mirror of
https://github.com/vee1e/tflite-micro.git
synced 2026-09-01 17:57:27 +00:00
93d4b1ccc6
efactor init, prepare , and eval functions to be unique names for kernels who's name starts with the Letters N-Z BUG=[b/313963581](https://b.corp.google.com/issues/313963581)
105 lines
3.8 KiB
C++
105 lines
3.8 KiB
C++
/* Copyright 2023 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include "tensorflow/lite/micro/kernels/svdf.h"
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#include <math.h>
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#include "tensorflow/lite/c/builtin_op_data.h"
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#include "tensorflow/lite/c/common.h"
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#include "tensorflow/lite/kernels/internal/common.h"
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#include "tensorflow/lite/kernels/internal/quantization_util.h"
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#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
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#include "tensorflow/lite/kernels/kernel_util.h"
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#include "tensorflow/lite/kernels/op_macros.h"
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#include "tensorflow/lite/micro/kernels/activation_utils.h"
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#include "tensorflow/lite/micro/kernels/kernel_util.h"
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#include "tensorflow/lite/micro/micro_log.h"
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#include "tensorflow/lite/micro/micro_utils.h"
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namespace tflite {
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namespace {
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void* InitSvdf(TfLiteContext* context, const char* buffer, size_t length) {
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TFLITE_DCHECK(context->AllocatePersistentBuffer != nullptr);
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return context->AllocatePersistentBuffer(context, sizeof(OpDataSvdf));
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}
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TfLiteStatus EvalSvdf(TfLiteContext* context, TfLiteNode* node) {
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auto* params = reinterpret_cast<TfLiteSVDFParams*>(node->builtin_data);
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TFLITE_DCHECK(node->user_data != nullptr);
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const OpDataSvdf& data = *(static_cast<const OpDataSvdf*>(node->user_data));
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const TfLiteEvalTensor* input =
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tflite::micro::GetEvalInput(context, node, kSvdfInputTensor);
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const TfLiteEvalTensor* weights_feature =
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tflite::micro::GetEvalInput(context, node, kSvdfWeightsFeatureTensor);
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const TfLiteEvalTensor* weights_time =
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tflite::micro::GetEvalInput(context, node, kSvdfWeightsTimeTensor);
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// TODO(#1751): account for optional bias tensor
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const TfLiteEvalTensor* bias =
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(NumInputs(node) == 5)
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? tflite::micro::GetEvalInput(context, node, kSvdfBiasTensor)
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: nullptr;
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TfLiteEvalTensor* activation_state = tflite::micro::GetMutableEvalInput(
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context, node, kSvdfInputActivationStateTensor);
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TfLiteEvalTensor* output =
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tflite::micro::GetEvalOutput(context, node, kSvdfOutputTensor);
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switch (weights_feature->type) {
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case kTfLiteFloat32: {
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EvalFloatSvdfReference(
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context, node, input, weights_feature, weights_time, bias, params,
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data.scratch_tensor_index, activation_state, output);
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break;
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}
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case kTfLiteInt8: {
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switch (weights_time->type) {
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case kTfLiteInt16: {
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EvalInt16SvdfReference(context, node, input, weights_feature,
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weights_time, bias, params, activation_state,
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output, data);
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break;
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}
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case kTfLiteInt8: {
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EvalInt8SvdfReference(context, node, input, weights_feature,
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weights_time, bias, params, activation_state,
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output, data);
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break;
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}
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default:
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MicroPrintf("Type %s not currently supported.",
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TfLiteTypeGetName(weights_time->type));
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return kTfLiteError;
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}
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break;
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}
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default:
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MicroPrintf("Type %s not currently supported.",
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TfLiteTypeGetName(weights_feature->type));
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return kTfLiteError;
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}
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return kTfLiteOk;
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}
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} // namespace
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TFLMRegistration Register_SVDF() {
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return tflite::micro::RegisterOp(InitSvdf, PrepareSvdf, EvalSvdf);
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}
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} // namespace tflite
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