wehub-resource-sync
89 lines
2.7 KiB
C++
89 lines
2.7 KiB
C++
/* Copyright 2022 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_SPLIT_TESTER_H_
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#define TENSORFLOW_LITE_DELEGATES_XNNPACK_SPLIT_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/interpreter.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 SplitTester {
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public:
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SplitTester() = default;
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SplitTester(const SplitTester&) = delete;
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SplitTester& operator=(const SplitTester&) = delete;
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inline SplitTester& SplitDimension(int32_t split_dim) {
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split_dim_ = split_dim;
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return *this;
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}
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inline SplitTester& InputShape(const std::vector<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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int32_t SplitDimension() const { return split_dim_; }
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inline SplitTester& NumSplits(int num_splits) {
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num_splits_ = num_splits;
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return *this;
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}
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inline const int NumSplits() const { return num_splits_; }
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inline const std::vector<int32_t>& InputShape() const { return input_shape_; }
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std::vector<int32_t> OutputShape() const {
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std::vector<int32_t> output_shape = InputShape();
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int32_t split_dim = SplitDimension();
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split_dim += split_dim < 0 ? InputShape().size() : 0;
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EXPECT_LE(0, split_dim);
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EXPECT_EQ(0, output_shape[split_dim] % NumSplits());
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output_shape[split_dim] /= NumSplits();
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return output_shape;
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}
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template <typename T>
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void Test(Interpreter* delegate_interpreter,
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Interpreter* default_interpreter) const;
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void Test(TensorType tensor_type, TfLiteDelegate* delegate) const;
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private:
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std::vector<char> CreateTfLiteModel(TensorType tensor_type) 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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int32_t split_dim_;
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int num_splits_;
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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_SPLIT_TESTER_H_
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