| /* 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/kernels/internal/reference/prelu.h" |
| |
| #include <cstdint> |
| |
| #include "tensorflow/lite/c/common.h" |
| #include "tensorflow/lite/kernels/internal/quantization_util.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/kernels/prelu.h" |
| #include "tensorflow/lite/micro/micro_log.h" |
| |
| namespace tflite { |
| |
| void* PreluInit(TfLiteContext* context, const char* buffer, size_t length) { |
| TFLITE_DCHECK(context->AllocatePersistentBuffer != nullptr); |
| return context->AllocatePersistentBuffer(context, sizeof(PreluParams)); |
| } |
| |
| TfLiteStatus PreluEval(TfLiteContext* context, TfLiteNode* node) { |
| TFLITE_DCHECK(node->user_data != nullptr); |
| const PreluParams& params = |
| *(static_cast<const PreluParams*>(node->user_data)); |
| |
| const TfLiteEvalTensor* input = tflite::micro::GetEvalInput(context, node, 0); |
| const TfLiteEvalTensor* alpha = tflite::micro::GetEvalInput(context, node, 1); |
| TfLiteEvalTensor* output = tflite::micro::GetEvalOutput(context, node, 0); |
| |
| switch (input->type) { |
| case kTfLiteFloat32: { |
| BroadcastPrelu4DSlowFloat(tflite::micro::GetTensorShape(input), |
| tflite::micro::GetTensorData<float>(input), |
| tflite::micro::GetTensorShape(alpha), |
| tflite::micro::GetTensorData<float>(alpha), |
| tflite::micro::GetTensorShape(output), |
| tflite::micro::GetTensorData<float>(output)); |
| return kTfLiteOk; |
| } break; |
| case kTfLiteInt8: { |
| reference_ops::BroadcastPrelu4DSlow( |
| params, tflite::micro::GetTensorShape(input), |
| tflite::micro::GetTensorData<int8_t>(input), |
| tflite::micro::GetTensorShape(alpha), |
| tflite::micro::GetTensorData<int8_t>(alpha), |
| tflite::micro::GetTensorShape(output), |
| tflite::micro::GetTensorData<int8_t>(output)); |
| return kTfLiteOk; |
| } break; |
| default: |
| MicroPrintf("Only float32 and uint8_t are supported currently, got %d.", |
| TfLiteTypeGetName(input->type)); |
| return kTfLiteError; |
| } |
| } |
| |
| TFLMRegistration Register_PRELU() { |
| return tflite::micro::RegisterOp(PreluInit, PreluPrepare, PreluEval); |
| } |
| |
| } // namespace tflite |