev/null
+++ b/nn/runtime/test/generated/models/batch_to_space_float_1_relaxed.model.cpp
@@ -0,0 +1,26 @@
+// Generated file (from: batch_to_space_float_1_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 4, 4, 1});
+  OperandType type0(Type::TENSOR_FLOAT32, {4, 2, 2, 1});
+  OperandType type1(Type::TENSOR_INT32, {2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto block_size = model->addOperand(&type1);
+  auto output = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t block_size_init[] = {2, 2};
+  model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2);
+  model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {input, block_size}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/batch_to_space_relaxed.model.cpp b/nn/runtime/test/generated/models/batch_to_space_relaxed.model.cpp
new file mode 100644
index 000000000..d3180cc0c
--- /dev/null
+++ b/nn/runtime/test/generated/models/batch_to_space_relaxed.model.cpp
@@ -0,0 +1,26 @@
+// Generated file (from: batch_to_space_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 2, 2, 2});
+  OperandType type0(Type::TENSOR_FLOAT32, {4, 1, 1, 2});
+  OperandType type1(Type::TENSOR_INT32, {2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto block_size = model->addOperand(&type1);
+  auto output = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t block_size_init[] = {2, 2};
+  model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2);
+  model->addOperation(ANEURALNETWORKS_BATCH_TO_SPACE_ND, {input, block_size}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/conv_float_2_relaxed.model.cpp b/nn/runtime/test/generated/models/conv_float_2_relaxed.model.cpp
new file mode 100644
index 000000000..84c5f6c42
--- /dev/null
+++ b/nn/runtime/test/generated/models/conv_float_2_relaxed.model.cpp
@@ -0,0 +1,39 @@
+// Generated file (from: conv_float_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type3(Type::INT32, {});
+  OperandType type1(Type::TENSOR_FLOAT32, {1, 3, 3, 1});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 3, 4, 1});
+  OperandType type2(Type::TENSOR_FLOAT32, {1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  auto pad_same = model->addOperand(&type3);
+  auto act_relu = model->addOperand(&type3);
+  auto stride = model->addOperand(&type3);
+  auto op4 = model->addOperand(&type0);
+  // Phase 2, operations
+  static float op2_init[] = {1.0f, 4.0f, 7.0f, 2.0f, 5.0f, 8.0f, 3.0f, 6.0f, 9.0f};
+  model->setOperandValue(op2, op2_init, sizeof(float) * 9);
+  static float op3_init[] = {-200.0f};
+  model->setOperandValue(op3, op3_init, sizeof(float) * 1);
+  static int32_t pad_same_init[] = {1};
+  model->setOperandValue(pad_same, pad_same_init, sizeof(int32_t) * 1);
+  static int32_t act_relu_init[] = {1};
+  model->setOperandValue(act_relu, act_relu_init, sizeof(int32_t) * 1);
+  static int32_t stride_init[] = {1};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad_same, stride, stride, act_relu}, {op4});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op4});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/depthwise_conv2d_float_2_relaxed.model.cpp b/nn/runtime/test/generated/models/depthwise_conv2d_float_2_relaxed.model.cpp
new file mode 100644
index 000000000..5875093e3
--- /dev/null
+++ b/nn/runtime/test/generated/models/depthwise_conv2d_float_2_relaxed.model.cpp
@@ -0,0 +1,43 @@
+// Generated file (from: depthwise_conv2d_float_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type3(Type::INT32, {});
+  OperandType type4(Type::TENSOR_FLOAT32, {1, 2, 1, 4});
+  OperandType type1(Type::TENSOR_FLOAT32, {1, 2, 2, 4});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 3, 2, 2});
+  OperandType type2(Type::TENSOR_FLOAT32, {4});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  auto pad_valid = model->addOperand(&type3);
+  auto act_none = model->addOperand(&type3);
+  auto stride = model->addOperand(&type3);
+  auto channelMultiplier = model->addOperand(&type3);
+  auto op4 = model->addOperand(&type4);
+  // Phase 2, operations
+  static float op2_init[] = {1.0f, 2.0f, 3.0f, 4.0f, -9.0f, 10.0f, -11.0f, 12.0f, 5.0f, 6.0f, 7.0f, 8.0f, 13.0f, -14.0f, 15.0f, -16.0f};
+  model->setOperandValue(op2, op2_init, sizeof(float) * 16);
+  static float op3_init[] = {1.0f, 2.0f, 3.0f, 4.0f};
+  model->setOperandValue(op3, op3_init, sizeof(float) * 4);
+  static int32_t pad_valid_init[] = {2};
+  model->setOperandValue(pad_valid, pad_valid_init, sizeof(int32_t) * 1);
+  static int32_t act_none_init[] = {0};
+  model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1);
+  static int32_t stride_init[] = {1};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  static int32_t channelMultiplier_init[] = {2};
+  model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad_valid, stride, stride, channelMultiplier, act_none}, {op4});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op4});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/depthwise_conv2d_float_large_2_relaxed.model.cpp b/nn/runtime/test/generated/models/depthwise_conv2d_float_large_2_relaxed.model.cpp
new file mode 100644
index 000000000..f736d8f83
--- /dev/null
+++ b/nn/runtime/test/generated/models/depthwise_conv2d_float_large_2_relaxed.model.cpp
@@ -0,0 +1,42 @@
+// Generated file (from: depthwise_conv2d_float_large_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {1, 1, 1, 4});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 4});
+  OperandType type1(Type::TENSOR_FLOAT32, {4});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type0);
+  auto op3 = model->addOperand(&type1);
+  auto pad0 = model->addOperand(&type2);
+  auto act = model->addOperand(&type2);
+  auto stride = model->addOperand(&type2);
+  auto channelMultiplier = model->addOperand(&type2);
+  auto op4 = model->addOperand(&type3);
+  // Phase 2, operations
+  static float op2_init[] = {0.25f, 0.0f, 10.0f, 100.0f, 0.25f, 1.0f, 20.0f, 100.0f, 0.25f, 0.0f, 30.0f, 100.0f, 0.25f, 1.0f, 40.0f, 100.0f};
+  model->setOperandValue(op2, op2_init, sizeof(float) * 16);
+  static float op3_init[] = {600000.0f, 700000.0f, 800000.0f, 900000.0f};
+  model->setOperandValue(op3, op3_init, sizeof(float) * 4);
+  static int32_t pad0_init[] = {0};
+  model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  static int32_t stride_init[] = {1};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  static int32_t channelMultiplier_init[] = {1};
+  model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op4});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/models/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.model.cpp
new file mode 100644
index 000000000..d24074c7b
--- /dev/null
+++ b/nn/runtime/test/generated/models/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.model.cpp
@@ -0,0 +1,39 @@
+// Generated file (from: depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type3(Type::INT32, {});
+  OperandType type4(Type::TENSOR_FLOAT32, {1, 1, 1, 4});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 3});
+  OperandType type1(Type::TENSOR_FLOAT32, {1, 2, 2, 4});
+  OperandType type2(Type::TENSOR_FLOAT32, {4});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  auto pad0 = model->addOperand(&type3);
+  auto act = model->addOperand(&type3);
+  auto stride = model->addOperand(&type3);
+  auto channelMultiplier = model->addOperand(&type3);
+  auto op4 = model->addOperand(&type4);
+  // Phase 2, operations
+  static int32_t pad0_init[] = {0};
+  model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  static int32_t stride_init[] = {1};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  static int32_t channelMultiplier_init[] = {1};
+  model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1, op2, op3},
+    {op4});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/depthwise_conv2d_float_relaxed.model.cpp b/nn/runtime/test/generated/models/depthwise_conv2d_float_relaxed.model.cpp
new file mode 100644
index 000000000..33eb3d341
--- /dev/null
+++ b/nn/runtime/test/generated/models/depthwise_conv2d_float_relaxed.model.cpp
@@ -0,0 +1,42 @@
+// Generated file (from: depthwise_conv2d_float_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type3(Type::INT32, {});
+  OperandType type1(Type::TENSOR_FLOAT32, {1, 2, 2, 4});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 3, 3, 2});
+  OperandType type2(Type::TENSOR_FLOAT32, {4});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  auto pad0 = model->addOperand(&type3);
+  auto act = model->addOperand(&type3);
+  auto stride = model->addOperand(&type3);
+  auto channelMultiplier = model->addOperand(&type3);
+  auto op4 = model->addOperand(&type1);
+  // Phase 2, operations
+  static float op2_init[] = {0.25f, 0.0f, 0.2f, 0.0f, 0.25f, 0.0f, 0.0f, 0.3f, 0.25f, 0.0f, 0.0f, 0.0f, 0.25f, 0.1f, 0.0f, 0.0f};
+  model->setOperandValue(op2, op2_init, sizeof(float) * 16);
+  static float op3_init[] = {1.0f, 2.0f, 3.0f, 4.0f};
+  model->setOperandValue(op3, op3_init, sizeof(float) * 4);
+  static int32_t pad0_init[] = {0};
+  model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  static int32_t stride_init[] = {1};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  static int32_t channelMultiplier_init[] = {2};
+  model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op4});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/depthwise_conv2d_float_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/models/depthwise_conv2d_float_weights_as_inputs_relaxed.model.cpp
new file mode 100644
index 000000000..281add460
--- /dev/null
+++ b/nn/runtime/test/generated/models/depthwise_conv2d_float_weights_as_inputs_relaxed.model.cpp
@@ -0,0 +1,38 @@
+// Generated file (from: depthwise_conv2d_float_weights_as_inputs_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type3(Type::INT32, {});
+  OperandType type1(Type::TENSOR_FLOAT32, {1, 2, 2, 4});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 3, 3, 2});
+  OperandType type2(Type::TENSOR_FLOAT32, {4});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  auto pad0 = model->addOperand(&type3);
+  auto act = model->addOperand(&type3);
+  auto stride = model->addOperand(&type3);
+  auto channelMultiplier = model->addOperand(&type3);
+  auto op4 = model->addOperand(&type1);
+  // Phase 2, operations
+  static int32_t pad0_init[] = {0};
+  model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  static int32_t stride_init[] = {1};
+  model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
+  static int32_t channelMultiplier_init[] = {2};
+  model->setOperandValue(channelMultiplier, channelMultiplier_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1, op2, op3},
+    {op4});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/dequantize_relaxed.model.cpp b/nn/runtime/test/generated/models/dequantize_relaxed.model.cpp
new file mode 100644
index 000000000..e1f924c37
--- /dev/null
+++ b/nn/runtime/test/generated/models/dequantize_relaxed.model.cpp
@@ -0,0 +1,22 @@
+// Generated file (from: dequantize_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
+  OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 2, 2, 1}, 1.f, 0);
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_DEQUANTIZE, {op1}, {op2});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op2});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/div_broadcast_float_relaxed.model.cpp b/nn/runtime/test/generated/models/div_broadcast_float_relaxed.model.cpp
new file mode 100644
index 000000000..d8f2c1efe
--- /dev/null
+++ b/nn/runtime/test/generated/models/div_broadcast_float_relaxed.model.cpp
@@ -0,0 +1,27 @@
+// Generated file (from: div_broadcast_float_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2});
+  OperandType type1(Type::TENSOR_FLOAT32, {2, 2});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto act = model->addOperand(&type2);
+  auto op3 = model->addOperand(&type1);
+  // Phase 2, operations
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_DIV, {op1, op2, act}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1, op2},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/div_relaxed.model.cpp b/nn/runtime/test/generated/models/div_relaxed.model.cpp
new file mode 100644
index 000000000..6634f18fb
--- /dev/null
+++ b/nn/runtime/test/generated/models/div_relaxed.model.cpp
@@ -0,0 +1,26 @@
+// Generated file (from: div_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type0);
+  auto act = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type0);
+  // Phase 2, operations
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_DIV, {op1, op2, act}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1, op2},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/fully_connected_float_2_relaxed.model.cpp b/nn/runtime/test/generated/models/fully_connected_float_2_relaxed.model.cpp
new file mode 100644
index 000000000..44db385b0
--- /dev/null
+++ b/nn/runtime/test/generated/models/fully_connected_float_2_relaxed.model.cpp
@@ -0,0 +1,34 @@
+// Generated file (from: fully_connected_float_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type4(Type::INT32, {});
+  OperandType type1(Type::TENSOR_FLOAT32, {16, 8});
+  OperandType type2(Type::TENSOR_FLOAT32, {16});
+  OperandType type3(Type::TENSOR_FLOAT32, {2, 16});
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 8});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto b0 = model->addOperand(&type2);
+  auto op3 = model->addOperand(&type3);
+  auto act_relu = model->addOperand(&type4);
+  // Phase 2, operations
+  static float op2_init[] = {0.091327f, 0.103366f, -0.316505f, -0.08312f, 0.149366f, -0.196636f, -0.123672f, 0.0628f, 0.063031f, 0.19167f, -0.062001f, -0.061504f, -0.275581f, 0.059388f, -0.118497f, -0.079224f, 0.109758f, 0.008307f, -0.062657f, -0.060962f, -0.049782f, -0.106719f, -0.319482f, -0.10365f, 0.266455f, 0.051517f, -0.123448f, 0.322464f, 0.043282f, -0.173782f, -0.190381f, 0.002013f, 0.096086f, 0.131157f, 0.031164f, 0.100638f, -0.312191f, -0.080923f, -0.101318f, -0.116614f, 0.142238f, 0.08654f, -0.139154f, 0.174268f, -0.073161f, 0.080072f, 0.006874f, 0.229382f, -0.104321f, -0.176035f, -0.208587f, -0.001019f, -0.162032f, 0.080824f, -0.025021f, 0.07446f, -0.252595f, -0.16175f, -0.136403f, 0.008308f, 0.00571f, 0.0966f, 0.289839f, 0.218816f, -0.304651f, -0.070958f, 0.054598f, 0.147113f, -0.139112f, -0.072798f, -0.163335f, -0.167863f, -0.128762f, -0.03578f, 0.117262f, 0.017177f, 0.263335f, -0.176612f, 0.262961f, -0.093654f, -0.339283f, 0.333071f, 0.180827f, 0.287583f, 0.06635f, -0.197947f, -0.114449f, -0.236035f, 0.103532f, -0.034284f, 0.093299f, -0.145361f, 0.054001f, 0.25057f, 0.15701f, -0.14348f, -0.139061f, -0.048873f, 0.067557f, 0.139038f, 0.324106f, 0.227041f, 0.037793f, -0.225747f, -0.241619f, 0.357835f, 0.135762f, -0.306764f, -0.125982f, 0.091916f, 0.266587f, 0.030135f, 0.265148f, 0.141627f, 0.02012f, 0.083815f, -0.124556f, -0.100124f, -0.048159f, 0.181172f, 0.302309f, -0.041084f, 0.146334f, -0.061511f, -0.232605f, 0.281324f, 0.145408f, -0.221897f};
+  model->setOperandValue(op2, op2_init, sizeof(float) * 128);
+  static float b0_init[] = {-0.160594f, 0.20577f, -0.078307f, -0.077984f, 0.001937f, 0.01586f, 0.03681f, 0.012346f, 0.001028f, 0.038551f, 0.075415f, 0.020804f, 0.048478f, -0.03227f, 0.175688f, -0.085662f};
+  model->setOperandValue(b0, b0_init, sizeof(float) * 16);
+  static int32_t act_relu_init[] = {1};
+  model->setOperandValue(act_relu, act_relu_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act_relu}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/fully_connected_float_4d_simple.model.cpp b/nn/runtime/test/generated/models/fully_connected_float_4d_simple.model.cpp
index 46932f5aa..aa645d966 100644
--- a/nn/runtime/test/generated/models/fully_connected_float_4d_simple.model.cpp
+++ b/nn/runtime/test/generated/models/fully_connected_float_4d_simple.model.cpp
@@ -23,8 +23,6 @@ void CreateModel(Model *model) {
   model->identifyInputsAndOutputs(
     {op1},
     {op3});
-  // Phase 4: set relaxed execution
-  model->relaxComputationFloat32toFloat16(true);
   assert(model->isValid());
 }
 
