810 lines
50 KiB
C++
810 lines
50 KiB
C++
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/*
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* Copyright (C) 2019 The Android Open Source Project
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "fuzzing/operation_signatures/OperationSignatureUtils.h"
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using namespace std::placeholders;
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namespace android {
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namespace nn {
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namespace fuzzing_test {
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static void conv2DExplicitConstructor(TestOperandType, uint32_t rank, TestHalVersion ver,
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RandomOperation* op) {
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NN_FUZZER_CHECK(rank == 4);
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// Parameters
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int32_t paddingLeft = op->inputs[3]->value<int32_t>();
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int32_t paddingRight = op->inputs[4]->value<int32_t>();
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int32_t paddingTop = op->inputs[5]->value<int32_t>();
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int32_t paddingBottom = op->inputs[6]->value<int32_t>();
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int32_t strideWidth = op->inputs[7]->value<int32_t>();
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int32_t strideHeight = op->inputs[8]->value<int32_t>();
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bool useNchw = false;
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int32_t dilationWidth = 1, dilationHeight = 1;
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if (op->inputs.size() > 10) {
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useNchw = op->inputs[10]->value<bool8>();
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if (op->inputs.size() > 11) {
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dilationWidth = op->inputs[11]->value<int32_t>();
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dilationHeight = op->inputs[12]->value<int32_t>();
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}
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}
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int heightIndex = useNchw ? 2 : 1;
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int widthIndex = useNchw ? 3 : 2;
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int channelIndex = useNchw ? 1 : 3;
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// Input, [batch, height_in, width_in, channel_in]
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op->inputs[0]->dimensions = {RandomVariableType::FREE, RandomVariableType::FREE,
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RandomVariableType::FREE, RandomVariableType::FREE};
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// Filter, [channel_out, height_flt, width_flt, channel_in]
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op->inputs[1]->dimensions = {RandomVariableType::FREE, RandomVariableType::FREE,
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RandomVariableType::FREE, op->inputs[0]->dimensions[channelIndex]};
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// Bias, [channel_out]
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op->inputs[2]->dimensions = {op->inputs[1]->dimensions[0]};
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// Output, [batch, height_out, width_out, channel_out]
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op->outputs[0]->dimensions.resize(4);
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// batch and channel
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op->outputs[0]->dimensions[0] = op->inputs[0]->dimensions[0];
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op->outputs[0]->dimensions[channelIndex] = op->inputs[1]->dimensions[0];
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// height
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explicitPadding(op->inputs[0]->dimensions[heightIndex], op->inputs[1]->dimensions[1],
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strideHeight, dilationHeight, paddingTop, paddingBottom,
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&op->outputs[0]->dimensions[heightIndex]);
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// width
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explicitPadding(op->inputs[0]->dimensions[widthIndex], op->inputs[1]->dimensions[2],
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strideWidth, dilationWidth, paddingLeft, paddingRight,
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&op->outputs[0]->dimensions[widthIndex]);
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setConvFCScale(/*applyOutputScaleBound=*/ver == TestHalVersion::V1_0, op);
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}
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static void conv2DImplicitConstructor(TestOperandType, uint32_t rank, TestHalVersion ver,
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RandomOperation* op) {
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NN_FUZZER_CHECK(rank == 4);
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// Parameters
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int32_t paddingScheme = op->inputs[3]->value<int32_t>();
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int32_t strideWidth = op->inputs[4]->value<int32_t>();
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int32_t strideHeight = op->inputs[5]->value<int32_t>();
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bool useNchw = false;
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int32_t dilationWidth = 1, dilationHeight = 1;
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if (op->inputs.size() > 7) {
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useNchw = op->inputs[7]->value<bool8>();
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if (op->inputs.size() > 8) {
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dilationWidth = op->inputs[8]->value<int32_t>();
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dilationHeight = op->inputs[9]->value<int32_t>();
