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- /* Copyright 2017 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.
- ==============================================================================*/
- #include "tensorflow/lite/c/builtin_op_data.h"
- #include "tensorflow/lite/c/common.h"
- #include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
- #include "tensorflow/lite/kernels/kernel_util.h"
- #include "tensorflow/lite/kernels/op_macros.h"
- #include "tensorflow/lite/micro/kernels/kernel_util.h"
- #include "tensorflow/lite/micro/memory_helpers.h"
- #include "tensorflow/lite/micro/micro_utils.h"
- namespace tflite {
- namespace ops {
- namespace micro {
- namespace reshape {
- constexpr int kInputTensor = 0;
- constexpr int kOutputTensor = 0;
- TfLiteStatus ReshapeOutput(TfLiteContext* context, TfLiteNode* node) {
- const TfLiteTensor* input = GetInput(context, node, kInputTensor);
- TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
- // Tensorflow's Reshape allows one of the shape components to have the
- // special -1 value, meaning it will be calculated automatically based on the
- // input. Here we calculate what that dimension should be so that the number
- // of output elements in the same as the number of input elements.
- int num_input_elements = NumElements(input);
- TfLiteIntArray* output_shape = output->dims;
- if (NumInputs(node) == 1 && // Legacy scalar supported with params.
- output_shape->size == 1 && output_shape->data[0] == 0) {
- // Legacy tflite models use a shape parameter of [0] to indicate scalars,
- // so adjust accordingly. TODO(b/111614235): Allow zero-sized buffers during
- // toco conversion.
- output_shape->size = 0;
- }
- int num_output_elements = 1;
- int stretch_dim = -1;
- for (int i = 0; i < output_shape->size; ++i) {
- int value = output_shape->data[i];
- if (value == -1) {
- TF_LITE_ENSURE_EQ(context, stretch_dim, -1);
- stretch_dim = i;
- } else {
- num_output_elements *= value;
- }
- }
- if (stretch_dim != -1) {
- output_shape->data[stretch_dim] = num_input_elements / num_output_elements;
- num_output_elements *= output_shape->data[stretch_dim];
- }
- TF_LITE_ENSURE_TYPES_EQ(context, input->type, output->type);
- TF_LITE_ENSURE_EQ(context, num_input_elements, num_output_elements);
- return kTfLiteOk;
- }
- TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
- TF_LITE_ENSURE(context, NumInputs(node) == 1 || NumInputs(node) == 2);
- TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
- TF_LITE_ENSURE_EQ(context, ReshapeOutput(context, node), kTfLiteOk);
- return kTfLiteOk;
- }
- TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
- const TfLiteEvalTensor* input =
- tflite::micro::GetEvalInput(context, node, kInputTensor);
- TfLiteEvalTensor* output =
- tflite::micro::GetEvalOutput(context, node, kOutputTensor);
- // TODO(b/162522304): storing input bytes in OpData increases some models
- // significantly, possibly due to alignment issues.
- size_t input_bytes;
- TF_LITE_ENSURE_STATUS(TfLiteTypeSizeOf(input->type, &input_bytes));
- input_bytes *= ElementCount(*input->dims);
- // Do nothing for in-place reshape.
- if (input->data.raw != output->data.raw) {
- // Otherwise perform reshape with copy.
- for (size_t i = 0; i < input_bytes; ++i) {
- output->data.raw[i] = input->data.raw[i];
- }
- }
- return kTfLiteOk;
- }
- } // namespace reshape
- TfLiteRegistration Register_RESHAPE() {
- return {/*init=*/nullptr,
- /*free=*/nullptr,
- /*prepare=*/reshape::Prepare,
- /*invoke=*/reshape::Eval,
- /*profiling_string=*/nullptr,
- /*builtin_code=*/0,
- /*custom_name=*/nullptr,
- /*version=*/0};
- }
- } // namespace micro
- } // namespace ops
- } // namespace tflite
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