166 lines
4.9 KiB
C++
166 lines
4.9 KiB
C++
/* Copyright 2019 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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#include "tensorflow/lite/kernels/internal/transpose_utils.h"
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namespace tflite {
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namespace transpose_utils {
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bool IsTranspose2DApplicable(const TransposeParams& params,
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const RuntimeShape& input_shape, int* dim0,
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int* dim1) {
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const int dims_cnt = input_shape.DimensionsCount();
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if (dims_cnt == 2) {
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*dim0 = input_shape.Dims(0);
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*dim1 = input_shape.Dims(1);
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return true;
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}
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const int first_perm = params.perm[0];
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for (int i = 1; i < dims_cnt; ++i) {
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int rebased = params.perm[i] - first_perm;
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if (rebased < 0) {
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rebased += dims_cnt;
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}
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if (rebased != i) {
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return false;
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}
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}
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*dim0 = 1;
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*dim1 = 1;
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for (int i = 0; i < dims_cnt; ++i) {
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if (i < first_perm) {
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*dim0 *= input_shape.Dims(i);
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} else {
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*dim1 *= input_shape.Dims(i);
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}
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}
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return true;
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}
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void RemoveOneSizeDimensions(RuntimeShape* input_shape,
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RuntimeShape* output_shape,
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TransposeParams* params) {
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const int dims_cnt = input_shape->DimensionsCount();
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TFLITE_DCHECK_EQ(params->perm_count, dims_cnt);
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bool foundOneSizeDim = false;
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for (int i = 0; i < dims_cnt; ++i) {
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if (input_shape->Dims(i) == 1) {
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foundOneSizeDim = true;
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break;
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}
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}
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// Return here if there is no one size dimension.
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if (!foundOneSizeDim) return;
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// Handle the case where all the dimension size is one.
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if (input_shape->FlatSize() == 1) {
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input_shape->Resize(1);
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input_shape->SetDim(0, 1);
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output_shape->Resize(1);
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output_shape->SetDim(0, 1);
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params->perm_count = 1;
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params->perm[0] = 0;
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return;
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}
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// Resize input shape.
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int new_dims_cnt = 0;
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for (int i = 0; i < dims_cnt; ++i) {
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if (input_shape->Dims(i) == 1) {
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continue;
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}
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input_shape->SetDim(new_dims_cnt, input_shape->Dims(i));
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++new_dims_cnt;
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}
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input_shape->Resize(new_dims_cnt);
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// Resize output shape and re-calculate the perm parameter.
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TransposeParams new_params;
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new_dims_cnt = 0;
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for (int i = 0; i < dims_cnt; ++i) {
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if (output_shape->Dims(i) == 1) {
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continue;
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}
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new_params.perm[new_dims_cnt] = params->perm[i];
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output_shape->SetDim(new_dims_cnt, output_shape->Dims(i));
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++new_dims_cnt;
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}
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output_shape->Resize(new_dims_cnt);
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new_params.perm_count = new_dims_cnt;
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for (int i = 0; i < new_dims_cnt; ++i) {
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int min_val_idx = -1;
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for (int j = 0; j < new_dims_cnt; ++j) {
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if (new_params.perm[j] >= i &&
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(min_val_idx == -1 ||
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new_params.perm[min_val_idx] > new_params.perm[j])) {
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min_val_idx = j;
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}
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}
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new_params.perm[min_val_idx] = i;
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}
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*params = new_params;
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}
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size_t Flatten(const RuntimeShape& input_shape,
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const RuntimeShape& output_shape, const TransposeParams& params,
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RuntimeShape* non_flatten_input_shape,
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RuntimeShape* non_flatten_output_shape,
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TransposeParams* non_flatten_params) {
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// Calculate the total size of non-flatten dimensions.
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int skip_dims_cnt = 0;
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size_t flat_size = input_shape.FlatSize();
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for (int i = 0; i < params.perm_count; ++i) {
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if (params.perm[i] == i) {
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flat_size /= input_shape.Dims(i);
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++skip_dims_cnt;
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} else {
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break;
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}
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}
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// Shrink the shapes and re-calculate the perm parameter.
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const int new_dims_cnt = params.perm_count - skip_dims_cnt;
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non_flatten_input_shape->Resize(new_dims_cnt);
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non_flatten_output_shape->Resize(new_dims_cnt);
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non_flatten_params->perm_count = new_dims_cnt;
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for (int i = skip_dims_cnt; i < params.perm_count; ++i) {
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non_flatten_input_shape->SetDim(i - skip_dims_cnt, input_shape.Dims(i));
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non_flatten_output_shape->SetDim(i - skip_dims_cnt, output_shape.Dims(i));
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non_flatten_params->perm[i - skip_dims_cnt] = params.perm[i];
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}
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for (int i = 0; i < new_dims_cnt; ++i) {
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int min_val_idx = -1;
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for (int j = 0; j < new_dims_cnt; ++j) {
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if (non_flatten_params->perm[j] >= i &&
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(min_val_idx == -1 || non_flatten_params->perm[min_val_idx] >
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non_flatten_params->perm[j])) {
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min_val_idx = j;
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}
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}
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non_flatten_params->perm[min_val_idx] = i;
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}
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return flat_size;
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}
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} // namespace transpose_utils
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} // namespace tflite
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