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}
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}
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int heightIndex = useNchw ? 2 : 1;
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int widthIndex = useNchw ? 3 : 2;
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int channelIndex = useNchw ? 1 : 3;
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// Input, [batch, height_in, width_in, channel_in]
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op->inputs[0]->dimensions = {RandomVariableType::FREE, RandomVariableType::FREE,
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RandomVariableType::FREE, RandomVariableType::FREE};
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// Filter, [channel_out, height_flt, width_flt, channel_in]
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op->inputs[1]->dimensions = {RandomVariableType::FREE, RandomVariableType::FREE,
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RandomVariableType::FREE, op->inputs[0]->dimensions[channelIndex]};
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// Bias, [channel_out]
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op->inputs[2]->dimensions = {op->inputs[1]->dimensions[0]};
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// Output, [batch, height_out, width_out, channel_out]
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op->outputs[0]->dimensions.resize(4);
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// batch and channel
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op->outputs[0]->dimensions[0] = op->inputs[0]->dimensions[0];
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op->outputs[0]->dimensions[channelIndex] = op->inputs[1]->dimensions[0];
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// height and width
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implicitPadding(op->inputs[0]->dimensions[heightIndex], op->inputs[1]->dimensions[1],
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strideHeight, dilationHeight, paddingScheme,
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&op->outputs[0]->dimensions[heightIndex]);
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implicitPadding(op->inputs[0]->dimensions[widthIndex], op->inputs[1]->dimensions[2],
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strideWidth, dilationWidth, paddingScheme,
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&op->outputs[0]->dimensions[widthIndex]);
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setConvFCScale(/*applyOutputScaleBound=*/ver == TestHalVersion::V1_0, op);
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}
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#define DEFINE_CONV_2D_SIGNATURE(ver, ...) \
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DEFINE_OPERATION_SIGNATURE(CONV_2D_explicit_##ver){ \
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.opType = TestOperationType::CONV_2D, \
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.supportedDataTypes = {__VA_ARGS__}, \
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.supportedRanks = {4}, \
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.version = TestHalVersion::ver, \
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.inputs = \
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{ \
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INPUT_DEFAULT, \
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INPUT_DEFAULT, \
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INPUT_BIAS, \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_CHOICE(TestOperandType::INT32, 0, 1, 2, 3), \
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}, \
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.outputs = {OUTPUT_DEFAULT}, \
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.constructor = std::bind(conv2DExplicitConstructor, _1, _2, TestHalVersion::ver, _3)}; \
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DEFINE_OPERATION_SIGNATURE(CONV_2D_implicit_##ver){ \
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.opType = TestOperationType::CONV_2D, \
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.supportedDataTypes = {__VA_ARGS__}, \
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.supportedRanks = {4}, \
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.version = TestHalVersion::ver, \
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.inputs = \
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{ \
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INPUT_DEFAULT, \
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INPUT_DEFAULT, \
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INPUT_BIAS, \
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PARAMETER_CHOICE(TestOperandType::INT32, 1, 2), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_CHOICE(TestOperandType::INT32, 0, 1, 2, 3), \
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}, \
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.outputs = {OUTPUT_DEFAULT}, \
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.constructor = std::bind(conv2DImplicitConstructor, _1, _2, TestHalVersion::ver, _3)};
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DEFINE_CONV_2D_SIGNATURE(V1_0, TestOperandType::TENSOR_FLOAT32,
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TestOperandType::TENSOR_QUANT8_ASYMM);
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DEFINE_CONV_2D_SIGNATURE(V1_2, TestOperandType::TENSOR_FLOAT16,
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TestOperandType::TENSOR_QUANT8_ASYMM);
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DEFINE_CONV_2D_SIGNATURE(V1_3, TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED);
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#define DEFINE_CONV_2D_WITH_LAYOUT_OR_DILATION_SIGNATURE(ver, ...) \
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DEFINE_OPERATION_SIGNATURE(CONV_2D_explicit_layout_##ver){ \
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.opType = TestOperationType::CONV_2D, \
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.supportedDataTypes = {__VA_ARGS__}, \
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.supportedRanks = {4}, \
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.version = TestHalVersion::ver, \
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.inputs = \