diff --git a/nn/runtime/test/generated/models/fully_connected_float_4d_simple_relaxed.model.cpp b/nn/runtime/test/generated/models/fully_connected_float_4d_simple_relaxed.model.cpp
new file mode 100644
index 000000000..496e066a2
--- /dev/null
+++ b/nn/runtime/test/generated/models/fully_connected_float_4d_simple_relaxed.model.cpp
@@ -0,0 +1,34 @@
+// Generated file (from: fully_connected_float_4d_simple_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type4(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {2, 3});
+  OperandType type1(Type::TENSOR_FLOAT32, {3, 10});
+  OperandType type2(Type::TENSOR_FLOAT32, {3});
+  OperandType type0(Type::TENSOR_FLOAT32, {4, 1, 5, 1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto b0 = model->addOperand(&type2);
+  auto op3 = model->addOperand(&type3);
+  auto act = model->addOperand(&type4);
+  // Phase 2, operations
+  static float op2_init[] = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f};
+  model->setOperandValue(op2, op2_init, sizeof(float) * 30);
+  static float b0_init[] = {1.0f, 2.0f, 3.0f};
+  model->setOperandValue(b0, b0_init, sizeof(float) * 3);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/fully_connected_float_large_relaxed.model.cpp b/nn/runtime/test/generated/models/fully_connected_float_large_relaxed.model.cpp
new file mode 100644
index 000000000..a4a719f8f
--- /dev/null
+++ b/nn/runtime/test/generated/models/fully_connected_float_large_relaxed.model.cpp
@@ -0,0 +1,33 @@
+// Generated file (from: fully_connected_float_large_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type3(Type::INT32, {});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 1});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 5});
+  OperandType type1(Type::TENSOR_FLOAT32, {1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type0);
+  auto b0 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  auto act = model->addOperand(&type3);
+  // Phase 2, operations
+  static float op2_init[] = {2.0f, 3.0f, 4.0f, 5.0f, 6.0f};
+  model->setOperandValue(op2, op2_init, sizeof(float) * 5);
+  static float b0_init[] = {900000.0f};
+  model->setOperandValue(b0, b0_init, sizeof(float) * 1);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/fully_connected_float_large_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/models/fully_connected_float_large_weights_as_inputs_relaxed.model.cpp
new file mode 100644
index 000000000..a0161d15f
--- /dev/null
+++ b/nn/runtime/test/generated/models/fully_connected_float_large_weights_as_inputs_relaxed.model.cpp
@@ -0,0 +1,29 @@
+// Generated file (from: fully_connected_float_large_weights_as_inputs_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type3(Type::INT32, {});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 1});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 5});
+  OperandType type1(Type::TENSOR_FLOAT32, {1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type0);
+  auto b0 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  auto act = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1, op2, b0},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/l2_normalization_2_relaxed.model.cpp b/nn/runtime/test/generated/models/l2_normalization_2_relaxed.model.cpp
new file mode 100644
index 000000000..cde12578b
--- /dev/null
+++ b/nn/runtime/test/generated/models/l2_normalization_2_relaxed.model.cpp
@@ -0,0 +1,21 @@
+// Generated file (from: l2_normalization_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 1, 1, 6});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type0);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_L2_NORMALIZATION, {op1}, {op2});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op2});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/l2_pool_float_2_relaxed.model.cpp b/nn/runtime/test/generated/models/l2_pool_float_2_relaxed.model.cpp
new file mode 100644
index 000000000..597cfeda5
--- /dev/null
+++ b/nn/runtime/test/generated/models/l2_pool_float_2_relaxed.model.cpp
@@ -0,0 +1,32 @@
+// Generated file (from: l2_pool_float_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 1, 2, 1});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 4, 1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto cons2 = model->addOperand(&type1);
+  auto pad_same = model->addOperand(&type1);
+  auto act_none = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t cons2_init[] = {2};
+  model->setOperandValue(cons2, cons2_init, sizeof(int32_t) * 1);
+  static int32_t pad_same_init[] = {1};
+  model->setOperandValue(pad_same, pad_same_init, sizeof(int32_t) * 1);
+  static int32_t act_none_init[] = {0};
+  model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_L2_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/l2_pool_float_large_relaxed.model.cpp b/nn/runtime/test/generated/models/l2_pool_float_large_relaxed.model.cpp
new file mode 100644
index 000000000..11bc8cfcc
--- /dev/null
+++ b/nn/runtime/test/generated/models/l2_pool_float_large_relaxed.model.cpp
@@ -0,0 +1,41 @@
+// Generated file (from: l2_pool_float_large_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 1, 1, 3});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 3});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto filter_width = model->addOperand(&type1);
+  auto filter_height = model->addOperand(&type1);
+  auto stride_width = model->addOperand(&type1);
+  auto stride_height = model->addOperand(&type1);
+  auto pad0 = model->addOperand(&type1);
+  auto act = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t filter_width_init[] = {2};
+  model->setOperandValue(filter_width, filter_width_init, sizeof(int32_t) * 1);
+  static int32_t filter_height_init[] = {2};
+  model->setOperandValue(filter_height, filter_height_init, sizeof(int32_t) * 1);
+  static int32_t stride_width_init[] = {1};
+  model->setOperandValue(stride_width, stride_width_init, sizeof(int32_t) * 1);
+  static int32_t stride_height_init[] = {1};
+  model->setOperandValue(stride_height, stride_height_init, sizeof(int32_t) * 1);
+  static int32_t pad0_init[] = {0};
+  model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_L2_POOL_2D, {op1, pad0, pad0, pad0, pad0, stride_width, stride_height, filter_width, filter_height, act}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/max_pool_float_4_relaxed.model.cpp b/nn/runtime/test/generated/models/max_pool_float_4_relaxed.model.cpp
new file mode 100644
index 000000000..0ea4461c1
--- /dev/null
+++ b/nn/runtime/test/generated/models/max_pool_float_4_relaxed.model.cpp
@@ -0,0 +1,32 @@
+// Generated file (from: max_pool_float_4_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 1, 2, 1});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 4, 1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto cons2 = model->addOperand(&type1);
+  auto pad_same = model->addOperand(&type1);
+  auto act_none = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t cons2_init[] = {2};
+  model->setOperandValue(cons2, cons2_init, sizeof(int32_t) * 1);
+  static int32_t pad_same_init[] = {1};
+  model->setOperandValue(pad_same, pad_same_init, sizeof(int32_t) * 1);
+  static int32_t act_none_init[] = {0};
+  model->setOperandValue(act_none, act_none_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_MAX_POOL_2D, {op1, pad_same, cons2, cons2, cons2, cons2, act_none}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/mean_float_1_relaxed.model.cpp b/nn/runtime/test/generated/models/mean_float_1_relaxed.model.cpp
new file mode 100644
index 000000000..d03939661
--- /dev/null
+++ b/nn/runtime/test/generated/models/mean_float_1_relaxed.model.cpp
@@ -0,0 +1,30 @@
+// Generated file (from: mean_float_1_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {2});
+  OperandType type0(Type::TENSOR_FLOAT32, {4, 3, 2});
+  OperandType type1(Type::TENSOR_INT32, {4});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto axis = model->addOperand(&type1);
+  auto keepDims = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t axis_init[] = {1, 0, -3, -3};
+  model->setOperandValue(axis, axis_init, sizeof(int32_t) * 4);
+  static int32_t keepDims_init[] = {0};
+  model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/mean_float_2_relaxed.model.cpp b/nn/runtime/test/generated/models/mean_float_2_relaxed.model.cpp
new file mode 100644
index 000000000..80c7ba519
--- /dev/null
+++ b/nn/runtime/test/generated/models/mean_float_2_relaxed.model.cpp
@@ -0,0 +1,30 @@
+// Generated file (from: mean_float_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {1, 3, 1});
+  OperandType type0(Type::TENSOR_FLOAT32, {4, 3, 2});
+  OperandType type1(Type::TENSOR_INT32, {2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto axis = model->addOperand(&type1);
+  auto keepDims = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t axis_init[] = {0, 2};
+  model->setOperandValue(axis, axis_init, sizeof(int32_t) * 2);
+  static int32_t keepDims_init[] = {1};
+  model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/mean_relaxed.model.cpp b/nn/runtime/test/generated/models/mean_relaxed.model.cpp
new file mode 100644
index 000000000..b420b6b7c
--- /dev/null
+++ b/nn/runtime/test/generated/models/mean_relaxed.model.cpp
@@ -0,0 +1,30 @@
+// Generated file (from: mean_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {1, 2, 1});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
+  OperandType type1(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto axis = model->addOperand(&type1);
+  auto keepDims = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t axis_init[] = {2};
+  model->setOperandValue(axis, axis_init, sizeof(int32_t) * 1);
+  static int32_t keepDims_init[] = {0};
+  model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/mobilenet_224_gender_basic_fixed.model.cpp b/nn/runtime/test/generated/models/mobilenet_224_gender_basic_fixed.model.cpp
index e20b010cf..9e0fcd5b8 100644
--- a/nn/runtime/test/generated/models/mobilenet_224_gender_basic_fixed.model.cpp
+++ b/nn/runtime/test/generated/models/mobilenet_224_gender_basic_fixed.model.cpp
@@ -625,11 +625,11 @@ void CreateModel(Model *model) {
   model->setOperandValue(op79, op79_init, sizeof(float) * 128);
   static float op80_init[] = {0.143542f, -0.139317f, -0.0557127f, 0.00193462f, -0.0166539f, 0.216436f, 0.0694379f, 0.0774276f, -0.061387f, 0.193228f, -0.0234282f, 0.0303868f, -0.10475f, 0.225842f, -0.0953071f, 0.0518284f, -0.177148f, 0.0706816f, -0.116163f, 0.23116f, 0.0276252f, 0.361075f, 0.114999f, -0.179934f, 0.0362276f, 0.098386f, 0.160729f, -0.203046f, -0.0214891f, -0.0217361f, -0.0319598f, -0.0163527f, 0.0405451f, -0.0441358f, -0.0010904f, -0.219479f, -0.0129676f, 0.0840713f, -0.334326f, -0.275725f, 0.00787852f, 0.102421f, 0.0265449f, -0.0439835f, -0.160807f, 0.128618f, 0.00937286f, 0.0634051f, 0.17013f, -0.149011f, -0.148228f, -0.185353f, -0.230108f, 0.0953904f, -0.0328099f, 0.08806f, 0.164153f, -0.155663f, 0.00662038f, 0.106636f, -0.110083f, -0.123108f, -0.0422361f, 0.00699063f, 0.0286107f, 0.0872556f, 0.0372735f, 0.129417f, 0.0114595f, 0.127069f, 0.0845895f, -0.103232f, -0.084375f, 0.0507973f, 0.0924024f, -0.0443189f, -0.0373084f, -0.0547004f, -0.107631f, -0.0137342f, -0.0308677f, 0.0818465f, 0.0348359f, -0.108934f, -0.0827724f, 0.0323507f, 0.0412687f, 0.0808453f, -0.051265f, 0.0951301f, -0.144128f, 0.0754425f, -0.127725f, 0.0168919f, -0.0751399f, -0.0739095f, 0.00380989f, -0.118355f, 0.131179f, 0.123024f, 0.13949f, -0.0452833f, 0.0908636f, -0.044923f, 0.0656833f, 0.154517f, -0.0803701f, -0.0962871f, 0.0389703f, 0.208096f, -0.0663933f, -0.131471f, -0.0790224f, 0.101245f, 0.0744562f, 0.210848f, -0.0880954f, 0.28261f, -0.0400531f, -0.0429046f, 0.115284f, 0.0810933f, -0.0732279f, -0.0363539f, 0.0390622f, 0.194268f, -0.125276f, 0.0660326f, -0.0191896f, -0.107549f, -0.068292f, 0.0296083f, -0.148026f, 0.00504009f, 0.136341f, 0.0185907f, 0.0354229f, 0.0570693f, -0.0652823f, 0.053643f, -0.226353f, -0.0586207f, 0.102557f, -0.0804407f, -0.0549814f, -0.0189678f, 0.0337161f, -0.240366f, -0.0152426f, -0.032301f, 0.0503872f, -0.00353695f, 0.0145041f, -0.0507668f, 0.0484236f, 0.0752401f, 0.131723f, 0.137027f, 0.0677545f, 0.149137f, -0.136712f, -0.047893f, -0.196069f, 0.000413097f, 0.0625105f, 0.0322905f, 0.053051f, -0.0330334f, 0.00132125f, 0.113487f, -0.120027f, 0.101515f, -0.0197327f, -0.0517467f, -0.11808f, 0.0443416f, 0.0221126f, 0.114449f, -0.0283071f, -0.139215f, 0.0598481f, 0.100257f, 0.0225039f, 0.0457186f, 0.0902391f, -0.0631196f, 0.0257833f, 0.112569f, -0.19343f, -0.0384445f, 0.0758919f, -0.0712537f, 0.00513168f, 0.151857f, -0.142854f, -0.0268036f, 0.0715712f, -0.0574248f, -0.03567f, -0.166058f, 0.0211768f, -0.119797f, -0.11925f, -0.0453431f, 0.0293065f, 0.120933f, 0.00402085f, 0.109672f, 0.134472f, 0.195219f, 0.180352f, -0.0515071f, -0.0545261f, 0.0322048f, 0.012976f, 0.0343293f, -0.0513619f, -0.0167084f, -0.160956f, -0.0328522f, -0.0399779f, 0.114662f, -0.0672433f, 0.125241f, -0.102642f, 0.0559623f, 0.13515f, 0.066221f, 0.0132642f, 0.0813321f, -0.0672475f, -0.0972056f, 0.0324055f, 0.0954416f, 0.0394797f, -0.0865308f, 0.0588531f, 0.0190956f, 0.102544f, 0.0641314f, 0.05755f, 0.114106f, 0.0457606f, -0.0910149f, -0.143913f, 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-0.0833115f, 0.132745f, -0.0764369f, -0.0667909f, 0.0471235f, -0.0951605f, 0.0251998f, 0.109606f, -0.0551212f, 0.0423476f, -0.0914923f, 0.104139f, -0.166891f, -0.144794f, 0.00263478f, 0.0549706f, -0.0192015f, -0.094959f, -0.0470626f};
   model->setOperandValue(op80, op80_init, sizeof(float) * 16384);
-  model->addOperation(ANEURALNETWORKS_CONV_2D, {op86, op2, op1, b87, b88, b89, b90}, {op0});
   static float op83_init[] = {-0.0293549f, -0.0835053f, -0.228576f, -0.0980885f, -0.0370638f, -0.195879f, -0.0452258f, 0.0371641f, -0.0585841f, -0.0984154f, -0.141293f};
   model->setOperandValue(op83, op83_init, sizeof(float) * 11);
