STT-tensorflow/tensorflow/lite/delegates/xnnpack/pad_tester.h
Marat Dukhan 7b48dab3ac Prune unused includes in XNNPACK tester headers
PiperOrigin-RevId: 313123993
Change-Id: I69549e97cc1c4926ea5c2cab7fb56f3aa1e28b0d
2020-05-25 20:24:56 -07:00

88 lines
2.6 KiB
C++

/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
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.
==============================================================================*/
#ifndef TENSORFLOW_LITE_DELEGATES_XNNPACK_PAD_TESTER_H_
#define TENSORFLOW_LITE_DELEGATES_XNNPACK_PAD_TESTER_H_
#include <cstdint>
#include <vector>
#include <gtest/gtest.h>
#include "tensorflow/lite/c/common.h"
namespace tflite {
namespace xnnpack {
class PadTester {
public:
PadTester() = default;
PadTester(const PadTester&) = delete;
PadTester& operator=(const PadTester&) = delete;
inline PadTester& InputShape(std::initializer_list<int32_t> shape) {
for (auto it = shape.begin(); it != shape.end(); ++it) {
EXPECT_GT(*it, 0);
}
input_shape_ = std::vector<int32_t>(shape.begin(), shape.end());
return *this;
}
inline const std::vector<int32_t>& InputShape() const { return input_shape_; }
inline PadTester& InputPrePaddings(std::initializer_list<int32_t> paddings) {
for (auto it = paddings.begin(); it != paddings.end(); ++it) {
EXPECT_GE(*it, 0);
}
input_pre_paddings_ =
std::vector<int32_t>(paddings.begin(), paddings.end());
return *this;
}
inline const std::vector<int32_t> InputPrePaddings() const {
return input_pre_paddings_;
}
inline PadTester& InputPostPaddings(std::initializer_list<int32_t> paddings) {
for (auto it = paddings.begin(); it != paddings.end(); ++it) {
EXPECT_GE(*it, 0);
}
input_post_paddings_ =
std::vector<int32_t>(paddings.begin(), paddings.end());
return *this;
}
inline const std::vector<int32_t> InputPostPaddings() const {
return input_post_paddings_;
}
std::vector<int32_t> OutputShape() const;
void Test(TfLiteDelegate* delegate) const;
private:
std::vector<char> CreateTfLiteModel() const;
static int32_t ComputeSize(const std::vector<int32_t>& shape);
std::vector<int32_t> input_shape_;
std::vector<int32_t> input_pre_paddings_;
std::vector<int32_t> input_post_paddings_;
};
} // namespace xnnpack
} // namespace tflite
#endif // TENSORFLOW_LITE_DELEGATES_XNNPACK_PAD_TESTER_H_