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{ \
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INPUT_DEFAULT, \
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INPUT_DEFAULT, \
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INPUT_BIAS, \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_CHOICE(TestOperandType::INT32, 0, 1, 2, 3), \
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PARAMETER_CHOICE(TestOperandType::BOOL, true, false), \
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}, \
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.outputs = {OUTPUT_DEFAULT}, \
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.constructor = std::bind(conv2DExplicitConstructor, _1, _2, TestHalVersion::ver, _3)}; \
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DEFINE_OPERATION_SIGNATURE(CONV_2D_implicit_layout_##ver){ \
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.opType = TestOperationType::CONV_2D, \
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.supportedDataTypes = {__VA_ARGS__}, \
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.supportedRanks = {4}, \
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.version = TestHalVersion::ver, \
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.inputs = \
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{ \
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INPUT_DEFAULT, \
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INPUT_DEFAULT, \
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INPUT_BIAS, \
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PARAMETER_CHOICE(TestOperandType::INT32, 1, 2), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_CHOICE(TestOperandType::INT32, 0, 1, 2, 3), \
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PARAMETER_CHOICE(TestOperandType::BOOL, true, false), \
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}, \
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.outputs = {OUTPUT_DEFAULT}, \
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.constructor = std::bind(conv2DImplicitConstructor, _1, _2, TestHalVersion::ver, _3)}; \
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DEFINE_OPERATION_SIGNATURE(CONV_2D_explicit_dilation_##ver){ \
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.opType = TestOperationType::CONV_2D, \
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.supportedDataTypes = {__VA_ARGS__}, \
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.supportedRanks = {4}, \
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.version = TestHalVersion::ver, \
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.inputs = \
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{ \
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INPUT_DEFAULT, \
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INPUT_DEFAULT, \
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INPUT_BIAS, \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_CHOICE(TestOperandType::INT32, 0, 1, 2, 3), \
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PARAMETER_CHOICE(TestOperandType::BOOL, true, false), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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}, \
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.outputs = {OUTPUT_DEFAULT}, \
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.constructor = std::bind(conv2DExplicitConstructor, _1, _2, TestHalVersion::ver, _3)}; \
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DEFINE_OPERATION_SIGNATURE(CONV_2D_implicit_dilation_##ver){ \
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.opType = TestOperationType::CONV_2D, \
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.supportedDataTypes = {__VA_ARGS__}, \
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.supportedRanks = {4}, \
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.version = TestHalVersion::ver, \
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.inputs = \
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{ \
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INPUT_DEFAULT, \
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INPUT_DEFAULT, \
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INPUT_BIAS, \
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PARAMETER_CHOICE(TestOperandType::INT32, 1, 2), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_CHOICE(TestOperandType::INT32, 0, 1, 2, 3), \
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PARAMETER_CHOICE(TestOperandType::BOOL, true, false), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
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}, \
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.outputs = {OUTPUT_DEFAULT}, \
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.constructor = std::bind(conv2DImplicitConstructor, _1, _2, TestHalVersion::ver, _3)};
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DEFINE_CONV_2D_WITH_LAYOUT_OR_DILATION_SIGNATURE(V1_2, TestOperandType::TENSOR_FLOAT32,
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TestOperandType::TENSOR_QUANT8_ASYMM,
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TestOperandType::TENSOR_FLOAT16);
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DEFINE_CONV_2D_WITH_LAYOUT_OR_DILATION_SIGNATURE(V1_3, TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED);
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static void depthwiseConv2DExplicitConstructor(TestOperandType, uint32_t rank, TestHalVersion ver,
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RandomOperation* op) {
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NN_FUZZER_CHECK(rank == 4);
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// Parameters
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int32_t paddingLeft = op->inputs[3]->value<int32_t>();
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int32_t paddingRight = op->inputs[4]->value<int32_t>();
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int32_t paddingTop = op->inputs[5]->value<int32_t>();
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int32_t paddingBottom = op->inputs[6]->value<int32_t>();
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int32_t strideWidth = op->inputs[7]->value<int32_t>();
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int32_t strideHeight = op->inputs[8]->value<int32_t>();