   static float op84_init[] = {0.0984852f, 0.672424f, 0.392549f, -0.262182f, 0.303914f, -0.0118188f, 0.027943f, 0.0164078f, 0.200583f, -0.808626f, 0.234772f, -0.0253635f, -0.198519f, -0.176824f, -0.580674f, 0.0681573f, -0.0134279f, 0.172173f, -0.284882f, -0.0895141f, 0.0142356f, -0.0479431f, 0.0736678f, 0.00298977f, 0.152355f, -0.0370715f, 0.463201f, 0.0146613f, 0.0971624f, -0.0791196f, 0.556621f, -0.00950762f, 0.0160531f, 0.091037f, 0.376353f, -0.0996081f, -0.0418334f, -0.427482f, -0.202679f, -0.197079f, 0.021873f, -0.105617f, 0.36447f, 0.389277f, 0.0429815f, 0.0480496f, -0.170086f, -0.191548f, -0.237921f, 0.155838f, -0.100796f, 0.0539355f, 0.103154f, 0.0441985f, -0.20672f, 0.358565f, -0.105794f, -0.635905f, 0.193301f, 0.112419f, -0.184668f, 0.157954f, -0.301095f, -0.153072f, -0.0535615f, -0.0661999f, -0.197056f, -0.0835003f, -0.074932f, -0.111766f, -0.356266f, 0.649165f, -0.0527003f, -0.0597135f, 0.109839f, -0.270809f, 0.0333183f, -0.211454f, 0.0594729f, -0.166949f, 0.21057f, 0.224925f, -0.222835f, -0.0178217f, 0.127268f, 0.229248f, 0.262987f, 0.0318244f, 0.293201f, -0.361254f, -0.0624992f, -0.0696259f, 0.0456531f, -0.0287401f, 0.0863351f, -0.106142f, 0.81137f, 0.305728f, 0.398482f, -0.0190696f, -0.133965f, -0.223757f, -0.153242f, -0.261303f, 0.111363f, -0.113733f, 0.0028724f, -0.0878969f, 0.0498853f, -0.000613516f, -0.0819123f, -0.0154599f, -0.0938842f, -0.108295f, 0.340323f, -0.139579f, -0.117066f, 0.145283f, -0.106254f, 0.201248f, -0.152479f, 0.162457f, -0.0751263f, 0.00127508f, -0.0218281f, 0.126278f, -0.100075f, 0.426783f, -0.108719f, 0.207569f, -0.327427f, 0.277309f, 0.0404061f, -0.334901f, 0.154047f, -0.287619f, 0.0161922f, -0.00054208f, -0.233675f, 0.564603f, 0.201628f, 0.0510375f, -0.16502f, -0.0155493f, -0.125359f, -0.0996153f, 0.0133961f, -0.492208f, 0.109118f, -0.136327f, 0.0252329f, 0.0556799f, -0.196804f, -0.0612012f, -0.0392273f, 0.133385f, 0.253763f, -0.208136f, -0.00507434f, -0.0584744f, 0.0855089f, -0.00321895f, -0.209376f, 0.0618401f, 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0.0515511f, -0.0446207f, 0.0495584f, 0.06504f, -0.0502581f, -0.0989093f, -0.242931f, -0.161322f, 0.0412978f, 0.0882053f, -0.0868244f, 0.0333411f, 0.0033292f, 0.0956053f, 0.224343f, -0.0605414f, 0.200487f, 0.139677f, 0.0741737f, 0.131144f, -0.0156217f, 0.119855f, -0.0672591f, 0.0646749f, 0.0212678f, -0.0612522f, 0.127438f, 0.165742f, 0.149455f, 0.120228f, 0.245928f, -0.536011f, -0.0221017f, 0.0210271f, 0.196356f, 0.0401149f, -0.00733165f, -0.270396f, -0.00968083f, -0.0709557f, -0.120717f, 0.140489f, 0.0935343f, -0.172696f, 0.301435f, -0.0935873f, -0.0353977f, 0.0539549f, -0.0338224f, -0.239903f, -0.0209894f, -0.17114f, 0.267786f, 0.20251f, -0.0980189f, -0.04852f, -0.207071f, -0.253257f, -0.0564701f, -0.0518127f, -0.0537929f, -0.390881f, 0.0470064f, 0.0306878f, 0.104422f, 0.150282f, 0.0117885f, -0.093087f, -0.0377776f, -0.0618607f, -0.0869537f, 0.137726f, 0.0903727f, 0.0346921f, 0.0111f, -0.241767f, -0.201946f, 0.09471f, -0.156048f, -0.0978701f, -0.239229f, -0.0308635f, -0.122071f, -0.433478f, -0.0514787f, -0.182472f, -0.181954f, 0.0416541f, -0.0883368f, 0.157402f, -0.462445f, -0.103609f, -0.160994f, -0.0133393f, -0.096508f, 0.100438f, 0.00418135f, -0.0122206f, 0.172408f, 0.0437795f, -0.172367f, -0.0189107f, -0.0304423f, 0.0780768f, -0.116228f, -0.0305065f, -0.0440305f, 0.00286725f, -0.157059f, 0.132452f, -0.101883f, -0.138483f, 0.00723927f, 0.0342281f, 0.206677f, -0.0770022f, 0.0227105f, -0.111016f, -0.170921f, 0.055846f, 0.246527f, -0.142554f, -0.380108f, -0.0346903f, 0.138706f, -0.176424f, 0.112018f, 0.0435032f, -0.127998f, -0.169885f, -0.0509104f, -0.0870096f, -0.535699f, -0.0638343f, -0.0311837f, 0.078099f, -0.0342351f, 0.0749799f, 0.3883f, -0.154977f, 0.224178f, 0.0550229f, 0.107375f, 0.33049f, 0.0969202f, 0.0756623f, -0.233299f, -0.104361f, 0.442374f, 0.0844492f, 0.0705411f, -0.140545f, -0.0663961f, -0.0728755f, -0.0621244f, -0.0819853f, -0.112193f, -0.176114f, -0.0938139f, -0.214228f, 0.0190762f, -0.213562f, -0.190233f, 0.133314f, -0.148665f, 0.0915799f, 0.187216f, -0.284974f, 0.00733069f, 0.0156916f, 0.015107f, 0.0318654f, 0.346104f, -0.124227f, 0.137341f, 0.0592528f, -0.387351f, -0.221991f, 0.360592f, -0.0931174f, -0.0492834f, 0.199867f, -0.0852204f, 0.150399f, 0.0413833f, 0.235906f, -0.0706518f, -0.166653f, -0.0586646f, -0.109711f, -0.0823073f, 0.257342f, -0.224644f, -0.430506f, -0.105588f, 0.0250296f, -0.042311f, -0.0996558f, -0.115579f, -0.286667f, -0.154598f, -0.137322f, 0.176363f, 0.088216f, 0.161978f, 0.255623f, -0.0123169f, -0.00387241f, -0.318043f, -0.21894f, -0.412465f, -0.415855f, 0.255024f, 0.361044f, 0.0300423f, -0.119439f, 0.0657428f, -0.238206f, 0.340391f, 0.201176f, 0.102395f, 0.216324f, -0.121531f, 0.265799f, 0.0327802f, 0.194072f, -0.0792337f, 0.456093f, 0.0971469f, -0.0170099f, -0.0294468f, -0.318039f, -0.242527f, -0.1083f, 0.295943f, -0.0284033f, -0.156199f, -0.20311f, -0.075091f, 0.528829f, -0.165604f, 0.0532403f, 0.0505752f, -0.413034f, 0.175453f, -0.0970195f, -0.029351f, 0.103333f, 0.271092f, 0.0511197f, -0.182135f, 0.112932f, -0.32439f, 0.294457f, -0.0818895f, 0.0914322f, 0.185025f, 0.0543957f, -0.0167575f, 0.504046f, -0.0647153f, -0.166975f, 0.0248059f, 0.0379442f, 0.0980366f, -0.178135f, 0.143822f, 0.45732f, -0.0912428f, -0.179338f, 0.349726f, -0.0596313f, -0.299861f, 0.112567f, 0.0666395f, 0.345303f, 0.164124f, -0.00265316f, -0.0732412f, 0.348079f, -0.249414f, 0.0465329f, 0.0693596f, 0.0799214f, 0.000123214f, 0.180679f, 0.0912923f, -0.300121f, -0.288428f, 0.150135f, 0.112936f, 0.104813f, -0.0555879f, -0.00205972f, -0.0251151f, -0.0788264f, -0.016778f, -0.110796f, -0.083048f, -0.212734f, 0.288568f, -0.114228f, -0.113358f, 0.110789f, 0.118645f, 0.133466f, -0.0298552f, -0.241374f, 0.157257f, 0.0861554f, -0.0909277f, 0.00156177f, 0.106539f, -0.209104f, -0.106974f, 0.0203283f, -0.18111f, -0.311602f, -0.00371812f, 0.0711113f, -0.206721f, 0.286076f, 0.139713f, 0.116621f, 0.182792f, 0.0246107f, -0.17972f, 0.041917f, 0.0724635f, 0.266344f, 0.0989191f, 0.0723898f, 0.0257298f, 0.104898f, 0.0681826f, -0.0704781f, 0.00212139f, -0.363547f, 0.0274255f, -0.106295f, -0.363965f, 0.127051f, -0.0575343f, -0.200952f, -0.0666189f, -0.139465f, -0.0171747f, 0.253794f, -0.258602f, -0.166356f, -0.107649f, 0.267331f, 0.104521f, -0.020921f, -0.0780469f, 0.125002f, 0.0202556f, -0.0899181f, -0.126559f, -0.297855f, 0.121539f, -0.0671643f, -0.0444782f, 0.334408f, 0.0882725f, -0.0879492f, -0.00277655f, -0.0616985f, 0.0564236f, -0.11618f, -0.22836f, 0.112953f, 0.176082f, 0.09988f, -0.00635589f, -0.114234f, 0.241135f, 0.0966775f, -0.0961065f, 0.137214f, -0.0832349f, -0.54299f, -0.2335f, -0.033801f, -0.11505f, -0.366386f, -0.238099f, -0.0951656f, 0.263106f, 0.129292f, -0.14762f, 0.0700404f, 0.0195349f, -0.286227f, -0.273371f, 0.0587288f, -0.257152f, -0.136248f, -0.13336f, -0.248086f, 0.273973f, -0.302625f, -0.085841f, -0.0839808f, -0.130464f, 0.252972f, -0.0415149f, -0.0695038f, -0.091557f, -0.262375f, -0.0645785f, 0.188566f, -0.202261f, -0.112712f, 0.00631479f, 0.0132917f, -0.0130675f, -0.302285f, 0.0556928f, -0.0211812f, -0.0555546f, 0.0291112f, 0.168815f, 0.143654f, -0.00564186f, -0.0614248f, -0.0939664f, 0.0959667f, -0.209823f, -0.103889f, -0.206011f, -0.0394793f, 0.0545815f, -0.0348762f, -0.132075f, -0.0489917f, -0.177563f, -0.164591f, -0.0174372f, -0.276844f, -0.132214f, -0.236278f, -0.0614254f, -0.230962f, -0.409367f, -0.08959f, 0.182197f, -0.341314f, -0.0645579f, -0.0161434f, -0.166644f, -0.0784324f, -0.387537f, 0.236617f, -0.115318f, -0.11315f, -0.109817f, -0.0949309f, -0.253715f, -0.254404f, -0.0876592f, -0.243118f, -0.219172f, 0.0341202f, 0.0203343f, 0.0435131f, -0.0266338f, 0.140304f, -0.20669f, -0.130739f, 0.0213059f, 0.182793f, -0.0711616f, -0.165651f, -0.212373f, -0.0972764f, -0.284464f, -0.0834676f, -0.129573f, -0.133945f, 0.0684521f, -0.133913f, 0.165726f, -0.176839f, -0.0940447f, -0.145421f, -0.0471074f, 0.00950449f, 0.0308656f, -0.00761046f, -0.19397f, -0.161623f, 0.10975f, -0.0398157f, 0.00168868f, 0.0626417f, -0.118388f, -0.134741f, -0.243707f, 0.146451f, -0.165854f, 0.0585878f, 0.0269307f, 0.163195f, -0.197056f, 0.0438799f, -0.152668f, -0.178631f, -0.167278f, 0.0258257f, -0.22958f, -0.101918f, 0.0360034f, -0.165612f, -0.112482f, -0.419959f, -0.369384f, 0.0468117f, 0.202511f, 0.161559f, 0.0360435f, -0.211843f, 0.0480519f, -0.252478f, -0.0951382f, 0.100791f, -0.379245f, -0.129869f, -0.036501f, 0.0685223f, 0.0247177f, -0.0751386f, -0.12451f, 0.244585f, -0.0103249f, -0.346383f, -0.300614f, 0.230366f, -0.187795f, -0.0326416f, 0.0735751f, -0.0136039f, -0.0219528f, 0.0629145f, -0.0308739f, -0.101514f, -0.169444f, 0.058706f, -0.133274f, -0.200294f, -0.372511f, -0.214898f, -0.184366f, 0.253648f, -0.0362453f, 0.0618937f, 0.0838244f, -0.0386255f, 0.129191f, -0.147435f, -0.180809f, -0.0797491f, -0.286544f, -0.273005f, 0.116222f, -0.255255f, -0.0504643f, -0.0567216f, -0.0204081f, 0.206331f, -0.225266f, -0.211665f, -0.259216f, -0.0676753f, -0.176153f, 0.285802f, -0.00560349f, -0.0253936f, -0.182537f, -0.344487f, -0.341246f, -0.171879f, 0.24462f, 0.015354f, -0.0255803f, -0.0855239f, -0.151488f, -0.0329621f, 0.311794f, 0.0889872f, -0.142655f, -0.00124048f, 0.0175189f, 0.0459686f, 0.279491f, -0.237445f, 0.0570048f, -0.00665275f, -0.0558817f, 0.0731352f, 0.0291331f, 0.0918153f, 0.0276626f, -0.135103f, -0.303909f, 0.0283329f, -0.203482f, -0.0849922f, -0.284485f, -0.214908f, 0.0836636f, -0.219738f, 0.136157f, 0.0332432f, -0.143305f, 0.0283252f, -0.178703f, -0.0742534f, -0.153174f, 0.02235f, -0.0753622f, -0.210102f, -0.0915751f, -0.0189732f, -0.239039f, -0.135349f, -0.104589f, -0.0658414f, -0.183206f, -0.123006f, 0.0835748f, -0.0703047f, -0.207461f, -0.274129f, -0.225327f, -0.113485f, 0.13316f, 0.0295303f, -0.0958281f};
   model->setOperandValue(op84, op84_init, sizeof(float) * 2816);
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op86, op2, op1, b87, b88, b89, b90}, {op0});
   model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op0, op29, op28, b91, b92, b93, b94, b95}, {op27});
   model->addOperation(ANEURALNETWORKS_CONV_2D, {op27, op32, op31, b96, b97, b98, b99}, {op30});
   model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op30, op35, op34, b100, b101, b102, b103, b104}, {op33});
diff --git a/nn/runtime/test/generated/models/mobilenet_quantized.model.cpp b/nn/runtime/test/generated/models/mobilenet_quantized.model.cpp
index 33d4ddfc6..0f7692336 100644
--- a/nn/runtime/test/generated/models/mobilenet_quantized.model.cpp
+++ b/nn/runtime/test/generated/models/mobilenet_quantized.model.cpp
@@ -617,7 +617,6 @@ void CreateModel(Model *model) {
   model->setOperandValue(op40, op40_init, sizeof(int32_t) * 128);
   static uint8_t op41_init[] = {130, 106, 119, 96, 123, 111, 103, 111, 123, 112, 130, 112, 136, 143, 130, 132, 125, 107, 116, 123, 123, 115, 111, 139, 135, 143, 115, 95, 134, 119, 108, 111, 108, 128, 128, 95, 107, 182, 115, 96, 125, 113, 106, 96, 128, 81, 121, 113, 101, 118, 134, 119, 111, 111, 139, 99, 129, 112, 117, 92, 123, 128, 120, 109, 115, 108, 108, 111, 118, 91, 120, 136, 121, 91, 111, 138, 113, 146, 136, 87, 117, 115, 111, 94, 117, 112, 70, 118, 109, 92, 82, 107, 133, 93, 113, 109, 113, 158, 104, 115, 111, 120, 114, 128, 121, 115, 114, 108, 104, 103, 123, 86, 112, 117, 103, 117, 143, 123, 104, 105, 80, 118, 96, 110, 115, 152, 106, 114, 101, 109, 126, 86, 113, 99, 99, 118, 110, 111, 116, 105, 74, 83, 110, 143, 136, 124, 124, 106, 95, 61, 109, 104, 76, 116, 118, 116, 80, 111, 125, 112, 113, 142, 105, 110, 128, 58, 112, 129, 163, 108, 86, 65, 129, 47, 135, 80, 123, 101, 158, 133, 114, 115, 83, 103, 101, 130, 110, 141, 74, 108, 106, 113, 114, 112, 95, 122, 154, 15, 100, 128, 123, 154, 116, 106, 108, 113, 98, 104, 106, 127, 99, 117, 130, 134, 132, 134, 125, 140, 54, 106, 158, 93, 109, 107, 104, 64, 109, 101, 80, 104, 118, 79, 176, 110, 116, 116, 158, 125, 136, 149, 127, 117, 114, 119, 113, 143, 109, 138, 50, 127, 72, 103, 110, 118, 94, 120, 111, 108, 103, 110, 113, 111, 109, 110, 120, 120, 98, 117, 131, 117, 113, 99, 118, 117, 113, 115, 120, 109, 107, 107, 125, 88, 110, 134, 131, 107, 111, 111, 114, 119, 114, 126, 110, 106, 112, 113, 117, 117, 137, 106, 103, 104, 101, 114, 115, 124, 115, 106, 123, 113, 118, 127, 112, 113, 108, 114, 123, 115, 114, 113, 116, 113, 106, 113, 114, 103, 113, 115, 116, 116, 115, 99, 122, 107, 139, 150, 120, 115, 112, 131, 102, 102, 142, 123, 114, 114, 102, 103, 123, 118, 120, 113, 114, 120, 106, 124, 124, 114, 112, 126, 73, 119, 113, 114, 111, 113, 104, 114, 103, 114, 107, 116, 88, 115, 108, 112, 84, 114, 108, 112, 119, 76, 109, 112, 171, 111, 123, 109, 139, 119, 126, 121, 108, 111, 172, 112, 81, 76, 103, 143, 111, 116, 121, 137, 104, 126, 106, 252, 103, 172, 118, 70, 155, 113, 104, 109, 109, 98, 161, 129, 93, 54, 117, 110, 98, 113, 108, 120, 116, 124, 87, 117, 122, 158, 113, 123, 113, 103, 122, 101, 149, 140, 124, 139, 111, 177, 103, 110, 109, 113, 106, 116, 111, 118, 150, 116, 123, 138, 120, 107, 110, 117, 117, 153, 106, 126, 122, 78, 129, 90, 149, 99, 83, 149, 119, 110, 113, 87, 110, 112, 115, 87, 111, 121, 122, 109, 125, 142, 86, 109, 123, 120, 127, 99, 123, 149, 119, 118, 142, 121, 174, 106, 106, 90, 104, 123, 118, 122, 111, 208, 125, 121, 78, 120, 137, 108, 113, 163, 147, 140, 87, 95, 100, 108, 159, 155, 77, 144, 106, 149, 134, 91, 105, 183, 172, 72, 146, 111, 146, 118, 52, 145, 143, 103, 155, 85, 95, 108, 146, 161, 140, 105, 84, 110, 87, 121, 127, 120, 138, 151, 140, 70, 112, 160, 94, 98, 95, 94, 77, 101, 142, 75, 149, 65, 79, 112, 90, 105, 106, 147, 80, 120, 102, 111, 129, 82, 139, 117, 97, 64, 0, 100, 105, 123, 147, 118, 137, 121, 92, 89, 143, 83, 120, 119, 109, 115, 107, 179, 148, 147, 112, 85, 155, 97, 138, 74, 108, 106, 138, 150, 77, 137, 134, 84, 144, 139, 229, 88, 111, 96, 255, 129, 98, 72, 120, 133, 91, 109, 152, 141, 100, 111, 111, 119, 114, 110, 116, 114, 112, 119, 76, 120, 108, 117, 134, 101, 110, 97, 111, 120, 118, 112, 103, 18, 104, 59, 112, 156, 149, 111, 104, 115, 102, 109, 114, 130, 106, 121, 114, 116, 107, 116, 121, 119, 110, 117, 125, 117, 106, 108, 115, 110, 118, 114, 135, 115, 122, 96, 110, 127, 111, 101, 119, 114, 114, 114, 107, 113, 114, 124, 116, 114, 111, 115, 111, 129, 117, 127, 148, 95, 116, 115, 116, 150, 107, 144, 101, 110, 119, 113, 120, 112, 113, 117, 116, 91, 114, 115, 111, 133, 105, 116, 112, 146, 130, 115, 114, 113, 116, 110, 107, 112, 107, 113, 119, 125, 61, 109, 106, 97, 116, 132, 114, 117, 118, 24, 118, 112, 121, 106, 104, 137, 115, 111, 113, 110, 119, 121, 117, 118, 122, 117, 115, 96, 106, 117, 114, 121, 104, 110, 111, 135, 110, 125, 112, 107, 120, 106, 112, 113, 118, 119, 110, 128, 109, 109, 111, 141, 112, 117, 133, 130, 108, 140, 110, 114, 116, 116, 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115, 113, 105, 108, 112, 107, 111, 121, 113, 114, 114, 111, 117, 116, 112, 119, 107, 113, 116, 103, 110, 114, 113, 114, 113, 119, 114, 103, 114, 104, 109, 123, 121, 114, 113, 114, 116, 113, 115, 93, 113, 110, 113, 115, 111, 117, 117, 121, 112, 124, 116, 112, 111, 115, 114, 108, 117, 114, 119, 123, 116, 129, 112, 107, 110, 116, 115, 114, 120, 114, 113, 108, 117, 125, 111, 114, 116, 114, 113, 118, 120, 122, 122, 115, 117, 113, 113, 120, 113, 115, 111, 115, 112, 115, 125, 108, 109, 114, 116, 119, 113, 104, 110, 117, 114, 119, 114, 121, 130, 117, 113, 111, 115, 114, 116, 117, 109, 111, 122, 116, 106, 112, 111, 105, 138, 113, 122, 115, 117, 91, 111, 112};
   model->setOperandValue(op41, op41_init, sizeof(uint8_t) * 1152);
-  model->addOperation(ANEURALNETWORKS_CONV_2D, {op88, op2, op1, b104, b105, b106, b107}, {op0});
   static int32_t op43_init[] = {-9119, 406, 8026, -2442, 22035, 7830, 5239, -16418, 3066, 244, 17626, -11691, -4541, 14457, 8384, 3859, -8220, -7972, -3881, -3717, 2242, -11349, -13582, 486, 3455, -2435, -1912, 3185, -10701, 3372, -3150, 6759, 10970, 6665, 16016, 2817, 14058, -556, 7218, -8752, 11568, -9512, -11502, -4894, 4890, -1483, 7517, 9618, 3061, 12316, 19276, 10143, -23717, -5637, 13399, -2423, 4260, 799, 2376, 3188, 4820, 7535, -3916, 13854, 14245, -704, -770, 1514, 3930, 745, 1798, -5644, -3217, 19698, -265, -26449, 11816, -20746, -2139, 1080, -13117, -2232, 4019, -4479, -6283, 1058, 16636, 16248, 3525, -2806, -2207, 3284, 952, 6117, 15768, -10433, 14577, -8859, -11789, 7781, 16966, 18525, -3438, 7560, 211, 3327, -807, 17839, -2552, 9905, 2938, -3158, 5764, 7175, 4135, -10571, 16909, 17722, 16820, 1561, 9099, 7644, 21318, 1901, 22449, 60, -7215, -9300};
   model->setOperandValue(op43, op43_init, sizeof(int32_t) * 128);
