178 lines
4.8 KiB
C++
178 lines
4.8 KiB
C++
/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#ifndef TENSORFLOW_LITE_DELEGATES_XNNPACK_POOL_2D_TESTER_H_
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#define TENSORFLOW_LITE_DELEGATES_XNNPACK_POOL_2D_TESTER_H_
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#include <cstdint>
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#include <vector>
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#include <gtest/gtest.h>
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#include "tensorflow/lite/c/common.h"
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#include "tensorflow/lite/schema/schema_generated.h"
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namespace tflite {
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namespace xnnpack {
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class Pool2DTester {
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public:
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Pool2DTester() = default;
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Pool2DTester(const Pool2DTester&) = delete;
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Pool2DTester& operator=(const Pool2DTester&) = delete;
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inline Pool2DTester& BatchSize(int32_t batch_size) {
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EXPECT_GT(batch_size, 0);
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batch_size_ = batch_size;
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return *this;
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}
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inline int32_t BatchSize() const { return batch_size_; }
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inline Pool2DTester& Channels(int32_t channels) {
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EXPECT_GT(channels, 0);
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channels_ = channels;
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return *this;
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}
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inline int32_t Channels() const { return channels_; }
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inline Pool2DTester& InputHeight(int32_t input_height) {
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EXPECT_GT(input_height, 0);
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input_height_ = input_height;
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return *this;
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}
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inline int32_t InputHeight() const { return input_height_; }
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inline Pool2DTester& InputWidth(int32_t input_width) {
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EXPECT_GT(input_width, 0);
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input_width_ = input_width;
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return *this;
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}
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inline int32_t InputWidth() const { return input_width_; }
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inline int32_t OutputWidth() const {
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if (Padding() == ::tflite::Padding_SAME) {
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return (InputWidth() - 1) / StrideWidth() + 1;
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} else {
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return (InputWidth() - PoolingWidth()) / StrideWidth() + 1;
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}
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}
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inline int32_t OutputHeight() const {
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if (Padding() == ::tflite::Padding_SAME) {
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return (InputHeight() - 1) / StrideHeight() + 1;
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} else {
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return (InputHeight() - PoolingHeight()) / StrideHeight() + 1;
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}
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}
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inline Pool2DTester& PoolingHeight(int32_t pooling_height) {
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EXPECT_GT(pooling_height, 0);
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pooling_height_ = pooling_height;
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return *this;
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}
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inline int32_t PoolingHeight() const { return pooling_height_; }
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inline Pool2DTester& PoolingWidth(int32_t pooling_width) {
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EXPECT_GT(pooling_width, 0);
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pooling_width_ = pooling_width;
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return *this;
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}
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inline int32_t PoolingWidth() const { return pooling_width_; }
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inline Pool2DTester& StrideHeight(int32_t stride_height) {
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EXPECT_GT(stride_height, 0);
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stride_height_ = stride_height;
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return *this;
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}
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inline int32_t StrideHeight() const { return stride_height_; }
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inline Pool2DTester& StrideWidth(int32_t stride_width) {
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EXPECT_GT(stride_width, 0);
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stride_width_ = stride_width;
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return *this;
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}
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inline int32_t StrideWidth() const { return stride_width_; }
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inline Pool2DTester& SamePadding() {
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padding_ = ::tflite::Padding_SAME;
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return *this;
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}
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inline Pool2DTester& ValidPadding() {
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padding_ = ::tflite::Padding_VALID;
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return *this;
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}
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inline Pool2DTester& ReluActivation() {
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activation_ = ::tflite::ActivationFunctionType_RELU;
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return *this;
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}
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inline Pool2DTester& Relu6Activation() {
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activation_ = ::tflite::ActivationFunctionType_RELU6;
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return *this;
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}
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inline Pool2DTester& ReluMinus1To1Activation() {
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activation_ = ::tflite::ActivationFunctionType_RELU_N1_TO_1;
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return *this;
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}
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inline Pool2DTester& TanhActivation() {
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activation_ = ::tflite::ActivationFunctionType_TANH;
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return *this;
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}
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inline Pool2DTester& SignBitActivation() {
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activation_ = ::tflite::ActivationFunctionType_SIGN_BIT;
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return *this;
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}
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void Test(tflite::BuiltinOperator pool_op, TfLiteDelegate* delegate) const;
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private:
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std::vector<char> CreateTfLiteModel(tflite::BuiltinOperator pool_op) const;
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inline ::tflite::Padding Padding() const { return padding_; }
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inline ::tflite::ActivationFunctionType Activation() const {
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return activation_;
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}
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int32_t batch_size_ = 1;
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int32_t channels_ = 1;
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int32_t input_height_ = 1;
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int32_t input_width_ = 1;
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int32_t pooling_height_ = 1;
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int32_t pooling_width_ = 1;
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int32_t stride_height_ = 1;
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int32_t stride_width_ = 1;
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::tflite::Padding padding_ = ::tflite::Padding_VALID;
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::tflite::ActivationFunctionType activation_ =
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::tflite::ActivationFunctionType_NONE;
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};
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} // namespace xnnpack
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} // namespace tflite
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#endif // TENSORFLOW_LITE_DELEGATES_XNNPACK_POOL_2D_TESTER_H_
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