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bool useNchw = false;
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int32_t dilationWidth = 1, dilationHeight = 1;
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if (op->inputs.size() > 11) {
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useNchw = op->inputs[11]->value<bool8>();
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if (op->inputs.size() > 12) {
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dilationWidth = op->inputs[12]->value<int32_t>();
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dilationHeight = op->inputs[13]->value<int32_t>();
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}
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}
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int heightIndex = useNchw ? 2 : 1;
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int widthIndex = useNchw ? 3 : 2;
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int channelIndex = useNchw ? 1 : 3;
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// Input, [batch, height_in, width_in, channel_in]
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op->inputs[0]->dimensions = {RandomVariableType::FREE, RandomVariableType::FREE,
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RandomVariableType::FREE, RandomVariableType::FREE};
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// Filter, [1, height_flt, width_flt, channel_out]
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RandomVariable channelOut =
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op->inputs[9]->value<RandomVariable>() * op->inputs[0]->dimensions[channelIndex];
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op->inputs[1]->dimensions = {1, RandomVariableType::FREE, RandomVariableType::FREE, channelOut};
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// Bias, [channel_out]
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op->inputs[2]->dimensions = {channelOut};
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// Output, [batch, height_out, width_out, channel_out]
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op->outputs[0]->dimensions.resize(4);
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// batch and channel
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op->outputs[0]->dimensions[0] = op->inputs[0]->dimensions[0];
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op->outputs[0]->dimensions[channelIndex] = channelOut;
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// height
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explicitPadding(op->inputs[0]->dimensions[heightIndex], op->inputs[1]->dimensions[1],
|
||
|
|
strideHeight, dilationHeight, paddingTop, paddingBottom,
|
||
|
|
&op->outputs[0]->dimensions[heightIndex]);
|
||
|
|
|
||
|
|
// width
|
||
|
|
explicitPadding(op->inputs[0]->dimensions[widthIndex], op->inputs[1]->dimensions[2],
|
||
|
|
strideWidth, dilationWidth, paddingLeft, paddingRight,
|
||
|
|
&op->outputs[0]->dimensions[widthIndex]);
|
||
|
|
|
||
|
|
setConvFCScale(/*applyOutputScaleBound=*/ver == TestHalVersion::V1_0, op);
|
||
|
|
}
|
||
|
|
|
||
|
|
static void depthwiseConv2DImplicitConstructor(TestOperandType, uint32_t rank, TestHalVersion ver,
|
||
|
|
RandomOperation* op) {
|
||
|
|
NN_FUZZER_CHECK(rank == 4);
|
||
|
|
|
||
|
|
// Parameters
|
||
|
|
int32_t paddingScheme = op->inputs[3]->value<int32_t>();
|
||
|
|
int32_t strideWidth = op->inputs[4]->value<int32_t>();
|
||
|
|
int32_t strideHeight = op->inputs[5]->value<int32_t>();
|
||
|
|
bool useNchw = false;
|
||
|
|
int32_t dilationWidth = 1, dilationHeight = 1;
|
||
|
|
if (op->inputs.size() > 8) {
|
||
|
|
useNchw = op->inputs[8]->value<bool8>();
|
||
|
|
if (op->inputs.size() > 9) {
|
||
|
|
dilationWidth = op->inputs[9]->value<int32_t>();
|
||
|
|
dilationHeight = op->inputs[10]->value<int32_t>();
|
||
|
|
}
|
||
|
|
}
|
||
|
|
int heightIndex = useNchw ? 2 : 1;
|
||
|
|
int widthIndex = useNchw ? 3 : 2;
|
||
|
|
int channelIndex = useNchw ? 1 : 3;
|
||
|
|
|
||
|
|
// Input, [batch, height_in, width_in, channel_in]
|
||
|
|
op->inputs[0]->dimensions = {RandomVariableType::FREE, RandomVariableType::FREE,
|
||
|
|
RandomVariableType::FREE, RandomVariableType::FREE};
|
||
|
|
|
||
|
|
// Filter, [1, height_flt, width_flt, channel_out]
|
||
|
|
RandomVariable channelOut =
|
||
|
|
op->inputs[6]->value<RandomVariable>() * op->inputs[0]->dimensions[channelIndex];
|
||
|
|
op->inputs[1]->dimensions = {1, RandomVariableType::FREE, RandomVariableType::FREE, channelOut};
|
||
|
|
|
||
|
|
// Bias, [channel_out]
|
||
|
|
op->inputs[2]->dimensions = {channelOut};
|
||
|
|
|
||
|
|
// Output, [batch, height_out, width_out, channel_out]
|
||
|
|
op->outputs[0]->dimensions.resize(4);
|
||
|
|
|
||
|
|
// batch and channel
|
||
|
|
op->outputs[0]->dimensions[0] = op->inputs[0]->dimensions[0];
|
||
|
|
op->outputs[0]->dimensions[channelIndex] = channelOut;
|
||
|
|
|
||
|
|
// height and width
|
||
|
|
implicitPadding(op->inputs[0]->dimensions[heightIndex], op->inputs[1]->dimensions[1],
|
||
|
|
strideHeight, dilationHeight, paddingScheme,
|
||
|
|
&op->outputs[0]->dimensions[heightIndex]);
|
||
|
|
implicitPadding(op->inputs[0]->dimensions[widthIndex], op->inputs[1]->dimensions[2],
|
||
|
|
strideWidth, dilationWidth, paddingScheme,
|
||
|
|
&op->outputs[0]->dimensions[widthIndex]);
|
||
|
|
|
||
|
|
setConvFCScale(/*applyOutputScaleBound=*/ver == TestHalVersion::V1_0, op);
|
||
|
|
}
|
||
|
|
|
||
|
|
#define DEFINE_DEPTHWISE_CONV_2D_SIGNATURE(ver, ...) \
|
||
|
|
DEFINE_OPERATION_SIGNATURE(DEPTHWISE_CONV_2D_explicit_##ver){ \
|
||
|
|
.opType = TestOperationType::DEPTHWISE_CONV_2D, \
|
||
|
|
.supportedDataTypes = {__VA_ARGS__}, \
|
||
|
|
.supportedRanks = {4}, \
|
||
|
|
.version = TestHalVersion::ver, \
|
||
|
|
.inputs = \
|
||
|
|
{ \
|
||
|
|
INPUT_DEFAULT, \
|
||
|
|
INPUT_DEFAULT, \
|
||
|
|
INPUT_BIAS, \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
RANDOM_INT_RANGE(1, 5), \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::INT32, 0, 1, 2, 3), \
|
||
|
|
}, \
|
||
|
|
.outputs = {OUTPUT_DEFAULT}, \
|
||
|
|
.constructor = std::bind(depthwiseConv2DExplicitConstructor, _1, _2, \
|
||
|
|
TestHalVersion::ver, _3)}; \
|
||
|
|
DEFINE_OPERATION_SIGNATURE(DEPTHWISE_CONV_2D_implicit_##ver){ \
|
||
|
|