   static uint8_t op44_init[] = {117, 122, 124, 128, 124, 104, 122, 132, 111, 133, 115, 130, 122, 119, 110, 126, 129, 110, 114, 115, 128, 111, 113, 124, 128, 126, 126, 125, 121, 115, 115, 132, 118, 105, 130, 136, 125, 113, 120, 122, 117, 118, 125, 123, 103, 117, 107, 122, 104, 116, 118, 125, 119, 132, 118, 125, 121, 125, 155, 120, 125, 127, 117, 120, 112, 121, 126, 121, 121, 120, 120, 121, 112, 108, 173, 136, 126, 117, 134, 114, 131, 120, 104, 124, 124, 128, 122, 116, 116, 114, 123, 125, 132, 129, 131, 156, 116, 119, 121, 133, 120, 125, 118, 126, 125, 123, 113, 121, 116, 119, 122, 119, 113, 117, 118, 124, 123, 143, 121, 137, 142, 133, 136, 105, 127, 121, 88, 100, 127, 125, 122, 116, 119, 131, 112, 127, 112, 114, 126, 124, 123, 135, 125, 122, 106, 117, 123, 136, 138, 119, 107, 123, 126, 125, 121, 129, 128, 133, 108, 137, 85, 106, 105, 97, 125, 132, 98, 122, 115, 122, 125, 122, 124, 126, 145, 143, 107, 123, 116, 123, 114, 123, 137, 118, 116, 138, 141, 119, 128, 122, 131, 133, 120, 117, 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123, 125, 128, 123, 125, 126, 128, 126, 124, 133, 122, 121, 134, 126, 132, 126, 121, 128, 124, 133, 126, 125, 119, 125, 128, 131, 120, 121, 123, 121, 118, 125, 115, 122, 122, 114, 125, 122, 123, 127, 120, 119, 128, 127, 123, 134, 126, 122, 131, 130, 123, 125, 141, 133, 122, 121, 125, 125, 128, 130, 119, 139, 110, 124, 118, 124, 127, 111, 124, 119, 114, 121, 125, 128, 119, 123, 124, 125, 125, 132, 129, 132, 124, 130, 118, 143, 125, 131, 130, 123, 122, 128, 124, 124, 126, 123, 116, 123, 129, 119, 120, 113, 127, 113, 120, 119, 106, 118, 121, 127, 130, 126, 119, 115, 131, 121, 120, 129, 116, 123, 123, 127, 124, 119, 124, 118, 132, 120, 107, 120, 111, 115, 115, 122, 125, 122, 119, 103, 116, 118, 123, 119, 123, 137, 122, 115, 117, 119, 125, 122, 125, 122, 125, 121, 123, 131, 121, 118, 123, 130, 128, 129, 122, 125, 118, 119, 124, 125, 116, 108, 131, 118, 121, 123, 117, 118, 131, 119, 117, 117, 126, 114, 124, 127, 124, 120, 114, 125, 126, 119, 126, 129, 130, 116, 127, 132, 126, 117, 138, 123, 114, 123, 124, 110, 123, 115, 117, 124, 116, 119, 122, 117, 125, 123, 113, 118, 112, 125, 128, 122, 112, 107, 124, 107, 127, 133, 117, 158, 121, 123, 117, 126, 125, 122, 126, 128, 138, 120, 122, 120, 89, 124, 120, 122, 120, 121, 118, 119, 123, 124, 116, 133, 120, 122, 125, 123, 121, 125, 125, 124, 119, 115, 126, 124, 121, 123, 125, 86, 119, 106, 117, 124, 124, 120, 123, 121, 149, 120, 154, 124, 99, 125, 122, 123, 121, 122, 120, 125, 120, 123, 121, 121, 121, 123, 126, 126, 125, 122, 121, 119, 118, 126, 122, 125, 123, 92, 120, 123, 120, 148, 124, 119, 121, 121, 121, 119, 126, 128, 126, 215, 127, 124, 121, 128, 122, 125, 128, 126, 123, 125, 124, 123, 122, 123, 126, 124, 120, 117, 125, 117, 120, 115, 123, 119, 123, 124, 118, 128, 115, 120, 122, 125, 124, 116, 121, 122, 124, 118, 126, 124, 136, 111, 132, 116, 116, 125, 124, 119, 118, 130, 121, 130, 103, 95, 121, 127, 121, 125, 122, 121, 120, 129, 111, 128, 126, 150, 122, 122, 131, 132, 123, 155, 172, 123, 121, 124, 125, 124, 121, 116, 120, 120, 121, 123, 117, 128, 123, 138, 115, 147, 136, 119, 119, 121, 121, 119, 138, 125, 132, 123, 106, 140, 120, 127, 123, 129, 124, 116, 106, 124, 122, 127, 123, 123, 111, 116, 122, 123, 118, 126, 132, 112, 113, 122, 115, 123, 131, 122, 119, 147, 110, 123, 111, 130, 118, 119, 108, 122, 122, 124, 102, 110, 131, 117, 131, 120, 107, 124, 113, 121, 107, 125, 122, 126, 114, 117, 117, 113, 120, 112, 117, 108, 133, 110, 124, 122, 123, 119, 119, 128, 123, 117, 120, 114, 123, 122, 125, 124, 120, 126, 123, 123, 107, 116, 142, 110, 89, 119, 76, 119, 101, 127, 117, 118, 129, 120, 126, 133, 118, 121, 120, 123, 132, 108, 142, 122, 150, 126, 123, 125, 119, 119, 131, 111, 105, 124, 123, 122, 115, 109, 114, 123, 129, 120, 126, 116, 115, 127, 123, 120, 91, 126, 121, 115, 122, 118, 124, 124, 123, 118, 128, 119, 126, 118, 117, 122, 126, 118, 120, 122, 125, 54, 120, 113, 127, 133, 114, 126, 118, 121, 125, 120, 121, 120, 128, 120, 127, 118, 120, 127, 123, 118, 121, 122, 122, 115, 120, 171, 126, 124, 124, 117, 129, 109, 128, 116, 114, 127, 120, 122, 132, 112, 110, 123, 110, 110, 123, 131, 124, 120, 120, 255, 113, 117, 130, 117, 105, 104, 129, 115, 120, 123, 126, 226, 97, 117, 93, 110, 104, 129, 132, 128, 121, 132, 126, 121, 133, 111, 127, 114, 113, 116, 103, 116, 108, 123, 111, 127, 108, 121, 111, 123, 120, 105, 122, 119, 125, 125, 253, 134, 118, 114, 124, 127, 139, 110, 119, 106, 121, 117, 134, 122, 117, 122, 117, 119, 119, 108, 130, 125, 108, 124, 115, 128, 129, 120, 123, 109, 120, 108, 113, 121, 110, 119, 127, 109, 126, 125, 124, 146, 118, 123, 118, 144, 121, 123, 113, 116, 114, 107, 135, 113, 102, 113, 121, 114, 130, 127, 112, 123, 109, 110, 122, 127, 115, 114, 107, 109, 123, 125, 111, 112, 122, 97, 118, 112, 134, 90, 126, 123, 126, 130, 123, 111, 116, 124, 112, 123, 121, 137, 127, 125, 116, 136, 116, 130, 127, 100, 127, 129, 104, 116, 117, 114, 121, 119, 115, 145, 126, 127, 130, 134, 114, 98, 123, 116, 121, 69, 118, 114, 126, 126, 116, 124, 117, 138, 126, 127, 80, 119, 127, 120, 113, 120, 126, 125, 121, 122, 122, 124, 115, 129, 119, 118, 121, 133, 124, 129, 123, 103, 123, 126, 137, 125, 128, 123, 121, 121, 126, 142, 111, 118, 122, 130, 122, 125, 132, 121, 123, 111, 117, 129, 126, 120, 124, 130, 123, 118, 127, 130, 129, 115, 126, 116, 133, 116, 113, 120, 118, 120, 117, 118, 121, 142, 129, 122, 118, 118, 113, 122, 114, 120, 126, 133, 127, 117, 119, 119, 145, 130, 117, 118, 114, 123, 113, 143, 122, 160, 121, 120, 122, 132, 119, 138, 124, 134, 124, 125, 111, 123, 115, 123, 156, 117, 105, 124, 123, 116, 115, 143, 126, 104, 125, 122, 119, 115, 111, 121, 116, 120, 116, 122, 117, 107, 122, 123, 126, 115, 132, 123, 124, 125, 127, 112, 118, 165, 117, 115, 114, 128, 118, 115, 131, 125, 107, 122, 111, 128, 127, 123, 190, 147, 112, 111, 120, 125, 139, 110, 112, 111, 104, 119, 136, 118, 107, 122, 127, 126, 109, 128, 121, 122, 133, 116, 153, 110, 124, 119, 123, 127, 117, 134, 119, 150, 126, 123, 109, 116, 120, 119, 125, 127, 126, 123, 89, 122, 110, 122, 121, 119, 123, 120, 125, 125, 140, 117, 120, 114, 127, 121, 125, 123, 123, 119, 124, 127, 121, 120, 122, 122, 135, 122, 120, 122, 121, 122, 121, 120, 118, 113, 122, 126, 125, 118, 109, 128, 136, 124, 116, 121, 125, 126, 123, 121, 108, 119, 102, 120, 121, 122, 125, 127, 112, 122, 118, 126, 121, 120, 119, 104, 122, 122, 88, 123, 121, 121, 123, 121, 122, 122, 116, 122, 123, 124, 123, 123, 116, 121, 119, 120, 124, 122, 119, 134, 120, 122, 120, 107, 126, 122, 126, 135, 123, 123, 132, 123, 120, 120, 119, 121, 120, 121, 121, 130, 118, 121, 122, 120, 124, 123, 127, 129, 124, 125, 115, 127, 118, 120, 123, 123, 121, 99, 123, 121, 125, 95, 123, 121, 119, 119, 127, 109, 123, 117, 114, 123, 126, 122, 126, 112, 117, 128, 124, 122, 123, 122, 115, 123, 120, 122, 123, 114, 123, 116, 122, 102, 127, 116, 111, 120, 115, 124, 126, 121, 119, 122, 119, 117, 121, 121, 120, 113, 123, 122, 126, 120, 134, 114, 123, 121, 118, 121, 121, 123, 136, 113, 123, 122, 108, 118, 123, 118, 131, 129, 110, 124, 126, 122, 118, 125, 121, 127, 119, 124, 121, 130, 122, 121, 122, 121, 116, 120, 122, 128, 128, 128, 120, 121, 116, 125, 129, 123, 122, 125, 119, 126, 112, 125, 121, 117, 110, 128, 115, 124, 120, 122, 124, 112, 119, 120, 116, 118, 122, 122, 121, 122, 119, 122, 123, 124, 97, 127, 118, 120, 119, 125, 127, 124, 123, 125, 110, 121, 120, 118, 126, 120, 121, 122, 126, 122, 127, 128, 118, 128, 119, 126, 126, 124, 124, 125, 123, 129, 120, 124, 123, 126, 122, 119, 120, 131, 124, 114, 158, 125, 115, 122, 122, 124, 120, 129, 126, 118, 119, 124, 123, 115, 118, 121, 126, 121, 124, 119, 124, 126, 126, 126, 125, 119, 87, 121, 122, 124, 118, 116, 123, 127, 112, 120, 122, 122, 121, 123, 124, 133, 122, 122, 114, 120, 123, 97, 121, 123, 117, 112, 127, 124, 117, 120, 118, 122, 128, 130, 123, 122, 120, 121, 120, 118, 121, 135, 126, 121, 121, 124, 123, 125, 123, 116, 113, 120, 120, 137, 128, 122, 121, 123, 120, 131, 125, 123, 120, 113, 121, 114, 114, 121, 93, 127, 117, 130, 137, 119, 120, 122, 131, 126, 117, 131, 126, 134, 124, 132, 125, 131, 131, 116, 133, 119, 103, 121, 118, 117, 125, 118, 134, 110, 122, 125, 118, 121, 123, 124, 123, 143, 132, 119, 114, 125, 122, 114, 121, 124, 128, 109, 126, 139, 119, 126, 123, 121, 134, 127, 123, 122, 119, 120, 121, 125, 111, 110, 146, 117, 122, 122, 121, 127, 129, 121, 121, 124, 128, 122, 126, 126, 123, 121, 120, 121, 128, 124, 128, 124, 127, 116, 135, 126, 119, 117, 136, 128, 119, 135, 129, 106, 133, 118, 117, 118, 116, 121, 131, 125, 127, 125, 120, 126, 115, 124, 115, 128, 117, 105, 123, 116, 133, 120, 124, 119, 122, 121, 123, 122, 125, 125, 120, 120, 123, 124, 120, 114, 124, 123, 121, 122, 123, 122, 124, 121, 93, 115, 101, 122, 134, 124, 123, 122, 121, 126, 121, 122, 123, 117, 126, 123, 122, 118, 119, 132, 111, 121, 131, 121, 124, 121, 123, 129, 123, 119, 119, 126, 122, 120, 123, 125, 126, 124, 126, 119, 123, 121, 124, 120, 121, 122, 138, 128, 124, 123, 121, 121, 121, 121, 121, 120, 126, 122, 121, 120, 121, 122, 121, 120, 115, 120, 125, 112, 122, 129, 117, 125, 122, 122, 121, 123, 123, 125, 124, 123, 118, 121, 124, 123, 122, 126, 119, 125, 126, 120, 122, 118, 120, 136, 123, 126, 115, 117, 118, 116, 120, 120, 131, 123, 125, 137, 125, 123, 117, 128, 113, 111, 122, 111, 126, 124, 117, 123, 122, 126, 124, 112, 121, 117, 131, 112, 118, 108, 123, 122, 119, 106, 120, 133, 107, 106, 124, 142, 124, 118, 114, 118, 102, 116, 122, 115, 119, 125, 122, 123, 124, 123, 119, 154, 116, 108, 122, 129, 121, 115, 116, 112, 103, 122, 120, 126, 135, 122, 139, 120, 144, 124, 128, 124, 124, 114, 121, 126, 118, 119, 100, 127, 123, 120, 118, 113, 122, 125, 120, 114, 127, 119, 112, 123, 145, 121, 120, 127, 132, 116, 123, 129, 126, 122, 111, 131, 125, 120, 102, 126, 125, 120, 113, 151, 142, 118, 103, 124, 115, 120, 111, 122, 116, 123, 120, 118, 104, 126, 118, 106, 114, 115, 120, 118, 117, 174, 117, 120, 124, 121, 119, 130, 125, 116, 127, 128, 119, 125, 135, 119, 122, 113, 126, 122, 133, 124, 120, 133, 125, 114, 126, 120, 125, 121, 122, 121, 121, 118, 122, 128, 117, 120, 121, 120, 134, 98, 126, 119, 126, 118, 121, 122, 120, 122, 126, 121, 119, 122, 135, 123, 122, 117, 126, 120, 120, 115, 123, 124, 123, 125, 121, 118, 119, 120, 123, 123, 119, 110, 125, 110, 127, 121, 119, 97, 122, 122, 123, 137, 124, 119, 119, 122, 122, 126, 122, 118, 121, 107, 124, 121, 117, 114, 123, 120, 114, 117, 121, 119, 116, 121, 121, 119, 120, 133, 121, 104, 120, 110, 122, 127, 118, 118, 122, 117, 120, 116, 124, 124, 122, 118, 108, 117, 122, 123, 124, 128, 104, 96, 111, 134, 130, 117, 124, 120, 120, 106, 122, 130, 117, 120, 113, 125, 128, 105, 119, 117, 124, 115, 120, 117, 111, 121, 123, 154, 132, 132, 110, 116, 123, 113, 127, 126, 120, 124, 127, 127, 126, 113, 124, 140, 136, 121, 120, 133, 123, 115, 116, 117, 93, 111, 122, 122, 124, 114, 116, 109, 133, 118, 126, 117, 123, 127, 111, 110, 121, 132, 109, 114, 127, 127, 153, 119, 121, 132, 122, 126, 133, 139, 131, 137, 128, 121, 134, 120, 124, 119, 112, 125, 112, 125, 111, 125, 116, 125, 127, 126, 118, 122, 120, 132, 111, 119, 115, 116, 117, 130, 111, 123, 98, 119, 120, 125, 113, 121, 124, 122, 122, 137, 121, 117, 119, 122, 121, 104, 119, 113, 109, 134, 121, 126, 114, 125, 120, 122, 117, 113, 123, 119, 117, 130, 120, 123, 122, 124, 121, 127, 117, 110, 120, 117, 120, 122, 117, 107, 123, 113, 122, 115, 121, 118, 121, 118, 119, 119, 118, 122, 121, 125, 127, 129, 128, 120, 124, 110, 122, 118, 124, 116, 124, 120, 121, 126, 146, 101, 121, 123, 107, 121, 120, 122, 125, 126, 120, 120, 116, 122, 122, 118, 123, 122, 133, 114, 120, 119, 125, 121, 120, 128, 125, 115, 122, 116, 121, 125, 129, 120, 123, 120, 117, 128, 122, 116, 114, 121, 115, 121, 116, 120, 114, 120, 123, 123, 119, 119, 119, 120, 120, 119, 114, 123, 126, 113, 116, 112, 124, 114, 140, 126, 117, 121, 119, 128, 127, 117, 111, 122, 122, 129, 123, 123, 123, 116, 123, 120, 118, 110, 127, 132, 122, 124, 119, 121, 120, 128, 123, 124, 118, 115, 128, 126, 103, 123, 138, 118, 114, 105, 113, 117, 125, 121, 123, 120, 122, 121, 123, 115, 94, 121, 122, 129, 116, 123, 122, 106, 133, 124, 120, 121, 117, 126, 120, 102, 105, 125, 128, 120, 121, 116, 109, 99, 116, 120, 127, 119, 120, 127, 133, 123, 114, 125, 122, 124, 122, 97, 133, 179, 133, 120, 131, 118, 127, 126, 123, 114, 120, 124, 120, 116, 127, 126, 128, 125, 116, 158, 129, 96, 126, 120, 128, 123, 129, 125, 105, 123, 133, 119, 118, 124, 123, 116, 121, 135, 121, 117, 125, 119, 126, 121, 125, 123, 149, 95, 123, 128, 131, 115, 131, 126, 88, 100, 126, 109, 188, 122, 122, 126, 116, 121, 127, 120, 122, 114, 116, 127, 119, 120, 137, 127, 113, 124, 112, 121, 127, 121, 123, 128, 128, 118, 118, 124, 123, 114, 113, 114, 125, 121, 118, 128, 116, 125, 124, 124, 122, 113, 121, 119, 125, 130, 124, 126, 122, 122, 120, 117, 120, 129, 83, 114, 114, 114, 112, 122, 120, 115, 122, 120, 122, 132, 122, 127, 100, 184, 121, 105, 124, 120, 129, 120, 125, 122, 126, 123, 139, 118, 128, 113, 131, 130, 118, 117, 127, 136, 112, 116, 130, 116, 127, 125, 119, 122, 117, 117, 143, 117, 127, 128, 121, 115, 135, 107, 117, 98, 126, 105, 118, 117, 122, 128, 128, 111, 118, 127, 132, 141, 126, 116, 113, 143, 116, 109, 117, 120, 98, 129, 120, 129, 117, 122, 122, 113, 124, 115, 106, 115, 129, 134, 106, 134, 109, 114, 120, 112, 126, 118, 124, 126, 123, 131, 122, 117, 117, 113, 118, 105, 117, 138, 129, 123, 115, 137, 150, 115, 123, 121, 139, 118, 117, 112, 133, 122, 120, 117, 119, 118, 117, 113, 123, 130, 116, 112, 127, 117, 110, 123, 122, 101, 123, 126, 113, 118, 123, 121, 149, 121, 123, 135, 138, 125, 144, 114, 123, 121, 114, 113, 115, 106, 117, 123, 125, 113, 117, 128, 120, 117, 150, 123, 121, 120, 123, 122, 124, 105, 121, 120, 138, 123, 116, 108, 111, 124, 123};
@@ -676,6 +675,7 @@ void CreateModel(Model *model) {
   model->setOperandValue(op84, op84_init, sizeof(uint8_t) * 1025024);
   static int32_t op87_init[] = {1, 1001};
   model->setOperandValue(op87, op87_init, sizeof(int32_t) * 2);
+  model->addOperation(ANEURALNETWORKS_CONV_2D, {op88, op2, op1, b104, b105, b106, b107}, {op0});
   model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op0, op29, op28, b108, b109, b110, b111, b112}, {op27});
   model->addOperation(ANEURALNETWORKS_CONV_2D, {op27, op32, op31, b113, b114, b115, b116}, {op30});
   model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op30, op35, op34, b117, b118, b119, b120, b121}, {op33});
diff --git a/nn/runtime/test/generated/models/pad_float_1_relaxed.model.cpp b/nn/runtime/test/generated/models/pad_float_1_relaxed.model.cpp
new file mode 100644
index 000000000..79e94e52a
--- /dev/null
+++ b/nn/runtime/test/generated/models/pad_float_1_relaxed.model.cpp
@@ -0,0 +1,26 @@
+// Generated file (from: pad_float_1_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 3, 1});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 4, 7, 1});
+  OperandType type1(Type::TENSOR_INT32, {4, 2});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t op2_init[] = {0, 0, 0, 2, 1, 3, 0, 0};
+  model->setOperandValue(op2, op2_init, sizeof(int32_t) * 8);
+  model->addOperation(ANEURALNETWORKS_PAD, {op1, op2}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/pad_relaxed.model.cpp b/nn/runtime/test/generated/models/pad_relaxed.model.cpp
new file mode 100644
index 000000000..bfdd87fc1
--- /dev/null
+++ b/nn/runtime/test/generated/models/pad_relaxed.model.cpp
@@ -0,0 +1,26 @@
+// Generated file (from: pad_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 4, 4, 1});
+  OperandType type1(Type::TENSOR_INT32, {4, 2});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t op2_init[] = {0, 0, 1, 1, 1, 1, 0, 0};
+  model->setOperandValue(op2, op2_init, sizeof(int32_t) * 8);
+  model->addOperation(ANEURALNETWORKS_PAD, {op1, op2}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/relu_float_2_relaxed.model.cpp b/nn/runtime/test/generated/models/relu_float_2_relaxed.model.cpp
new file mode 100644
index 000000000..ac0c412be
--- /dev/null
+++ b/nn/runtime/test/generated/models/relu_float_2_relaxed.model.cpp
@@ -0,0 +1,21 @@
+// Generated file (from: relu_float_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 64, 40, 2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto output = model->addOperand(&type0);
+  // Phase 2, operations
+  model->addOperation(ANEURALNETWORKS_RELU, {input}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/resize_bilinear_2_relaxed.model.cpp b/nn/runtime/test/generated/models/resize_bilinear_2_relaxed.model.cpp
new file mode 100644
index 000000000..4d196b023
--- /dev/null
+++ b/nn/runtime/test/generated/models/resize_bilinear_2_relaxed.model.cpp
@@ -0,0 +1,29 @@
+// Generated file (from: resize_bilinear_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 2});
+  OperandType type1(Type::TENSOR_FLOAT32, {1, 3, 3, 2});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto height = model->addOperand(&type2);
+  auto width = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t height_init[] = {3};
+  model->setOperandValue(height, height_init, sizeof(int32_t) * 1);
+  static int32_t width_init[] = {3};
+  model->setOperandValue(width, width_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_RESIZE_BILINEAR, {op1, height, width}, {op2});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1},
+    {op2});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/space_to_batch_float_1_relaxed.model.cpp b/nn/runtime/test/generated/models/space_to_batch_float_1_relaxed.model.cpp
new file mode 100644
index 000000000..dfd2d6035
--- /dev/null
+++ b/nn/runtime/test/generated/models/space_to_batch_float_1_relaxed.model.cpp
@@ -0,0 +1,30 @@
+// Generated file (from: space_to_batch_float_1_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 4, 4, 1});
+  OperandType type3(Type::TENSOR_FLOAT32, {4, 2, 2, 1});
+  OperandType type2(Type::TENSOR_INT32, {2, 2});
+  OperandType type1(Type::TENSOR_INT32, {2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto block_size = model->addOperand(&type1);
+  auto paddings = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t block_size_init[] = {2, 2};
+  model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2);
