| /* 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/exp.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/micro/kernels/kernel_util.h" |
| #include "tensorflow/lite/micro/micro_log.h" |
| |
| namespace tflite { |
| namespace { |
| |
| constexpr int kInputTensor = 0; |
| constexpr int kOutputTensor = 0; |
| |
| TfLiteStatus ExpPrepare(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); |
| TF_LITE_ENSURE_TYPES_EQ(context, input->type, kTfLiteFloat32); |
| TF_LITE_ENSURE_TYPES_EQ(context, output->type, input->type); |
| TF_LITE_ENSURE_EQ(context, output->bytes, input->bytes); |
| TF_LITE_ENSURE_EQ(context, output->dims->size, input->dims->size); |
| for (int i = 0; i < output->dims->size; ++i) { |
| TF_LITE_ENSURE_EQ(context, output->dims->data[i], input->dims->data[i]); |
| } |
| micro_context->DeallocateTempTfLiteTensor(input); |
| micro_context->DeallocateTempTfLiteTensor(output); |
| |
| return kTfLiteOk; |
| } |
| |
| TfLiteStatus ExpEval(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)); |
| |
| if (input->type == kTfLiteFloat32) { |
| reference_ops::Exp(tflite::micro::GetTensorData<float>(input), |
| static_cast<size_t>(flat_size), |
| tflite::micro::GetTensorData<float>(output)); |
| } else { |
| MicroPrintf("Type %s (%d) currently not supported by Exp.", |
| TfLiteTypeGetName(input->type), input->type); |
| return kTfLiteError; |
| } |
| return kTfLiteOk; |
| } |
| } // namespace |
| |
| TFLMRegistration Register_EXP() { |
| return tflite::micro::RegisterOp(nullptr, ExpPrepare, ExpEval); |
| } |
| |
| } // namespace tflite |