.opType = TestOperationType::DEPTHWISE_CONV_2D, \
|
||
|
|
.supportedDataTypes = {__VA_ARGS__}, \
|
||
|
|
.supportedRanks = {4}, \
|
||
|
|
.version = TestHalVersion::ver, \
|
||
|
|
.inputs = \
|
||
|
|
{ \
|
||
|
|
INPUT_DEFAULT, \
|
||
|
|
INPUT_DEFAULT, \
|
||
|
|
INPUT_BIAS, \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::INT32, 1, 2), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
RANDOM_INT_RANGE(1, 5), \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::INT32, 0, 1, 2, 3), \
|
||
|
|
}, \
|
||
|
|
.outputs = {OUTPUT_DEFAULT}, \
|
||
|
|
.constructor = std::bind(depthwiseConv2DImplicitConstructor, _1, _2, \
|
||
|
|
TestHalVersion::ver, _3)};
|
||
|
|
|
||
|
|
DEFINE_DEPTHWISE_CONV_2D_SIGNATURE(V1_0, TestOperandType::TENSOR_FLOAT32,
|
||
|
|
TestOperandType::TENSOR_QUANT8_ASYMM);
|
||
|
|
DEFINE_DEPTHWISE_CONV_2D_SIGNATURE(V1_2, TestOperandType::TENSOR_FLOAT16,
|
||
|
|
TestOperandType::TENSOR_QUANT8_ASYMM);
|
||
|
|
DEFINE_DEPTHWISE_CONV_2D_SIGNATURE(V1_3, TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED);
|
||
|
|
|
||
|
|
#define DEFINE_DEPTHWISE_CONV_2D_WITH_LAYOUT_OR_DILATION_SIGNATURE(ver, ...) \
|
||
|
|
DEFINE_OPERATION_SIGNATURE(DEPTHWISE_CONV_2D_explicit_layout_##ver){ \
|
||
|
|
.opType = TestOperationType::DEPTHWISE_CONV_2D, \
|
||
|
|
.supportedDataTypes = {__VA_ARGS__}, \
|
||
|
|
.supportedRanks = {4}, \
|
||
|
|
.version = TestHalVersion::ver, \
|
||
|
|
.inputs = \
|
||
|
|
{ \
|
||
|
|
INPUT_DEFAULT, \
|
||
|
|
INPUT_DEFAULT, \
|
||
|
|
INPUT_BIAS, \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
RANDOM_INT_RANGE(1, 5), \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::INT32, 0, 1, 2, 3), \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::BOOL, true, false), \
|
||
|
|
}, \
|
||
|
|
.outputs = {OUTPUT_DEFAULT}, \
|
||
|
|
.constructor = std::bind(depthwiseConv2DExplicitConstructor, _1, _2, \
|
||
|
|
TestHalVersion::ver, _3)}; \
|
||
|
|
DEFINE_OPERATION_SIGNATURE(DEPTHWISE_CONV_2D_implicit_layout_##ver){ \
|
||
|
|
.opType = TestOperationType::DEPTHWISE_CONV_2D, \
|
||
|
|
.supportedDataTypes = {__VA_ARGS__}, \
|
||
|
|
.supportedRanks = {4}, \
|
||
|
|
.version = TestHalVersion::ver, \
|
||
|
|
.inputs = \
|
||
|
|
{ \
|
||
|
|
INPUT_DEFAULT, \
|
||
|
|
INPUT_DEFAULT, \
|
||
|
|
INPUT_BIAS, \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::INT32, 1, 2), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
RANDOM_INT_RANGE(1, 5), \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::INT32, 0, 1, 2, 3), \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::BOOL, true, false), \
|
||
|
|
}, \
|
||
|
|
.outputs = {OUTPUT_DEFAULT}, \
|
||
|
|
.constructor = std::bind(depthwiseConv2DImplicitConstructor, _1, _2, \
|
||
|
|
TestHalVersion::ver, _3)}; \
|
||
|
|
DEFINE_OPERATION_SIGNATURE(DEPTHWISE_CONV_2D_explicit_dilation_##ver){ \
|
||
|
|
.opType = TestOperationType::DEPTHWISE_CONV_2D, \
|
||
|
|
.supportedDataTypes = {__VA_ARGS__}, \
|
||
|
|
.supportedRanks = {4}, \
|
||
|
|
.version = TestHalVersion::ver, \
|
||
|
|
.inputs = \
|
||
|
|
{ \
|
||
|
|
INPUT_DEFAULT, \
|
||
|
|
INPUT_DEFAULT, \
|
||
|
|
INPUT_BIAS, \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
RANDOM_INT_RANGE(1, 5), \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::INT32, 0, 1, 2, 3), \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::BOOL, true, false), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
}, \
|
||
|
|
.outputs = {OUTPUT_DEFAULT}, \
|
||
|
|
.constructor = std::bind(depthwiseConv2DExplicitConstructor, _1, _2, \
|
||
|
|
TestHalVersion::ver, _3)}; \
|
||
|
|
DEFINE_OPERATION_SIGNATURE(DEPTHWISE_CONV_2D_implicit_dilation_##ver){ \
|
||
|
|
.opType = TestOperationType::DEPTHWISE_CONV_2D, \
|
||
|
|
.supportedDataTypes = {__VA_ARGS__}, \
|
||
|
|
.supportedRanks = {4}, \
|
||
|
|
.version = TestHalVersion::ver, \
|
||
|
|
.inputs = \
|
||
|
|
{ \
|
||
|
|
INPUT_DEFAULT, \
|
||
|
|
INPUT_DEFAULT, \
|
||
|
|
INPUT_BIAS, \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::INT32, 1, 2), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
RANDOM_INT_RANGE(1, 5), \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::INT32, 0, 1, 2, 3), \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::BOOL, true, false), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
}, \
|
||
|
|
.outputs = {OUTPUT_DEFAULT}, \
|
||
|
|
.constructor = std::bind(depthwiseConv2DImplicitConstructor, _1, _2, \
|
||
|
|
TestHalVersion::ver, _3)};
|
||
|
|
|
||
|
|
DEFINE_DEPTHWISE_CONV_2D_WITH_LAYOUT_OR_DILATION_SIGNATURE(V1_2, TestOperandType::TENSOR_FLOAT32,
|
||
|
|
TestOperandType::TENSOR_QUANT8_ASYMM,
|
||
|
|
TestOperandType::TENSOR_FLOAT16);
|
||
|
|
DEFINE_DEPTHWISE_CONV_2D_WITH_LAYOUT_OR_DILATION_SIGNATURE(
|
||
|
|
V1_3, TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED);
|
||
|
|
|
||
|
|
static void groupedConv2DExplicitConstructor(TestOperandType, uint32_t rank, RandomOperation* op) {
|
||
|
|
NN_FUZZER_CHECK(rank == 4);
|
||
|
|
|
||
|
|
// Parameters
|
||
|
|
int32_t paddingLeft = op->inputs[3]->value<int32_t>();
|
||
|
|
int32_t paddingRight = op->inputs[4]->value<int32_t>();
|
||
|
|
int32_t paddingTop = op->inputs[5]->value<int32_t>();
|
||
|
|
int32_t paddingBottom = op->inputs[6]->value<int32_t>();
|
||
|
|
int32_t strideWidth = op->inputs[7]->value<int32_t>();
|
||
|
|
int32_t strideHeight = op->inputs[8]->value<int32_t>();
|
||
|
|
bool useNchw = op->inputs[11]->value<bool8>();
|
||
|
|
int heightIndex = useNchw ? 2 : 1;
|
||
|
|
int widthIndex = useNchw ? 3 : 2;
|
||
|
|
int channelIndex = useNchw ? 1 : 3;
|
||
|
|
|
||
|
|
// Input, [batch, height_in, width_in, channel_in]
|
||
|
|
RandomVariable numGroups = op->inputs[9]->value<RandomVariable>();
|
||
|
|
RandomVariable channelGroup = RandomVariableType::FREE;
|
||
|
|
if (useNchw) {
|
||
|
|
op->inputs[0]->dimensions = {RandomVariableType::FREE, numGroups * channelGroup,
|
||
|
|
RandomVariableType::FREE, RandomVariableType::FREE};
|
||
|
|
} else {
|
||
|
|
op->inputs[0]->dimensions = {RandomVariableType::FREE, RandomVariableType::FREE,
|
||
|
|
RandomVariableType::FREE, numGroups * channelGroup};
|
||
|
|
}
|
||
|
|
|
||
|
|
// Filter, [channel_out, height_flt, width_flt, channel_group]
|
||
|
|
op->inputs[1]->dimensions = {RandomVariableType::FREE, RandomVariableType::FREE,
|
||
|
|
RandomVariableType::FREE, channelGroup};
|
||
|
|
// channel_out must be divisible by num_groups.