+  static int32_t paddings_init[] = {0, 0, 0, 0};
+  model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4);
+  model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/space_to_batch_float_2_relaxed.model.cpp b/nn/runtime/test/generated/models/space_to_batch_float_2_relaxed.model.cpp
new file mode 100644
index 000000000..09c98af93
--- /dev/null
+++ b/nn/runtime/test/generated/models/space_to_batch_float_2_relaxed.model.cpp
@@ -0,0 +1,30 @@
+// Generated file (from: space_to_batch_float_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 5, 2, 1});
+  OperandType type3(Type::TENSOR_FLOAT32, {6, 2, 2, 1});
+  OperandType type2(Type::TENSOR_INT32, {2, 2});
+  OperandType type1(Type::TENSOR_INT32, {2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto block_size = model->addOperand(&type1);
+  auto paddings = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t block_size_init[] = {3, 2};
+  model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2);
+  static int32_t paddings_init[] = {1, 0, 2, 0};
+  model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4);
+  model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/space_to_batch_float_3_relaxed.model.cpp b/nn/runtime/test/generated/models/space_to_batch_float_3_relaxed.model.cpp
new file mode 100644
index 000000000..7c75a611d
--- /dev/null
+++ b/nn/runtime/test/generated/models/space_to_batch_float_3_relaxed.model.cpp
@@ -0,0 +1,30 @@
+// Generated file (from: space_to_batch_float_3_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 4, 2, 1});
+  OperandType type3(Type::TENSOR_FLOAT32, {6, 2, 4, 1});
+  OperandType type2(Type::TENSOR_INT32, {2, 2});
+  OperandType type1(Type::TENSOR_INT32, {2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto block_size = model->addOperand(&type1);
+  auto paddings = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t block_size_init[] = {3, 2};
+  model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2);
+  static int32_t paddings_init[] = {1, 1, 2, 4};
+  model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4);
+  model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/space_to_batch_relaxed.model.cpp b/nn/runtime/test/generated/models/space_to_batch_relaxed.model.cpp
new file mode 100644
index 000000000..fa24e8f91
--- /dev/null
+++ b/nn/runtime/test/generated/models/space_to_batch_relaxed.model.cpp
@@ -0,0 +1,30 @@
+// Generated file (from: space_to_batch_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 2});
+  OperandType type3(Type::TENSOR_FLOAT32, {4, 1, 1, 2});
+  OperandType type2(Type::TENSOR_INT32, {2, 2});
+  OperandType type1(Type::TENSOR_INT32, {2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto block_size = model->addOperand(&type1);
+  auto paddings = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t block_size_init[] = {2, 2};
+  model->setOperandValue(block_size, block_size_init, sizeof(int32_t) * 2);
+  static int32_t paddings_init[] = {0, 0, 0, 0};
+  model->setOperandValue(paddings, paddings_init, sizeof(int32_t) * 4);
+  model->addOperation(ANEURALNETWORKS_SPACE_TO_BATCH_ND, {input, block_size, paddings}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/squeeze_float_1_relaxed.model.cpp b/nn/runtime/test/generated/models/squeeze_float_1_relaxed.model.cpp
new file mode 100644
index 000000000..57ba0b31a
--- /dev/null
+++ b/nn/runtime/test/generated/models/squeeze_float_1_relaxed.model.cpp
@@ -0,0 +1,26 @@
+// Generated file (from: squeeze_float_1_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 24, 1});
+  OperandType type2(Type::TENSOR_FLOAT32, {1, 24});
+  OperandType type1(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto squeezeDims = model->addOperand(&type1);
+  auto output = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t squeezeDims_init[] = {2};
+  model->setOperandValue(squeezeDims, squeezeDims_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_SQUEEZE, {input, squeezeDims}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/squeeze_relaxed.model.cpp b/nn/runtime/test/generated/models/squeeze_relaxed.model.cpp
new file mode 100644
index 000000000..9a4108944
--- /dev/null
+++ b/nn/runtime/test/generated/models/squeeze_relaxed.model.cpp
@@ -0,0 +1,26 @@
+// Generated file (from: squeeze_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {4, 1, 1, 2});
+  OperandType type2(Type::TENSOR_FLOAT32, {4, 2});
+  OperandType type1(Type::TENSOR_INT32, {2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto squeezeDims = model->addOperand(&type1);
+  auto output = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t squeezeDims_init[] = {1, 2};
+  model->setOperandValue(squeezeDims, squeezeDims_init, sizeof(int32_t) * 2);
+  model->addOperation(ANEURALNETWORKS_SQUEEZE, {input, squeezeDims}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/strided_slice_float_10_relaxed.model.cpp b/nn/runtime/test/generated/models/strided_slice_float_10_relaxed.model.cpp
new file mode 100644
index 000000000..bb119d6b8
--- /dev/null
+++ b/nn/runtime/test/generated/models/strided_slice_float_10_relaxed.model.cpp
@@ -0,0 +1,42 @@
+// Generated file (from: strided_slice_float_10_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {1, 3});
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 3});
+  OperandType type1(Type::TENSOR_INT32, {2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto begins = model->addOperand(&type1);
+  auto ends = model->addOperand(&type1);
+  auto strides = model->addOperand(&type1);
+  auto beginMask = model->addOperand(&type2);
+  auto endMask = model->addOperand(&type2);
+  auto shrinkAxisMask = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t begins_init[] = {1, 0};
+  model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2);
+  static int32_t ends_init[] = {2, 2};
+  model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2);
+  static int32_t strides_init[] = {1, 1};
+  model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2);
+  static int32_t beginMask_init[] = {0};
+  model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1);
+  static int32_t endMask_init[] = {2};
+  model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1);
+  static int32_t shrinkAxisMask_init[] = {0};
+  model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/strided_slice_float_11_relaxed.model.cpp b/nn/runtime/test/generated/models/strided_slice_float_11_relaxed.model.cpp
new file mode 100644
index 000000000..6ef5523fd
--- /dev/null
+++ b/nn/runtime/test/generated/models/strided_slice_float_11_relaxed.model.cpp
@@ -0,0 +1,42 @@
+// Generated file (from: strided_slice_float_11_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 3});
+  OperandType type3(Type::TENSOR_FLOAT32, {3});
+  OperandType type1(Type::TENSOR_INT32, {2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto begins = model->addOperand(&type1);
+  auto ends = model->addOperand(&type1);
+  auto strides = model->addOperand(&type1);
+  auto beginMask = model->addOperand(&type2);
+  auto endMask = model->addOperand(&type2);
+  auto shrinkAxisMask = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t begins_init[] = {0, 0};
+  model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2);
+  static int32_t ends_init[] = {2, 3};
+  model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2);
+  static int32_t strides_init[] = {1, 1};
+  model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2);
+  static int32_t beginMask_init[] = {0};
+  model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1);
+  static int32_t endMask_init[] = {0};
+  model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1);
+  static int32_t shrinkAxisMask_init[] = {1};
+  model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/strided_slice_float_1_relaxed.model.cpp b/nn/runtime/test/generated/models/strided_slice_float_1_relaxed.model.cpp
new file mode 100644
index 000000000..af53508bf
--- /dev/null
+++ b/nn/runtime/test/generated/models/strided_slice_float_1_relaxed.model.cpp
@@ -0,0 +1,42 @@
+// Generated file (from: strided_slice_float_1_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {2});
+  OperandType type0(Type::TENSOR_FLOAT32, {4});
+  OperandType type1(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto begins = model->addOperand(&type1);
+  auto ends = model->addOperand(&type1);
+  auto strides = model->addOperand(&type1);
+  auto beginMask = model->addOperand(&type2);
+  auto endMask = model->addOperand(&type2);
+  auto shrinkAxisMask = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t begins_init[] = {1};
+  model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1);
+  static int32_t ends_init[] = {3};
+  model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1);
+  static int32_t strides_init[] = {1};
+  model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1);
+  static int32_t beginMask_init[] = {0};
+  model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1);
+  static int32_t endMask_init[] = {0};
+  model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1);
+  static int32_t shrinkAxisMask_init[] = {0};
+  model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/strided_slice_float_2_relaxed.model.cpp b/nn/runtime/test/generated/models/strided_slice_float_2_relaxed.model.cpp
new file mode 100644
index 000000000..94e14aafa
--- /dev/null
+++ b/nn/runtime/test/generated/models/strided_slice_float_2_relaxed.model.cpp
@@ -0,0 +1,42 @@
+// Generated file (from: strided_slice_float_2_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {2});
+  OperandType type0(Type::TENSOR_FLOAT32, {4});
+  OperandType type1(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto begins = model->addOperand(&type1);
+  auto ends = model->addOperand(&type1);
+  auto strides = model->addOperand(&type1);
+  auto beginMask = model->addOperand(&type2);
+  auto endMask = model->addOperand(&type2);
+  auto shrinkAxisMask = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t begins_init[] = {-3};
+  model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1);
+  static int32_t ends_init[] = {3};
+  model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1);
+  static int32_t strides_init[] = {1};
+  model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1);
+  static int32_t beginMask_init[] = {0};
+  model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1);
+  static int32_t endMask_init[] = {0};
+  model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1);
+  static int32_t shrinkAxisMask_init[] = {0};
+  model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/strided_slice_float_3_relaxed.model.cpp b/nn/runtime/test/generated/models/strided_slice_float_3_relaxed.model.cpp
new file mode 100644
index 000000000..54fe6b707
--- /dev/null
+++ b/nn/runtime/test/generated/models/strided_slice_float_3_relaxed.model.cpp
@@ -0,0 +1,42 @@
+// Generated file (from: strided_slice_float_3_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {3});
+  OperandType type0(Type::TENSOR_FLOAT32, {4});
+  OperandType type1(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto begins = model->addOperand(&type1);
+  auto ends = model->addOperand(&type1);
+  auto strides = model->addOperand(&type1);
+  auto beginMask = model->addOperand(&type2);
+  auto endMask = model->addOperand(&type2);
+  auto shrinkAxisMask = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t begins_init[] = {-5};
+  model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1);
+  static int32_t ends_init[] = {3};
+  model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1);
+  static int32_t strides_init[] = {1};
+  model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1);
+  static int32_t beginMask_init[] = {0};
+  model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1);
+  static int32_t endMask_init[] = {0};
+  model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1);
+  static int32_t shrinkAxisMask_init[] = {0};
+  model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/strided_slice_float_4_relaxed.model.cpp b/nn/runtime/test/generated/models/strided_slice_float_4_relaxed.model.cpp
new file mode 100644
index 000000000..ceaae5a40
--- /dev/null
+++ b/nn/runtime/test/generated/models/strided_slice_float_4_relaxed.model.cpp
@@ -0,0 +1,42 @@
+// Generated file (from: strided_slice_float_4_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {1});
+  OperandType type0(Type::TENSOR_FLOAT32, {4});
+  OperandType type1(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto begins = model->addOperand(&type1);
+  auto ends = model->addOperand(&type1);
+  auto strides = model->addOperand(&type1);
+  auto beginMask = model->addOperand(&type2);
+  auto endMask = model->addOperand(&type2);
+  auto shrinkAxisMask = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t begins_init[] = {1};
+  model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1);
+  static int32_t ends_init[] = {-2};
+  model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1);
+  static int32_t strides_init[] = {1};
+  model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1);
+  static int32_t beginMask_init[] = {0};
+  model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1);
+  static int32_t endMask_init[] = {0};
+  model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1);
+  static int32_t shrinkAxisMask_init[] = {0};
+  model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/strided_slice_float_5_relaxed.model.cpp b/nn/runtime/test/generated/models/strided_slice_float_5_relaxed.model.cpp
new file mode 100644
index 000000000..133ce3de7
--- /dev/null
+++ b/nn/runtime/test/generated/models/strided_slice_float_5_relaxed.model.cpp
@@ -0,0 +1,42 @@
+// Generated file (from: strided_slice_float_5_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {3});
+  OperandType type0(Type::TENSOR_FLOAT32, {4});
+  OperandType type1(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto begins = model->addOperand(&type1);
+  auto ends = model->addOperand(&type1);
+  auto strides = model->addOperand(&type1);
+  auto beginMask = model->addOperand(&type2);
+  auto endMask = model->addOperand(&type2);
+  auto shrinkAxisMask = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t begins_init[] = {1};
+  model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1);
+  static int32_t ends_init[] = {3};
+  model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1);
+  static int32_t strides_init[] = {1};
+  model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1);
+  static int32_t beginMask_init[] = {1};
+  model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1);
+  static int32_t endMask_init[] = {0};
+  model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1);
+  static int32_t shrinkAxisMask_init[] = {0};
+  model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/strided_slice_float_6_relaxed.model.cpp b/nn/runtime/test/generated/models/strided_slice_float_6_relaxed.model.cpp
new file mode 100644
index 000000000..52a95d526
--- /dev/null
+++ b/nn/runtime/test/generated/models/strided_slice_float_6_relaxed.model.cpp
@@ -0,0 +1,42 @@
+// Generated file (from: strided_slice_float_6_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {3});
+  OperandType type0(Type::TENSOR_FLOAT32, {4});
+  OperandType type1(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto begins = model->addOperand(&type1);
+  auto ends = model->addOperand(&type1);
+  auto strides = model->addOperand(&type1);
+  auto beginMask = model->addOperand(&type2);
+  auto endMask = model->addOperand(&type2);
+  auto shrinkAxisMask = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t begins_init[] = {1};
+  model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1);
+  static int32_t ends_init[] = {3};
+  model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1);
+  static int32_t strides_init[] = {1};
+  model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1);
+  static int32_t beginMask_init[] = {0};
+  model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1);
+  static int32_t endMask_init[] = {1};
+  model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1);
