121 lines
3.5 KiB
C++
121 lines
3.5 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_FULLY_CONNECTED_TESTER_H_
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#define TENSORFLOW_LITE_DELEGATES_XNNPACK_FULLY_CONNECTED_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 FullyConnectedTester {
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public:
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FullyConnectedTester() = default;
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FullyConnectedTester(const FullyConnectedTester&) = delete;
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FullyConnectedTester& operator=(const FullyConnectedTester&) = delete;
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inline FullyConnectedTester& InputShape(
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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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input_size_ = ComputeSize(input_shape_);
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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 int32_t InputSize() const { return input_size_; }
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inline FullyConnectedTester& InputChannels(int32_t input_channels) {
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EXPECT_GT(input_channels, 0);
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input_channels_ = input_channels;
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return *this;
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}
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inline int32_t InputChannels() const { return input_channels_; }
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inline FullyConnectedTester& OutputChannels(int32_t output_channels) {
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EXPECT_GT(output_channels, 0);
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output_channels_ = output_channels;
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return *this;
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}
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inline int32_t OutputChannels() const { return output_channels_; }
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std::vector<int32_t> OutputShape() const;
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inline FullyConnectedTester& KeepDims(bool keep_dims) {
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keep_dims_ = keep_dims;
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return *this;
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}
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inline bool KeepDims() const { return keep_dims_; }
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inline FullyConnectedTester& 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 FullyConnectedTester& ReluActivation() {
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activation_ = ::tflite::ActivationFunctionType_RELU;
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return *this;
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}
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inline FullyConnectedTester& Relu6Activation() {
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activation_ = ::tflite::ActivationFunctionType_RELU6;
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return *this;
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}
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inline FullyConnectedTester& 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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void Test(TfLiteDelegate* delegate) const;
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private:
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std::vector<char> CreateTfLiteModel() const;
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inline ::tflite::ActivationFunctionType Activation() const {
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return activation_;
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}
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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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int32_t input_size_ = 1;
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int32_t input_channels_ = 1;
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int32_t output_channels_ = 1;
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bool keep_dims_ = false;
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bool fp16_weights_ = false;
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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_FULLY_CONNECTED_TESTER_H_
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