|
||
|
|
(op->inputs[1]->dimensions[0] % numGroups).setEqual(0);
|
||
|
|
|
||
|
|
// Bias, [channel_out]
|
||
|
|
op->inputs[2]->dimensions = {op->inputs[1]->dimensions[0]};
|
||
|
|
|
||
|
|
// Output, [batch, height_out, width_out, channel_out]
|
||
|
|
op->outputs[0]->dimensions.resize(4);
|
||
|
|
|
||
|
|
// batch and channel
|
||
|
|
op->outputs[0]->dimensions[0] = op->inputs[0]->dimensions[0];
|
||
|
|
op->outputs[0]->dimensions[channelIndex] = op->inputs[1]->dimensions[0];
|
||
|
|
|
||
|
|
// height
|
||
|
|
explicitPadding(op->inputs[0]->dimensions[heightIndex], op->inputs[1]->dimensions[1],
|
||
|
|
strideHeight, /*dilation=*/1, paddingTop, paddingBottom,
|
||
|
|
&op->outputs[0]->dimensions[heightIndex]);
|
||
|
|
|
||
|
|
// width
|
||
|
|
explicitPadding(op->inputs[0]->dimensions[widthIndex], op->inputs[1]->dimensions[2],
|
||
|
|
strideWidth, /*dilation=*/1, paddingLeft, paddingRight,
|
||
|
|
&op->outputs[0]->dimensions[widthIndex]);
|
||
|
|
|
||
|
|
setConvFCScale(/*applyOutputScaleBound=*/false, op);
|
||
|
|
}
|
||
|
|
|
||
|
|
static void groupedConv2DImplicitConstructor(TestOperandType, uint32_t rank, RandomOperation* op) {
|
||
|
|
NN_FUZZER_CHECK(rank == 4);
|
||
|
|
|
||
|
|
// Parameters
|
||
|
|
int32_t paddingScheme = op->inputs[3]->value<int32_t>();
|
||
|
|
int32_t strideWidth = op->inputs[4]->value<int32_t>();
|
||
|
|
int32_t strideHeight = op->inputs[5]->value<int32_t>();
|
||
|
|
bool useNchw = op->inputs[8]->value<bool8>();
|
||
|
|
int heightIndex = useNchw ? 2 : 1;
|
||
|
|
int widthIndex = useNchw ? 3 : 2;
|
||
|
|
int channelIndex = useNchw ? 1 : 3;
|
||
|
|
|
||
|
|
// Input, [batch, height_in, width_in, channel_in]
|
||
|
|
RandomVariable numGroups = op->inputs[6]->value<RandomVariable>();
|
||
|
|
RandomVariable channelGroup = RandomVariableType::FREE;
|
||
|
|
if (useNchw) {
|
||
|
|
op->inputs[0]->dimensions = {RandomVariableType::FREE, numGroups * channelGroup,
|
||
|
|
RandomVariableType::FREE, RandomVariableType::FREE};
|
||
|
|
} else {
|
||
|
|
op->inputs[0]->dimensions = {RandomVariableType::FREE, RandomVariableType::FREE,
|
||
|
|
RandomVariableType::FREE, numGroups * channelGroup};
|
||
|
|
}
|
||
|
|
|
||
|
|
// Filter, [channel_out, height_flt, width_flt, channel_group]
|
||
|
|
op->inputs[1]->dimensions = {RandomVariableType::FREE, RandomVariableType::FREE,
|
||
|
|
RandomVariableType::FREE, channelGroup};
|
||
|
|
// channel_out must be divisible by num_groups.
|
||
|
|
(op->inputs[1]->dimensions[0] % numGroups).setEqual(0);
|
||
|
|
|
||
|
|
// Bias, [channel_out]
|
||
|
|
op->inputs[2]->dimensions = {op->inputs[1]->dimensions[0]};
|
||
|
|
|
||
|
|
// Output, [batch, height_out, width_out, channel_out]
|
||
|
|
op->outputs[0]->dimensions.resize(4);
|
||
|
|
|
||
|
|
// batch and channel
|
||
|
|
op->outputs[0]->dimensions[0] = op->inputs[0]->dimensions[0];
|
||
|
|
op->outputs[0]->dimensions[channelIndex] = op->inputs[1]->dimensions[0];
|
||
|
|
|
||
|
|
// height and width
|
||
|
|
implicitPadding(op->inputs[0]->dimensions[heightIndex], op->inputs[1]->dimensions[1],
|
||
|
|
strideHeight, /*dilation=*/1, paddingScheme,
|
||
|
|
&op->outputs[0]->dimensions[heightIndex]);
|
||
|
|
implicitPadding(op->inputs[0]->dimensions[widthIndex], op->inputs[1]->dimensions[2],
|
||
|
|
strideWidth, /*dilation=*/1, paddingScheme,
|
||
|
|
&op->outputs[0]->dimensions[widthIndex]);
|
||
|
|
|
||
|
|
setConvFCScale(/*applyOutputScaleBound=*/false, op);
|
||
|
|
}
|
||
|
|
|
||
|
|
#define DEFINE_GROUPED_CONV_2D_SIGNATURE(ver, ...) \
|
||
|
|
DEFINE_OPERATION_SIGNATURE(GROUPED_CONV_2D_explicit_##ver){ \
|
||
|
|
.opType = TestOperationType::GROUPED_CONV_2D, \
|
||
|
|
.supportedDataTypes = {__VA_ARGS__}, \
|
||
|
|
.supportedRanks = {4}, \
|
||
|
|
.version = TestHalVersion::ver, \
|
||
|
|
.inputs = \
|
||
|
|
{ \
|
||
|
|