+  static int32_t shrinkAxisMask_init[] = {0};
+  model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/strided_slice_float_7_relaxed.model.cpp b/nn/runtime/test/generated/models/strided_slice_float_7_relaxed.model.cpp
new file mode 100644
index 000000000..f9e3187a6
--- /dev/null
+++ b/nn/runtime/test/generated/models/strided_slice_float_7_relaxed.model.cpp
@@ -0,0 +1,41 @@
+// Generated file (from: strided_slice_float_7_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {3});
+  OperandType type1(Type::TENSOR_INT32, {1});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto begins = model->addOperand(&type1);
+  auto ends = model->addOperand(&type1);
+  auto strides = model->addOperand(&type1);
+  auto beginMask = model->addOperand(&type2);
+  auto endMask = model->addOperand(&type2);
+  auto shrinkAxisMask = model->addOperand(&type2);
+  auto output = model->addOperand(&type0);
+  // Phase 2, operations
+  static int32_t begins_init[] = {-1};
+  model->setOperandValue(begins, begins_init, sizeof(int32_t) * 1);
+  static int32_t ends_init[] = {-4};
+  model->setOperandValue(ends, ends_init, sizeof(int32_t) * 1);
+  static int32_t strides_init[] = {-1};
+  model->setOperandValue(strides, strides_init, sizeof(int32_t) * 1);
+  static int32_t beginMask_init[] = {0};
+  model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1);
+  static int32_t endMask_init[] = {0};
+  model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1);
+  static int32_t shrinkAxisMask_init[] = {0};
+  model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/strided_slice_float_8_relaxed.model.cpp b/nn/runtime/test/generated/models/strided_slice_float_8_relaxed.model.cpp
new file mode 100644
index 000000000..9e15b708b
--- /dev/null
+++ b/nn/runtime/test/generated/models/strided_slice_float_8_relaxed.model.cpp
@@ -0,0 +1,42 @@
+// Generated file (from: strided_slice_float_8_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {1, 3});
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 3});
+  OperandType type1(Type::TENSOR_INT32, {2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto begins = model->addOperand(&type1);
+  auto ends = model->addOperand(&type1);
+  auto strides = model->addOperand(&type1);
+  auto beginMask = model->addOperand(&type2);
+  auto endMask = model->addOperand(&type2);
+  auto shrinkAxisMask = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t begins_init[] = {1, -1};
+  model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2);
+  static int32_t ends_init[] = {2, -4};
+  model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2);
+  static int32_t strides_init[] = {2, -1};
+  model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2);
+  static int32_t beginMask_init[] = {0};
+  model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1);
+  static int32_t endMask_init[] = {0};
+  model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1);
+  static int32_t shrinkAxisMask_init[] = {0};
+  model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/strided_slice_float_9_relaxed.model.cpp b/nn/runtime/test/generated/models/strided_slice_float_9_relaxed.model.cpp
new file mode 100644
index 000000000..f5a27bc6a
--- /dev/null
+++ b/nn/runtime/test/generated/models/strided_slice_float_9_relaxed.model.cpp
@@ -0,0 +1,42 @@
+// Generated file (from: strided_slice_float_9_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {2, 2});
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 3});
+  OperandType type1(Type::TENSOR_INT32, {2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto begins = model->addOperand(&type1);
+  auto ends = model->addOperand(&type1);
+  auto strides = model->addOperand(&type1);
+  auto beginMask = model->addOperand(&type2);
+  auto endMask = model->addOperand(&type2);
+  auto shrinkAxisMask = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t begins_init[] = {1, 0};
+  model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2);
+  static int32_t ends_init[] = {2, 2};
+  model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2);
+  static int32_t strides_init[] = {1, 1};
+  model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2);
+  static int32_t beginMask_init[] = {1};
+  model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1);
+  static int32_t endMask_init[] = {0};
+  model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1);
+  static int32_t shrinkAxisMask_init[] = {0};
+  model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/strided_slice_relaxed.model.cpp b/nn/runtime/test/generated/models/strided_slice_relaxed.model.cpp
new file mode 100644
index 000000000..1dcb838b4
--- /dev/null
+++ b/nn/runtime/test/generated/models/strided_slice_relaxed.model.cpp
@@ -0,0 +1,42 @@
+// Generated file (from: strided_slice_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type3(Type::TENSOR_FLOAT32, {1, 2});
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 3});
+  OperandType type1(Type::TENSOR_INT32, {2});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto begins = model->addOperand(&type1);
+  auto ends = model->addOperand(&type1);
+  auto strides = model->addOperand(&type1);
+  auto beginMask = model->addOperand(&type2);
+  auto endMask = model->addOperand(&type2);
+  auto shrinkAxisMask = model->addOperand(&type2);
+  auto output = model->addOperand(&type3);
+  // Phase 2, operations
+  static int32_t begins_init[] = {0, 0};
+  model->setOperandValue(begins, begins_init, sizeof(int32_t) * 2);
+  static int32_t ends_init[] = {2, 3};
+  model->setOperandValue(ends, ends_init, sizeof(int32_t) * 2);
+  static int32_t strides_init[] = {2, 2};
+  model->setOperandValue(strides, strides_init, sizeof(int32_t) * 2);
+  static int32_t beginMask_init[] = {0};
+  model->setOperandValue(beginMask, beginMask_init, sizeof(int32_t) * 1);
+  static int32_t endMask_init[] = {0};
+  model->setOperandValue(endMask, endMask_init, sizeof(int32_t) * 1);
+  static int32_t shrinkAxisMask_init[] = {0};
+  model->setOperandValue(shrinkAxisMask, shrinkAxisMask_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_STRIDED_SLICE, {input, begins, ends, strides, beginMask, endMask, shrinkAxisMask}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/sub_broadcast_float_relaxed.model.cpp b/nn/runtime/test/generated/models/sub_broadcast_float_relaxed.model.cpp
new file mode 100644
index 000000000..610b8e369
--- /dev/null
+++ b/nn/runtime/test/generated/models/sub_broadcast_float_relaxed.model.cpp
@@ -0,0 +1,27 @@
+// Generated file (from: sub_broadcast_float_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type2(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2});
+  OperandType type1(Type::TENSOR_FLOAT32, {2, 2});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type1);
+  auto act = model->addOperand(&type2);
+  auto op3 = model->addOperand(&type1);
+  // Phase 2, operations
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_SUB, {op1, op2, act}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1, op2},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/sub_relaxed.model.cpp b/nn/runtime/test/generated/models/sub_relaxed.model.cpp
new file mode 100644
index 000000000..440de653c
--- /dev/null
+++ b/nn/runtime/test/generated/models/sub_relaxed.model.cpp
@@ -0,0 +1,26 @@
+// Generated file (from: sub_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type1(Type::INT32, {});
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
+  // Phase 1, operands
+  auto op1 = model->addOperand(&type0);
+  auto op2 = model->addOperand(&type0);
+  auto act = model->addOperand(&type1);
+  auto op3 = model->addOperand(&type0);
+  // Phase 2, operations
+  static int32_t act_init[] = {0};
+  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
+  model->addOperation(ANEURALNETWORKS_SUB, {op1, op2, act}, {op3});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {op1, op2},
+    {op3});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/transpose_float_1_relaxed.model.cpp b/nn/runtime/test/generated/models/transpose_float_1_relaxed.model.cpp
new file mode 100644
index 000000000..c73b4bb0c
--- /dev/null
+++ b/nn/runtime/test/generated/models/transpose_float_1_relaxed.model.cpp
@@ -0,0 +1,26 @@
+// Generated file (from: transpose_float_1_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {2, 3, 4, 5});
+  OperandType type2(Type::TENSOR_FLOAT32, {4, 2, 3, 5});
+  OperandType type1(Type::TENSOR_INT32, {4});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto perms = model->addOperand(&type1);
+  auto output = model->addOperand(&type2);
+  // Phase 2, operations
+  static int32_t perms_init[] = {2, 0, 1, 3};
+  model->setOperandValue(perms, perms_init, sizeof(int32_t) * 4);
+  model->addOperation(ANEURALNETWORKS_TRANSPOSE, {input, perms}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/models/transpose_relaxed.model.cpp b/nn/runtime/test/generated/models/transpose_relaxed.model.cpp
new file mode 100644
index 000000000..af74ac488
--- /dev/null
+++ b/nn/runtime/test/generated/models/transpose_relaxed.model.cpp
@@ -0,0 +1,25 @@
+// Generated file (from: transpose_relaxed.mod.py). Do not edit
+void CreateModel(Model *model) {
+  OperandType type0(Type::TENSOR_FLOAT32, {1, 2, 2, 1});
+  OperandType type1(Type::TENSOR_INT32, {4});
+  // Phase 1, operands
+  auto input = model->addOperand(&type0);
+  auto perms = model->addOperand(&type1);
+  auto output = model->addOperand(&type0);
+  // Phase 2, operations
+  static int32_t perms_init[] = {0, 2, 1, 3};
+  model->setOperandValue(perms, perms_init, sizeof(int32_t) * 4);
+  model->addOperation(ANEURALNETWORKS_TRANSPOSE, {input, perms}, {output});
+  // Phase 3, inputs and outputs
+  model->identifyInputsAndOutputs(
+    {input},
+    {output});
+  // Phase 4: set relaxed execution
+  model->relaxComputationFloat32toFloat16(true);
+  assert(model->isValid());
+}
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/avg_pool_float_5_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/avg_pool_float_5_relaxed.model.cpp
new file mode 100644
index 000000000..fc6032777
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/avg_pool_float_5_relaxed.model.cpp
@@ -0,0 +1,82 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 4, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::AVERAGE_POOL_2D,
+            .inputs = {0, 2, 1, 1, 1, 1, 3},
+            .outputs = {4},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {4};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/batch_to_space_float_1_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/batch_to_space_float_1_relaxed.model.cpp
new file mode 100644
index 000000000..94852f138
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/batch_to_space_float_1_relaxed.model.cpp
@@ -0,0 +1,64 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 8},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4, 4, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::BATCH_TO_SPACE_ND,
+            .inputs = {0, 1},
+            .outputs = {2},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {2};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0, 2, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/batch_to_space_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/batch_to_space_relaxed.model.cpp
new file mode 100644
index 000000000..5ea7313d9
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/batch_to_space_relaxed.model.cpp
@@ -0,0 +1,64 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 1, 1, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 8},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::BATCH_TO_SPACE_ND,
+            .inputs = {0, 1},
+            .outputs = {2},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {2};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0, 2, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/conv_float_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/conv_float_2_relaxed.model.cpp
new file mode 100644
index 000000000..19a9ff550
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/conv_float_2_relaxed.model.cpp
@@ -0,0 +1,100 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 3, 4, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 3, 3, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 36},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 36, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 40, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 44, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 48, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 3, 4, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::CONV_2D,
+            .inputs = {0, 1, 2, 3, 5, 5, 4},
+            .outputs = {6},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {6};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 128, 63, 0, 0, 128, 64, 0, 0, 224, 64, 0, 0, 0, 64, 0, 0, 160, 64, 0, 0, 0, 65, 0, 0, 64, 64, 0, 0, 192, 64, 0, 0, 16, 65, 0, 0, 72, 195, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_2_relaxed.model.cpp
new file mode 100644
index 000000000..aae5378a2
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_2_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 3, 2, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 64},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 64, .length = 16},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 80, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 84, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 88, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 92, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {0, 1, 2, 3, 5, 5, 6, 4},
+            .outputs = {7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {7};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 128, 63, 0, 0, 0, 64, 0, 0, 64, 64, 0, 0, 128, 64, 0, 0, 16, 193, 0, 0, 32, 65, 0, 0, 48, 193, 0, 0, 64, 65, 0, 0, 160, 64, 0, 0, 192, 64, 0, 0, 224, 64, 0, 0, 0, 65, 0, 0, 80, 65, 0, 0, 96, 193, 0, 0, 112, 65, 0, 0, 128, 193, 0, 0, 128, 63, 0, 0, 0, 64, 0, 0, 64, 64, 0, 0, 128, 64, 2, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 2, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2_relaxed.model.cpp
new file mode 100644
index 000000000..81fc5524b
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 64},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 64, .length = 16},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 80, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 84, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 88, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 92, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {0, 1, 2, 3, 3, 3, 3, 5, 5, 6, 4},
+            .outputs = {7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {7};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 128, 62, 0, 0, 0, 0, 0, 0, 32, 65, 0, 0, 200, 66, 0, 0, 128, 62, 0, 0, 128, 63, 0, 0, 160, 65, 0, 0, 200, 66, 0, 0, 128, 62, 0, 0, 0, 0, 0, 0, 240, 65, 0, 0, 200, 66, 0, 0, 128, 62, 0, 0, 128, 63, 0, 0, 32, 66, 0, 0, 200, 66, 0, 124, 18, 73, 0, 230, 42, 73, 0, 80, 67, 73, 0, 186, 91, 73, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.model.cpp
new file mode 100644
index 000000000..e205e2dbb
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {0, 1, 2, 3, 3, 3, 3, 5, 5, 6, 4},
+            .outputs = {7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2};
+    const std::vector<uint32_t> outputIndexes = {7};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_relaxed.model.cpp
new file mode 100644
index 000000000..4af71d6c3
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 3, 3, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 64},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 64, .length = 16},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 80, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 84, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 88, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 92, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {0, 1, 2, 3, 3, 3, 3, 5, 5, 6, 4},
