1 files changed, 109 insertions, 0 deletions
diff --git a/nn/runtime/test/specs/V1_3/logistic_quant8_signed.mod.py b/nn/runtime/test/specs/V1_3/logistic_quant8_signed.mod.py
new file mode 100644
index 000000000..17dd369d5
--- /dev/null
+++ b/nn/runtime/test/specs/V1_3/logistic_quant8_signed.mod.py
@@ -0,0 +1,109 @@
+#
+# Copyright (C) 2019 The Android Open Source Project
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+import math
+
+model = Model()
+i1 = Input("op1", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 2, 2, 1}, 0.5f, -128")
+i3 = Output("op3", "TENSOR_QUANT8_ASYMM_SIGNED",
+            "{1, 2, 2, 1}, 0.00390625f, -128")
+model = model.Operation("LOGISTIC", i1).To(i3)
+
+# Example 1. Input in operand 0,
+input0 = {
+    i1:  # input 0
+        [-128, -127, -126, -1]
+}
+
+output0 = {
+    i3:  # output 0
+        [0, 31, 59, 127]
+}
+
+# Instantiate an example
+Example((input0, output0))
+
+#######################################################
+
+model = Model()
+
+d0 = 1  #2
+d1 = 16  #256
+d2 = 16  #256
+d3 = 1  #2
+
+i0 = Input("input", "TENSOR_QUANT8_ASYMM_SIGNED",
+           "{%d, %d, %d, %d}, .5f, -128" % (d0, d1, d2, d3))
+output = Output("output", "TENSOR_QUANT8_ASYMM_SIGNED",
+                "{%d, %d, %d, %d}, 0.00390625f, -128" % (d0, d1, d2, d3))
+model = model.Operation("LOGISTIC", i0).To(output)
+
+# Example 1. Input in operand 0,
+rng = d0 * d1 * d2 * d3
+input_values = (lambda r=rng: [x % 256 for x in range(r)])()
+output_values = [
+    255 if 1. / (1. + math.exp(-x * .5)) * 256 > 255 else int(
+        round(1. / (1. + math.exp(-x * .5)) * 256)) for x in input_values
+]
+
+input0 = {i0: [val - 128 for val in input_values]}
+output0 = {output: [val - 128 for val in output_values]}
+
+# Instantiate an example
+Example((input0, output0))
+
+#######################################################
+
+# Zero-sized input test
+# Use BOX_WITH_NMS_LIMIT op to generate a zero-sized internal tensor for box cooridnates.
+p1 = Parameter("scores", "TENSOR_FLOAT32", "{1, 2}", [0.90, 0.10])  # scores
+p2 = Parameter("roi", "TENSOR_FLOAT32", "{1, 8}",
+               [1, 1, 10, 10, 0, 0, 10, 10])  # roi
+o1 = Output("scoresOut", "TENSOR_FLOAT32", "{0}")  # scores out
+o2 = Output("classesOut", "TENSOR_INT32", "{0}")  # classes out
+tmp1 = Internal("roiOut", "TENSOR_FLOAT32", "{0, 4}")  # roi out
+tmp2 = Internal("batchSplitOut", "TENSOR_INT32", "{0}")  # batch split out
+model = Model("zero_sized").Operation("BOX_WITH_NMS_LIMIT", p1, p2, [0], 0.3,
+                                      -1, 0, 0.4, 1.0,
+                                      0.3).To(o1, tmp1, o2, tmp2)
+
+# Use ROI_ALIGN op to convert into zero-sized feature map.
+layout = BoolScalar("layout", False)  # NHWC
+i1 = Input("in", "TENSOR_FLOAT32", "{1, 1, 1, 1}")
+zero_sized = Internal("featureMap", "TENSOR_FLOAT32", "{0, 2, 2, 1}")
+model = model.Operation("ROI_ALIGN", i1, tmp1, tmp2, 2, 2, 2.0, 2.0, 4, 4,
+                        layout).To(zero_sized)
+
+# LOGISTIC op with numBatches = 0.
+o3 = Output("out", "TENSOR_FLOAT32", "{0, 2, 2, 1}")  # out
+model = model.Operation("LOGISTIC", zero_sized).To(o3)
+
+quant8_signed = DataTypeConverter().Identify({
+    p1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0),
+    p2: ("TENSOR_QUANT16_ASYMM", 0.125, 0),
+    o1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0),
+    tmp1: ("TENSOR_QUANT16_ASYMM", 0.125, 0),
+    i1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0),
+    zero_sized: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.1, 0),
+    o3: ("TENSOR_QUANT8_ASYMM_SIGNED", 1.0 / 256, -128)
+})
+
+Example({
+    i1: [1],
+    o1: [],
+    o2: [],
+    o3: [],
+}).AddVariations(
+    quant8_signed, includeDefault=False)