| /* Copyright 2023 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 "signal/src/fft_auto_scale.h" |
| |
| #include <math.h> |
| #include <stddef.h> |
| #include <stdint.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_context.h" |
| |
| namespace tflite { |
| namespace { |
| |
| constexpr int kInputTensor = 0; |
| constexpr int kOutputTensor = 0; |
| constexpr int kScaleBitTensor = 1; |
| |
| TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) { |
| TF_LITE_ENSURE_EQ(context, NumInputs(node), 1); |
| TF_LITE_ENSURE_EQ(context, NumOutputs(node), 2); |
| |
| MicroContext* micro_context = GetMicroContext(context); |
| 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); |
| TfLiteTensor* scale_bit = |
| micro_context->AllocateTempOutputTensor(node, kScaleBitTensor); |
| TF_LITE_ENSURE(context, scale_bit != nullptr); |
| |
| TF_LITE_ENSURE_EQ(context, NumDimensions(input), 1); |
| TF_LITE_ENSURE_EQ(context, NumDimensions(output), 1); |
| TF_LITE_ENSURE_EQ(context, NumDimensions(scale_bit), 0); |
| |
| TF_LITE_ENSURE_TYPES_EQ(context, input->type, kTfLiteInt16); |
| TF_LITE_ENSURE_TYPES_EQ(context, output->type, kTfLiteInt16); |
| TF_LITE_ENSURE_TYPES_EQ(context, scale_bit->type, kTfLiteInt32); |
| |
| micro_context->DeallocateTempTfLiteTensor(scale_bit); |
| micro_context->DeallocateTempTfLiteTensor(input); |
| micro_context->DeallocateTempTfLiteTensor(output); |
| 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); |
| TfLiteEvalTensor* scale_bit = |
| tflite::micro::GetEvalOutput(context, node, kScaleBitTensor); |
| |
| const int16_t* input_data = tflite::micro::GetTensorData<int16_t>(input); |
| int16_t* output_data = tflite::micro::GetTensorData<int16_t>(output); |
| int32_t* scale_bit_data = tflite::micro::GetTensorData<int32_t>(scale_bit); |
| |
| *scale_bit_data = |
| tflm_signal::FftAutoScale(input_data, output->dims->data[0], output_data); |
| return kTfLiteOk; |
| } |
| |
| } // namespace |
| |
| // TODO(b/286250473): remove namespace once de-duped libraries |
| namespace tflm_signal { |
| |
| TFLMRegistration* Register_FFT_AUTO_SCALE() { |
| static TFLMRegistration r = tflite::micro::RegisterOp(nullptr, Prepare, Eval); |
| return &r; |
| } |
| |
| } // namespace tflm_signal |
| } // namespace tflite |