+            .outputs = {7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {7};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 128, 62, 0, 0, 0, 0, 205, 204, 76, 62, 0, 0, 0, 0, 0, 0, 128, 62, 0, 0, 0, 0, 0, 0, 0, 0, 154, 153, 153, 62, 0, 0, 128, 62, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 128, 62, 205, 204, 204, 61, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 128, 63, 0, 0, 0, 64, 0, 0, 64, 64, 0, 0, 128, 64, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 2, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_weights_as_inputs_relaxed.model.cpp
new file mode 100644
index 000000000..ddec86c3f
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/depthwise_conv2d_float_weights_as_inputs_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 3, 3, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 2,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 4},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::DEPTHWISE_CONV_2D,
+            .inputs = {0, 1, 2, 3, 3, 3, 3, 5, 5, 6, 4},
+            .outputs = {7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2};
+    const std::vector<uint32_t> outputIndexes = {7};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 2, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/dequantize_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/dequantize_relaxed.model.cpp
new file mode 100644
index 000000000..c08e16c41
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/dequantize_relaxed.model.cpp
@@ -0,0 +1,53 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_QUANT8_ASYMM,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 1.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::DEQUANTIZE,
+            .inputs = {0},
+            .outputs = {1},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {1};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/div_broadcast_float_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/div_broadcast_float_relaxed.model.cpp
new file mode 100644
index 000000000..9f6d6b7de
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/div_broadcast_float_relaxed.model.cpp
@@ -0,0 +1,73 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::DIV,
+            .inputs = {0, 1, 2},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/div_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/div_relaxed.model.cpp
new file mode 100644
index 000000000..c875b57cd
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/div_relaxed.model.cpp
@@ -0,0 +1,73 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::DIV,
+            .inputs = {0, 1, 2},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/fully_connected_float_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/fully_connected_float_2_relaxed.model.cpp
new file mode 100644
index 000000000..ef3d655b9
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/fully_connected_float_2_relaxed.model.cpp
@@ -0,0 +1,82 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 8},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {16, 8},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 512},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {16},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 512, .length = 64},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 16},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 576, .length = 4},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::FULLY_CONNECTED,
+            .inputs = {0, 1, 2, 4},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      166, 9, 187, 61, 142, 177, 211, 61, 242, 12, 162, 190, 210, 58, 170, 189, 103, 243, 24, 62, 243, 90, 73, 190, 191, 71, 253, 189, 73, 157, 128, 61, 102, 22, 129, 61, 36, 69, 68, 62, 195, 244, 125, 189, 158, 235, 123, 189, 244, 24, 141, 190, 213, 64, 115, 61, 142, 174, 242, 189, 49, 64, 162, 189, 205, 200, 224, 61, 21, 26, 8, 60, 80, 82, 128, 189, 74, 179, 121, 189, 54, 232, 75, 189, 126, 143, 218, 189, 37, 147, 163, 190, 116, 70, 212, 189, 202, 108, 136, 62, 125, 3, 83, 61, 78, 210, 252, 189, 0, 26, 165, 62, 119, 72, 49, 61, 233, 243, 49, 190, 61, 243, 66, 190, 137, 236, 3, 59, 189, 200, 196, 61, 5, 78, 6, 62, 165, 75, 255, 60, 76, 27, 206, 61, 128, 215, 159, 190, 245, 186, 165, 189, 208, 127, 207, 189, 82, 211, 238, 189, 215, 166, 17, 62, 226, 59, 177, 61, 99, 126, 14, 190, 80, 115, 50, 62, 111, 213, 149, 189, 202, 252, 163, 61, 75, 63, 225, 59, 29, 227, 106, 62, 64, 166, 213, 189, 133, 66, 52, 190, 213, 151, 85, 190, 247, 143, 133, 186, 183, 235, 37, 190, 14, 135, 165, 61, 215, 248, 204, 188, 124, 126, 152, 61, 34, 84, 129, 190, 203, 161, 37, 190, 58, 173, 11, 190, 71, 30, 8, 60, 244, 26, 187, 59, 57, 214, 197, 61, 199, 101, 148, 62, 77, 17, 96, 62, 55, 251, 155, 190, 110, 82, 145, 189, 39, 162, 95, 61, 202, 164, 22, 62, 96, 115, 14, 190, 30, 23, 149, 189, 74, 65, 39, 190, 71, 228, 43, 190, 48, 218, 3, 190, 13, 142, 18, 189, 15, 39, 240, 61, 200, 182, 140, 60, 216, 211, 134, 62, 199, 217, 52, 190, 211, 162, 134, 62, 171, 205, 191, 189, 128, 182, 173, 190, 72, 136, 170, 62, 183, 42, 57, 62, 20, 62, 147, 62, 130, 226, 135, 61, 158, 178, 74, 190, 61, 100, 234, 189, 41, 179, 113, 190, 150, 8, 212, 61, 97, 109, 12, 189, 140, 19, 191, 61, 132, 217, 20, 190, 39, 48, 93, 61, 182, 74, 128, 62, 59, 199, 32, 62, 108, 236, 18, 190, 2, 102, 14, 190, 14, 47, 72, 189, 83, 91, 138, 61, 250, 95, 14, 62, 57, 241, 165, 62, 112, 125, 104, 62, 213, 204, 26, 61, 57, 42, 103, 190, 249, 106, 119, 190, 38, 54, 183, 62, 50, 5, 11, 62, 44, 16, 157, 190, 109, 1, 1, 190, 117, 62, 188, 61, 23, 126, 136, 62, 173, 221, 246, 60, 123, 193, 135, 62, 171, 6, 17, 62, 179, 210, 164, 60, 51, 167, 171, 61, 55, 23, 255, 189, 208, 13, 205, 189, 95, 66, 69, 189, 39, 133, 57, 62, 63, 200, 154, 62, 178, 71, 40, 189, 149, 216, 21, 62, 245, 242, 123, 189, 1, 48, 110, 190, 179, 9, 144, 62, 214, 229, 20, 62, 248, 56, 99, 190, 193, 114, 36, 190, 95, 181, 82, 62, 108, 95, 160, 189, 19, 182, 159, 189, 239, 226, 253, 58, 213, 236, 129, 60, 21, 198, 22, 61, 225, 70, 74, 60, 245, 189, 134, 58, 167, 231, 29, 61, 46, 115, 154, 61, 38, 109, 170, 60, 222, 144, 70, 61, 140, 45, 4, 189, 142, 231, 51, 62, 143, 111, 175, 189, 1, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/fully_connected_float_4d_simple.model.cpp b/nn/runtime/test/generated/vts_models/fully_connected_float_4d_simple.model.cpp
index fcf290060..5ad81c96c 100644
--- a/nn/runtime/test/generated/vts_models/fully_connected_float_4d_simple.model.cpp
+++ b/nn/runtime/test/generated/vts_models/fully_connected_float_4d_simple.model.cpp
@@ -71,7 +71,6 @@ Model createTestModel() {
         .outputIndexes = outputIndexes,
         .operandValues = operandValues,
         .pools = pools,
-        .relaxComputationFloat32toFloat16 = true,
     };
 }
 
diff --git a/nn/runtime/test/generated/vts_models/fully_connected_float_4d_simple_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/fully_connected_float_4d_simple_relaxed.model.cpp
new file mode 100644
index 000000000..fcf290060
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/fully_connected_float_4d_simple_relaxed.model.cpp
@@ -0,0 +1,82 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 1, 5, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3, 10},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 120},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 120, .length = 12},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 132, .length = 4},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::FULLY_CONNECTED,
+            .inputs = {0, 1, 2, 4},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 128, 63, 0, 0, 0, 64, 0, 0, 64, 64, 0, 0, 128, 64, 0, 0, 160, 64, 0, 0, 192, 64, 0, 0, 224, 64, 0, 0, 0, 65, 0, 0, 16, 65, 0, 0, 32, 65, 0, 0, 128, 63, 0, 0, 0, 64, 0, 0, 64, 64, 0, 0, 128, 64, 0, 0, 160, 64, 0, 0, 192, 64, 0, 0, 224, 64, 0, 0, 0, 65, 0, 0, 16, 65, 0, 0, 32, 65, 0, 0, 128, 63, 0, 0, 0, 64, 0, 0, 64, 64, 0, 0, 128, 64, 0, 0, 160, 64, 0, 0, 192, 64, 0, 0, 224, 64, 0, 0, 0, 65, 0, 0, 16, 65, 0, 0, 32, 65, 0, 0, 128, 63, 0, 0, 0, 64, 0, 0, 64, 64, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/fully_connected_float_large_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/fully_connected_float_large_relaxed.model.cpp
new file mode 100644
index 000000000..9a3314046
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/fully_connected_float_large_relaxed.model.cpp
@@ -0,0 +1,82 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 20},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 20, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 24, .length = 4},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::FULLY_CONNECTED,
+            .inputs = {0, 1, 2, 4},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 64, 0, 0, 64, 64, 0, 0, 128, 64, 0, 0, 160, 64, 0, 0, 192, 64, 0, 186, 91, 73, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/fully_connected_float_large_weights_as_inputs_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/fully_connected_float_large_weights_as_inputs_relaxed.model.cpp
new file mode 100644
index 000000000..63801367d
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/fully_connected_float_large_weights_as_inputs_relaxed.model.cpp
@@ -0,0 +1,82 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::FULLY_CONNECTED,
+            .inputs = {0, 1, 2, 4},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1, 2};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/l2_normalization_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/l2_normalization_2_relaxed.model.cpp
new file mode 100644
index 000000000..8be70f221
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/l2_normalization_2_relaxed.model.cpp
@@ -0,0 +1,53 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 6},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 6},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::L2_NORMALIZATION,
+            .inputs = {0},
+            .outputs = {1},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {1};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/l2_pool_float_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/l2_pool_float_2_relaxed.model.cpp
new file mode 100644
index 000000000..afa7aa3aa
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/l2_pool_float_2_relaxed.model.cpp
@@ -0,0 +1,82 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 4, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::L2_POOL_2D,
+            .inputs = {0, 2, 1, 1, 1, 1, 3},
+            .outputs = {4},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {4};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/l2_pool_float_large_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/l2_pool_float_large_relaxed.model.cpp
new file mode 100644
index 000000000..453d1b9d7
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/l2_pool_float_large_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 20, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 1, 3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::L2_POOL_2D,
+            .inputs = {0, 5, 5, 5, 5, 3, 4, 1, 2, 6},
+            .outputs = {7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {7};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/max_pool_float_4_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/max_pool_float_4_relaxed.model.cpp
new file mode 100644
index 000000000..33cac4917
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/max_pool_float_4_relaxed.model.cpp
@@ -0,0 +1,82 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 4, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 4,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 1, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::MAX_POOL_2D,
+            .inputs = {0, 2, 1, 1, 1, 1, 3},
+            .outputs = {4},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {4};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/mean_float_1_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/mean_float_1_relaxed.model.cpp
new file mode 100644
index 000000000..436a063f9
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/mean_float_1_relaxed.model.cpp
@@ -0,0 +1,73 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 3, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 16},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::MEAN,
+            .inputs = {0, 1, 2},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      1, 0, 0, 0, 0, 0, 0, 0, 253, 255, 255, 255, 253, 255, 255, 255, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/mean_float_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/mean_float_2_relaxed.model.cpp
new file mode 100644
index 000000000..bae3fd2ff
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/mean_float_2_relaxed.model.cpp
@@ -0,0 +1,73 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 3, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 8},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 3, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::MEAN,
+            .inputs = {0, 1, 2},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/mean_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/mean_relaxed.model.cpp
new file mode 100644
index 000000000..8896acf05
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/mean_relaxed.model.cpp
@@ -0,0 +1,73 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::MEAN,
+            .inputs = {0, 1, 2},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/pad_float_1_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/pad_float_1_relaxed.model.cpp
new file mode 100644
index 000000000..6f04ef501
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/pad_float_1_relaxed.model.cpp
@@ -0,0 +1,64 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 3, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 32},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4, 7, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::PAD,
+            .inputs = {0, 1},
+            .outputs = {2},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {2};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/pad_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/pad_relaxed.model.cpp
new file mode 100644
index 000000000..3aa8599a0
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/pad_relaxed.model.cpp
@@ -0,0 +1,64 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 32},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4, 4, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::PAD,
+            .inputs = {0, 1},
+            .outputs = {2},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {2};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/relu_float_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/relu_float_2_relaxed.model.cpp
new file mode 100644
index 000000000..b4ba428c9
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/relu_float_2_relaxed.model.cpp
@@ -0,0 +1,53 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 64, 40, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 64, 40, 2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::RELU,
+            .inputs = {0},
+            .outputs = {1},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {1};
+    std::vector<uint8_t> operandValues = {};
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/resize_bilinear_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/resize_bilinear_2_relaxed.model.cpp
new file mode 100644
index 000000000..6c4c7f32b
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/resize_bilinear_2_relaxed.model.cpp
@@ -0,0 +1,73 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 3, 3, 2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::RESIZE_BILINEAR,
+            .inputs = {0, 2, 3},
+            .outputs = {1},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {1};
+    std::vector<uint8_t> operandValues = {
+      3, 0, 0, 0, 3, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/space_to_batch_float_1_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/space_to_batch_float_1_relaxed.model.cpp
new file mode 100644
index 000000000..39d8e5c39