INPUT_DEFAULT, \
|
||
|
|
INPUT_DEFAULT, \
|
||
|
|
INPUT_BIAS, \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
RANDOM_INT_RANGE(1, 5), \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::INT32, 0, 1, 2, 3), \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::BOOL, true, false), \
|
||
|
|
}, \
|
||
|
|
.outputs = {OUTPUT_DEFAULT}, \
|
||
|
|
.constructor = groupedConv2DExplicitConstructor}; \
|
||
|
|
DEFINE_OPERATION_SIGNATURE(GROUPED_CONV_2D_implicit_##ver){ \
|
||
|
|
.opType = TestOperationType::GROUPED_CONV_2D, \
|
||
|
|
.supportedDataTypes = {__VA_ARGS__}, \
|
||
|
|
.supportedRanks = {4}, \
|
||
|
|
.version = TestHalVersion::ver, \
|
||
|
|
.inputs = \
|
||
|
|
{ \
|
||
|
|
INPUT_DEFAULT, \
|
||
|
|
INPUT_DEFAULT, \
|
||
|
|
INPUT_BIAS, \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::INT32, 1, 2), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
RANDOM_INT_RANGE(1, 5), \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::INT32, 0, 1, 2, 3), \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::BOOL, true, false), \
|
||
|
|
}, \
|
||
|
|
.outputs = {OUTPUT_DEFAULT}, \
|
||
|
|
.constructor = groupedConv2DImplicitConstructor};
|
||
|
|
|
||
|
|
DEFINE_GROUPED_CONV_2D_SIGNATURE(V1_2, TestOperandType::TENSOR_FLOAT32,
|
||
|
|
TestOperandType::TENSOR_QUANT8_ASYMM,
|
||
|
|
TestOperandType::TENSOR_FLOAT16);
|
||
|
|
DEFINE_GROUPED_CONV_2D_SIGNATURE(V1_3, TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED);
|
||
|
|
|
||
|
|
static void transposeConv2DExplicitConstructor(TestOperandType, uint32_t rank,
|
||
|
|
RandomOperation* op) {
|
||
|
|
NN_FUZZER_CHECK(rank == 4);
|
||
|
|
|
||
|
|
// Parameters
|
||
|
|
int32_t paddingLeft = op->inputs[3]->value<int32_t>();
|
||
|
|
int32_t paddingRight = op->inputs[4]->value<int32_t>();
|
||
|
|
int32_t paddingTop = op->inputs[5]->value<int32_t>();
|
||
|
|
int32_t paddingBottom = op->inputs[6]->value<int32_t>();
|
||
|
|
int32_t strideWidth = op->inputs[7]->value<int32_t>();
|
||
|
|
int32_t strideHeight = op->inputs[8]->value<int32_t>();
|
||
|
|
bool useNchw = op->inputs[10]->value<bool8>();
|
||
|
|
int heightIndex = useNchw ? 2 : 1;
|
||
|
|
int widthIndex = useNchw ? 3 : 2;
|
||
|
|
int channelIndex = useNchw ? 1 : 3;
|
||
|
|
|
||
|
|
// Input, [batch, height_in, width_in, channel_in]
|
||
|
|
op->inputs[0]->dimensions = {RandomVariableType::FREE, RandomVariableType::FREE,
|
||
|
|
RandomVariableType::FREE, RandomVariableType::FREE};
|
||
|
|
|
||
|
|
// Filter, [channel_out, height_flt, width_flt, channel_in]
|
||
|
|
op->inputs[1]->dimensions = {RandomVariableType::FREE, RandomVariableType::FREE,
|
||
|
|
RandomVariableType::FREE, op->inputs[0]->dimensions[channelIndex]};
|
||
|
|
|
||
|
|
// Bias, [channel_out]
|
||
|
|
op->inputs[2]->dimensions = {op->inputs[1]->dimensions[0]};
|
||
|
|
|
||
|
|
// Output, [batch, height_out, width_out, channel_out]
|
||
|
|
op->outputs[0]->dimensions.resize(4);
|
||
|
|
|
||
|
|
// batch and channel
|
||
|
|
op->outputs[0]->dimensions[0] = op->inputs[0]->dimensions[0];
|
||
|
|
op->outputs[0]->dimensions[channelIndex] = op->inputs[1]->dimensions[0];
|
||
|
|
|
||
|
|
// height
|
||
|
|
explicitPaddingTranspose(op->inputs[0]->dimensions[heightIndex], op->inputs[1]->dimensions[1],
|
||
|
|
strideHeight, paddingTop, paddingBottom,
|
||
|
|
&op->outputs[0]->dimensions[heightIndex]);
|
||
|
|
|
||
|
|
// width
|
||
|
|
explicitPaddingTranspose(op->inputs[0]->dimensions[widthIndex], op->inputs[1]->dimensions[2],
|
||
|
|
strideWidth, paddingLeft, paddingRight,
|
||
|
|
&op->outputs[0]->dimensions[widthIndex]);
|
||
|
|
|
||
|
|
setConvFCScale(/*applyOutputScaleBound=*/false, op);
|
||
|
|
}
|
||
|
|
|
||
|
|
static void transposeConv2DImplicitConstructor(TestOperandType, uint32_t rank,
|
||
|
|
RandomOperation* op) {
|
||
|
|
NN_FUZZER_CHECK(rank == 4);
|
