1 files changed, 136 insertions, 0 deletions
diff --git a/nn/runtime/test/specs/V1_3/softmax_quant8_signed.mod.py b/nn/runtime/test/specs/V1_3/softmax_quant8_signed.mod.py
new file mode 100644
index 000000000..18e83a40b
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+++ b/nn/runtime/test/specs/V1_3/softmax_quant8_signed.mod.py
@@ -0,0 +1,136 @@
+#
+# 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.
+#
+model = Model()
+
+i1 = Input("input", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 4}, 0.5f, -128") # batch = 1, depth = 1
+beta = Float32Scalar("beta", 0.00001) # close to 0
+output = Output("output", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 4}, 0.00390625f, -128")
+
+# model 1
+model = model.Operation("SOFTMAX", i1, beta).To(output)
+
+# Example 1. Input in operand 0,
+input0 = {i1: [-127, -126, -118, -108]}
+
+output0 = {output: [-64, -64, -64, -64]}
+
+# Instantiate an example
+Example((input0, output0))
+
+#######################################################
+
+model = Model()
+
+i1 = Input("input", "TENSOR_QUANT8_ASYMM_SIGNED", "{2, 5}, 0.5f, -128") # batch = 2, depth = 5
+beta = Float32Scalar("beta", 1.)
+output = Output("output", "TENSOR_QUANT8_ASYMM_SIGNED", "{2, 5}, 0.00390625f, -128")
+
+# model 1
+model = model.Operation("SOFTMAX", i1, beta).To(output)
+
+# Example 1. Input in operand 0,
+input0 = {i1:
+          [-127, -126, -125, -124, -123,
+           127, 126, 125, 124, 123]}
+
+output0 = {output:
+           [-113, -104, -88, -61, -18,
+            -18, -61, -88, -104, -113]}
+
+# Instantiate an example
+Example((input0, output0))
+
+#######################################################
+
+i = Input("op1", "TENSOR_FLOAT32", "{2, 2, 2, 5}") # input 0
+o = Output("op2", "TENSOR_FLOAT32", "{2, 2, 2, 5}") # output 0
+axis = Int32Scalar("axis", -1) # last axis
+
+# Additional data type
+quant8_signed = DataTypeConverter().Identify({
+    i: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, 0),
+    o: ("TENSOR_QUANT8_ASYMM_SIGNED", 1./256, -128)
+})
+
+example1 = {
+    i: [17., 16., 15., 14.,  1.,
+        -1., -2., -3., -4., -17.] * 4,
+    o: [0.643914213228014,
+        0.236882800924671,
+        0.087144312427294,
+        0.032058600957022,
+        7.246299848982885e-08] * 8
+}
+example2 = {
+    i: [1., 2., 3., 4., 5., -1., -2., -3., -4., -5.] * 4,
+    o: [0.2] * 40
+}
+
+# All dimensions other than 2 or 4, without axis parameter
+# beta = 1.0
+Model().Operation("SOFTMAX", i, 1.0).To(o)
+Example(example1).AddVariations(quant8_signed, includeDefault=False).AddDims([1, 3], i, o)
+# beta = 0.000001
+Model().Operation("SOFTMAX", i, 0.000001).To(o)
+Example(example2).AddVariations(quant8_signed, includeDefault=False).AddDims([1, 3], i, o)
+
+#######################################################
+# All dimensions, with all possible axis parameter
+# beta = 1.0
+Model("axis").Operation("SOFTMAX", i, 1.0, axis).To(o)
+Example(example1).AddVariations(quant8_signed, includeDefault=False).AddAllDimsAndAxis(i, o, axis)
+# beta = 0.000001
+Model("axis").Operation("SOFTMAX", i, 0.000001, axis).To(o)
+Example(example2).AddVariations(quant8_signed, includeDefault=False).AddAllDimsAndAxis(i, o, axis)
+
+#######################################################
+# zero-sized input
+
+# 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)
+
+# SOFTMAX op with numBatches = 0.
+o3 = Output("out", "TENSOR_FLOAT32", "{0, 2, 2, 1}") # out
+model = model.Operation("SOFTMAX", zero_sized, 1.0).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./256, -128)
+})
+
+Example({
+    i1: [1],
+    o1: [],
+    o2: [],
+    o3: [],
+}).AddVariations(quant8_signed, includeDefault=False)