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/space_to_batch_float_1_relaxed.model.cpp
@@ -0,0 +1,73 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4, 4, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 8},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 16},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::SPACE_TO_BATCH_ND,
+            .inputs = {0, 1, 2},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/space_to_batch_float_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/space_to_batch_float_2_relaxed.model.cpp
new file mode 100644
index 000000000..3871335cd
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/space_to_batch_float_2_relaxed.model.cpp
@@ -0,0 +1,73 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 5, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 8},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 16},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {6, 2, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::SPACE_TO_BATCH_ND,
+            .inputs = {0, 1, 2},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      3, 0, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/space_to_batch_float_3_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/space_to_batch_float_3_relaxed.model.cpp
new file mode 100644
index 000000000..819de5262
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/space_to_batch_float_3_relaxed.model.cpp
@@ -0,0 +1,73 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 4, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 8},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 16},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {6, 2, 4, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::SPACE_TO_BATCH_ND,
+            .inputs = {0, 1, 2},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      3, 0, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 2, 0, 0, 0, 4, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/space_to_batch_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/space_to_batch_relaxed.model.cpp
new file mode 100644
index 000000000..51bf2a9d3
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/space_to_batch_relaxed.model.cpp
@@ -0,0 +1,73 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 8},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 16},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 1, 1, 2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::SPACE_TO_BATCH_ND,
+            .inputs = {0, 1, 2},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/squeeze_float_1_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/squeeze_float_1_relaxed.model.cpp
new file mode 100644
index 000000000..8ebd2805d
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/squeeze_float_1_relaxed.model.cpp
@@ -0,0 +1,64 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 24, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 24},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::SQUEEZE,
+            .inputs = {0, 1},
+            .outputs = {2},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {2};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/squeeze_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/squeeze_relaxed.model.cpp
new file mode 100644
index 000000000..3f7769a59
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/squeeze_relaxed.model.cpp
@@ -0,0 +1,64 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 1, 1, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 8},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::SQUEEZE,
+            .inputs = {0, 1},
+            .outputs = {2},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {2};
+    std::vector<uint8_t> operandValues = {
+      1, 0, 0, 0, 2, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_10_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_10_relaxed.model.cpp
new file mode 100644
index 000000000..28789fe46
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_10_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 8},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 8},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 8},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 24, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 28, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 32, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::STRIDED_SLICE,
+            .inputs = {0, 1, 2, 3, 4, 5, 6},
+            .outputs = {7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {7};
+    std::vector<uint8_t> operandValues = {
+      1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_11_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_11_relaxed.model.cpp
new file mode 100644
index 000000000..33e24b6ae
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_11_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 8},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 8},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 8},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 24, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 28, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 32, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::STRIDED_SLICE,
+            .inputs = {0, 1, 2, 3, 4, 5, 6},
+            .outputs = {7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {7};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_1_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_1_relaxed.model.cpp
new file mode 100644
index 000000000..a271a1098
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_1_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 20, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::STRIDED_SLICE,
+            .inputs = {0, 1, 2, 3, 4, 5, 6},
+            .outputs = {7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {7};
+    std::vector<uint8_t> operandValues = {
+      1, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_2_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_2_relaxed.model.cpp
new file mode 100644
index 000000000..490ead682
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_2_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 20, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::STRIDED_SLICE,
+            .inputs = {0, 1, 2, 3, 4, 5, 6},
+            .outputs = {7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {7};
+    std::vector<uint8_t> operandValues = {
+      253, 255, 255, 255, 3, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_3_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_3_relaxed.model.cpp
new file mode 100644
index 000000000..a89cb2a6e
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_3_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 20, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::STRIDED_SLICE,
+            .inputs = {0, 1, 2, 3, 4, 5, 6},
+            .outputs = {7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {7};
+    std::vector<uint8_t> operandValues = {
+      251, 255, 255, 255, 3, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_4_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_4_relaxed.model.cpp
new file mode 100644
index 000000000..7a669c854
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_4_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 20, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::STRIDED_SLICE,
+            .inputs = {0, 1, 2, 3, 4, 5, 6},
+            .outputs = {7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {7};
+    std::vector<uint8_t> operandValues = {
+      1, 0, 0, 0, 254, 255, 255, 255, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_5_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_5_relaxed.model.cpp
new file mode 100644
index 000000000..54eb217d9
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_5_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 20, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::STRIDED_SLICE,
+            .inputs = {0, 1, 2, 3, 4, 5, 6},
+            .outputs = {7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {7};
+    std::vector<uint8_t> operandValues = {
+      1, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_6_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_6_relaxed.model.cpp
new file mode 100644
index 000000000..d35d04e41
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_6_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 20, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::STRIDED_SLICE,
+            .inputs = {0, 1, 2, 3, 4, 5, 6},
+            .outputs = {7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {7};
+    std::vector<uint8_t> operandValues = {
+      1, 0, 0, 0, 3, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_7_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_7_relaxed.model.cpp
new file mode 100644
index 000000000..6103b3bca
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_7_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 4, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 12, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 20, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::STRIDED_SLICE,
+            .inputs = {0, 1, 2, 3, 4, 5, 6},
+            .outputs = {7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {7};
+    std::vector<uint8_t> operandValues = {
+      255, 255, 255, 255, 252, 255, 255, 255, 255, 255, 255, 255, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_8_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_8_relaxed.model.cpp
new file mode 100644
index 000000000..6a1f53287
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_8_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 8},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 8},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 8},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 24, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 28, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 32, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 3},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::STRIDED_SLICE,
+            .inputs = {0, 1, 2, 3, 4, 5, 6},
+            .outputs = {7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {7};
+    std::vector<uint8_t> operandValues = {
+      1, 0, 0, 0, 255, 255, 255, 255, 2, 0, 0, 0, 252, 255, 255, 255, 2, 0, 0, 0, 255, 255, 255, 255, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_float_9_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_float_9_relaxed.model.cpp
new file mode 100644
index 000000000..1f52adae2
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/strided_slice_float_9_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 8},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 8},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 8},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 24, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 28, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 32, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::STRIDED_SLICE,
+            .inputs = {0, 1, 2, 3, 4, 5, 6},
+            .outputs = {7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {7};
+    std::vector<uint8_t> operandValues = {
+      1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/strided_slice_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/strided_slice_relaxed.model.cpp
new file mode 100644
index 000000000..c0ddf4499
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/strided_slice_relaxed.model.cpp
@@ -0,0 +1,109 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 3},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 8},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 8, .length = 8},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 16, .length = 8},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 24, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 28, .length = 4},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 32, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::STRIDED_SLICE,
+            .inputs = {0, 1, 2, 3, 4, 5, 6},
+            .outputs = {7},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {7};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 3, 0, 0, 0, 2, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/sub_broadcast_float_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/sub_broadcast_float_relaxed.model.cpp
new file mode 100644
index 000000000..3a2c09b3b
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/sub_broadcast_float_relaxed.model.cpp
@@ -0,0 +1,73 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 2},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 2},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::SUB,
+            .inputs = {0, 1, 2},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/sub_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/sub_relaxed.model.cpp
new file mode 100644
index 000000000..03fb88f73
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/sub_relaxed.model.cpp
@@ -0,0 +1,73 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 4},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::SUB,
+            .inputs = {0, 1, 2},
+            .outputs = {3},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0, 1};
+    const std::vector<uint32_t> outputIndexes = {3};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/transpose_float_1_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/transpose_float_1_relaxed.model.cpp
new file mode 100644
index 000000000..40b09965c
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/transpose_float_1_relaxed.model.cpp
@@ -0,0 +1,64 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {2, 3, 4, 5},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 16},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {4, 2, 3, 5},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::TRANSPOSE,
+            .inputs = {0, 1},
+            .outputs = {2},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {2};
+    std::vector<uint8_t> operandValues = {
+      2, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}
diff --git a/nn/runtime/test/generated/vts_models/transpose_relaxed.model.cpp b/nn/runtime/test/generated/vts_models/transpose_relaxed.model.cpp
new file mode 100644
index 000000000..11d963925
--- /dev/null
+++ b/nn/runtime/test/generated/vts_models/transpose_relaxed.model.cpp
@@ -0,0 +1,64 @@
+// Generated code. Do not edit
+// Create the model
+Model createTestModel() {
+    const std::vector<Operand> operands = {
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_INPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        },
+        {
+            .type = OperandType::TENSOR_INT32,
+            .dimensions = {4},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::CONSTANT_COPY,
+            .location = {.poolIndex = 0, .offset = 0, .length = 16},
+        },
+        {
+            .type = OperandType::TENSOR_FLOAT32,
+            .dimensions = {1, 2, 2, 1},
+            .numberOfConsumers = 0,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = OperandLifeTime::MODEL_OUTPUT,
+            .location = {.poolIndex = 0, .offset = 0, .length = 0},
+        }
+    };
+
+    const std::vector<Operation> operations = {
+        {
+            .type = OperationType::TRANSPOSE,
+            .inputs = {0, 1},
+            .outputs = {2},
+        }
+    };
+
+    const std::vector<uint32_t> inputIndexes = {0};
+    const std::vector<uint32_t> outputIndexes = {2};
+    std::vector<uint8_t> operandValues = {
+      0, 0, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 0
+    };
+    const std::vector<hidl_memory> pools = {};
+
+    return {
+        .operands = operands,
+        .operations = operations,
+        .inputIndexes = inputIndexes,
+        .outputIndexes = outputIndexes,
+        .operandValues = operandValues,
+        .pools = pools,
+        .relaxComputationFloat32toFloat16 = true,
+    };
+}
+
+
+bool is_ignored(int i) {
+  static std::set<int> ignore = {};
+  return ignore.find(i) != ignore.end();
+}