wehub-resource-sync
115 lines
3.2 KiB
C++
115 lines
3.2 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_PRELU_TESTER_H_
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#define TENSORFLOW_LITE_DELEGATES_XNNPACK_PRELU_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/core/c/common.h"
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#include "tensorflow/lite/delegates/xnnpack/xnnpack_delegate.h"
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namespace tflite {
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namespace xnnpack {
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class PreluTester {
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public:
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PreluTester() = default;
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PreluTester(const PreluTester&) = delete;
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PreluTester& operator=(const PreluTester&) = delete;
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inline PreluTester& InputShape(std::initializer_list<int32_t> shape) {
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for (auto it = shape.begin(); it != shape.end(); ++it) {
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EXPECT_GT(*it, 0);
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}
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input_shape_ = std::vector<int32_t>(shape.begin(), shape.end());
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return *this;
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}
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inline const std::vector<int32_t>& InputShape() const { return input_shape_; }
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inline PreluTester& SlopeShape(std::initializer_list<int32_t> shape) {
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for (auto it = shape.begin(); it != shape.end(); ++it) {
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EXPECT_GT(*it, 0);
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}
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slope_shape_ = std::vector<int32_t>(shape.begin(), shape.end());
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return *this;
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}
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inline const std::vector<int32_t>& SlopeShape() const { return slope_shape_; }
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inline const std::vector<int32_t>& OutputShape() const {
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return InputShape();
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}
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inline PreluTester& FP16Weights() {
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fp16_weights_ = true;
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return *this;
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}
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inline bool FP16Weights() const { return fp16_weights_; }
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inline PreluTester& INT8Weights() {
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int8_weights_ = true;
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return *this;
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}
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inline bool INT8Weights() const { return int8_weights_; }
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inline PreluTester& INT8ChannelWiseWeights() {
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int8_channel_wise_weights_ = true;
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return *this;
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}
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inline bool INT8ChannelWiseWeights() const {
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return int8_channel_wise_weights_;
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}
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inline PreluTester& SparseWeights() {
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sparse_weights_ = true;
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return *this;
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}
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inline bool SparseWeights() const { return sparse_weights_; }
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inline PreluTester& WeightsCache(
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TfLiteXNNPackDelegateWeightsCache* weights_cache) {
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weights_cache_ = weights_cache;
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return *this;
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}
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void Test(TfLiteDelegate* delegate) const;
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private:
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std::vector<char> CreateTfLiteModel() const;
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static int32_t ComputeSize(const std::vector<int32_t>& shape);
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std::vector<int32_t> input_shape_;
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std::vector<int32_t> slope_shape_;
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bool fp16_weights_ = false;
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bool int8_weights_ = false;
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bool int8_channel_wise_weights_ = false;
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bool sparse_weights_ = false;
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TfLiteXNNPackDelegateWeightsCache* weights_cache_ = nullptr;
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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_PRELU_TESTER_H_
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