||
|
|
|
||
|
|
// Parameters
|
||
|
|
int32_t paddingScheme = op->inputs[4]->value<int32_t>();
|
||
|
|
int32_t strideWidth = op->inputs[5]->value<int32_t>();
|
||
|
|
int32_t strideHeight = op->inputs[6]->value<int32_t>();
|
||
|
|
bool useNchw = op->inputs[8]->value<bool8>();
|
||
|
|
int heightIndex = useNchw ? 2 : 1;
|
||
|
|
int widthIndex = useNchw ? 3 : 2;
|
||
|
|
int channelIndex = useNchw ? 1 : 3;
|
||
|
|
|
||
|
|
// Input, [batch, height_in, width_in, channel_in]
|
||
|
|
op->inputs[0]->dimensions = {RandomVariableType::FREE, RandomVariableType::FREE,
|
||
|
|
RandomVariableType::FREE, RandomVariableType::FREE};
|
||
|
|
|
||
|
|
// Filter, [channel_out, height_flt, width_flt, channel_in]
|
||
|
|
op->inputs[1]->dimensions = {RandomVariableType::FREE, RandomVariableType::FREE,
|
||
|
|
RandomVariableType::FREE, op->inputs[0]->dimensions[channelIndex]};
|
||
|
|
|
||
|
|
// Bias, [channel_out]
|
||
|
|
op->inputs[2]->dimensions = {op->inputs[1]->dimensions[0]};
|
||
|
|
|
||
|
|
// Output, [batch, height_out, width_out, channel_out]
|
||
|
|
op->outputs[0]->dimensions.resize(4);
|
||
|
|
|
||
|
|
// batch and channel
|
||
|
|
op->outputs[0]->dimensions[0] = op->inputs[0]->dimensions[0];
|
||
|
|
op->outputs[0]->dimensions[channelIndex] = op->inputs[1]->dimensions[0];
|
||
|
|
|
||
|
|
// height and width
|
||
|
|
implicitPaddingTranspose(op->inputs[0]->dimensions[heightIndex], op->inputs[1]->dimensions[1],
|
||
|
|
strideHeight, paddingScheme, &op->outputs[0]->dimensions[heightIndex]);
|
||
|
|
implicitPaddingTranspose(op->inputs[0]->dimensions[widthIndex], op->inputs[1]->dimensions[2],
|
||
|
|
strideWidth, paddingScheme, &op->outputs[0]->dimensions[widthIndex]);
|
||
|
|
op->inputs[3]->dimensions = {4};
|
||
|
|
op->inputs[3]->randomBuffer = op->outputs[0]->dimensions;
|
||
|
|
|
||
|
|
setConvFCScale(/*applyOutputScaleBound=*/false, op);
|
||
|
|
}
|
||
|
|
|
||
|
|
#define DEFINE_TRANSPOSE_CONV_2D_SIGNATURE(ver, ...) \
|
||
|
|
DEFINE_OPERATION_SIGNATURE(TRANSPOSE_CONV_2D_explicit_##ver){ \
|
||
|
|
.opType = TestOperationType::TRANSPOSE_CONV_2D, \
|
||
|
|
.supportedDataTypes = {__VA_ARGS__}, \
|
||
|
|
.supportedRanks = {4}, \
|
||
|
|
.version = TestHalVersion::ver, \
|
||
|
|
.inputs = \
|
||
|
|
{ \
|
||
|
|
INPUT_DEFAULT, \
|
||
|
|
INPUT_DEFAULT, \
|
||
|
|
INPUT_BIAS, \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::INT32, 0, 1, 2, 3), \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::BOOL, true, false), \
|
||
|
|
}, \
|
||
|
|
.outputs = {OUTPUT_DEFAULT}, \
|
||
|
|
.constructor = transposeConv2DExplicitConstructor}; \
|
||
|
|
DEFINE_OPERATION_SIGNATURE(TRANSPOSE_CONV_2D_implicit_##ver){ \
|
||
|
|
.opType = TestOperationType::TRANSPOSE_CONV_2D, \
|
||
|
|
.supportedDataTypes = {__VA_ARGS__}, \
|
||
|
|
.supportedRanks = {4}, \
|
||
|
|
.version = TestHalVersion::ver, \
|
||
|
|
.inputs = \
|
||
|
|
{ \
|
||
|
|
INPUT_DEFAULT, \
|
||
|
|
INPUT_DEFAULT, \
|
||
|
|
INPUT_BIAS, \
|
||
|
|
PARAMETER_NONE(TestOperandType::TENSOR_INT32), \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::INT32, 1, 2), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_RANGE(TestOperandType::INT32, 1, 3), \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::INT32, 0, 1, 2, 3), \
|
||
|
|
PARAMETER_CHOICE(TestOperandType::BOOL, true, false), \
|
||
|
|
}, \
|
||
|
|
.outputs = {OUTPUT_DEFAULT}, \
|
||
|
|
.constructor = transposeConv2DImplicitConstructor};
|
||
|
|
|
||
|
|
DEFINE_TRANSPOSE_CONV_2D_SIGNATURE(V1_2, TestOperandType::TENSOR_FLOAT32,
|
||
|
|
TestOperandType::TENSOR_QUANT8_ASYMM,
|
||
|
|
TestOperandType::TENSOR_FLOAT16);
|
||
|
|
DEFINE_TRANSPOSE_CONV_2D_SIGNATURE(V1_3, TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED);
|
||
|
|
|
||
|
|
} // namespace fuzzing_test
|
||
|
|
} // namespace nn
|
||
|
|
} // namespace android
|