wehub-resource-sync
69 lines
2.4 KiB
C++
69 lines
2.4 KiB
C++
/* Copyright 2017 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_KERNELS_TRANSPOSE_TEST_UTILS_H_
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#define TENSORFLOW_LITE_KERNELS_TRANSPOSE_TEST_UTILS_H_
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#include <functional>
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#include <vector>
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#include "absl/algorithm/container.h"
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#include "absl/types/span.h"
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#include "tensorflow/lite/kernels/internal/portable_tensor.h"
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#include "tensorflow/lite/kernels/internal/reference/transpose.h"
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#include "tensorflow/lite/kernels/internal/runtime_shape.h"
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#include "tensorflow/lite/kernels/internal/types.h"
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namespace tflite {
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// Generates an input tensor and permutes its dimensions.
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//
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// The input tensor is filled with sequentially increasing values.
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//
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// - shape: input tensor shape.
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// - perms: permutation for the dimensions. This should hold a permutation of
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// `[|0, shape.size()|]`.
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//
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// Returns a vector holding the transposed data.
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template <typename T>
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std::vector<T> RunTestPermutation(const absl::Span<const int> shape,
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const absl::Span<const int> perms) {
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// Count elements and allocate output.
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const int count = absl::c_accumulate(shape, 1, std::multiplies<>{});
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std::vector<T> out(count);
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// Create the dummy data
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std::vector<T> input(count);
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absl::c_iota(input, static_cast<T>(0));
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// Make input and output shapes.
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const RuntimeShape input_shape(shape.size(), shape.data());
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RuntimeShape output_shape(perms.size());
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for (int i = 0; i < perms.size(); i++) {
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output_shape.SetDim(i, input_shape.Dims(perms[i]));
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}
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TransposeParams params{};
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params.perm_count = static_cast<int8_t>(perms.size());
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absl::c_copy(perms, params.perm);
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reference_ops::Transpose(params, input_shape, input.data(), output_shape,
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out.data());
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return out;
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}
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} // namespace tflite
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#endif // TENSORFLOW_LITE_KERNELS_TRANSPOSE_TEST_UTILS_H_
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