| /* Copyright 2021 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/common.h" |
| #include "tensorflow/lite/kernels/internal/tensor_ctypes.h" |
| #include "tensorflow/lite/kernels/kernel_util.h" |
| #include "tensorflow/lite/micro/kernels/kernel_util.h" |
| #include "tensorflow/lite/micro/micro_log.h" |
| |
| namespace tflite { |
| namespace { |
| |
| constexpr int kInputTensor = 0; |
| constexpr int kOutputTensor = 0; |
| |
| TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) { |
| MicroContext* micro_context = GetMicroContext(context); |
| |
| TF_LITE_ENSURE_EQ(context, NumInputs(node), 1); |
| TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1); |
| TfLiteTensor* input = |
| micro_context->AllocateTempInputTensor(node, kInputTensor); |
| TF_LITE_ENSURE(context, input != nullptr); |
| TfLiteTensor* output = |
| micro_context->AllocateTempOutputTensor(node, kOutputTensor); |
| TF_LITE_ENSURE(context, output != nullptr); |
| output->type = input->type; |
| |
| micro_context->DeallocateTempTfLiteTensor(input); |
| micro_context->DeallocateTempTfLiteTensor(output); |
| return kTfLiteOk; |
| } |
| |
| template <typename T> |
| void resetZeros(T* out, const int num_elements) { |
| for (int i = 0; i < num_elements; ++i) { |
| out[i] = static_cast<T>(0); |
| } |
| } |
| |
| TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { |
| const TfLiteEvalTensor* input = |
| tflite::micro::GetEvalInput(context, node, kInputTensor); |
| TfLiteEvalTensor* output = |
| tflite::micro::GetEvalOutput(context, node, kOutputTensor); |
| int flat_size = MatchingFlatSize(tflite::micro::GetTensorShape(input), |
| tflite::micro::GetTensorShape(output)); |
| switch (input->type) { |
| case kTfLiteInt64: |
| resetZeros(tflite::micro::GetTensorData<int64_t>(output), flat_size); |
| break; |
| case kTfLiteInt32: |
| resetZeros(tflite::micro::GetTensorData<int32_t>(output), flat_size); |
| break; |
| case kTfLiteInt8: |
| resetZeros(tflite::micro::GetTensorData<int8_t>(output), flat_size); |
| break; |
| case kTfLiteFloat32: |
| resetZeros(tflite::micro::GetTensorData<float>(output), flat_size); |
| break; |
| default: |
| MicroPrintf( |
| "ZerosLike only currently supports int64, int32, " |
| "and float32, got %d.", |
| input->type); |
| return kTfLiteError; |
| } |
| return kTfLiteOk; |
| } |
| } // namespace |
| |
| TFLMRegistration Register_ZEROS_LIKE() { |
| return tflite::micro::RegisterOp(nullptr, Prepare, Eval); |
| } |
| |
| } // namespace tflite |