blob: 007dc8acfccaabc947d0b63fbfba2c27c995c878 [file] [log] [blame]
/* 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.
==============================================================================*/
/* Copyright 2020 The Qualcomm Innovation Center, Inc. All Rights Reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted (subject to the limitations in the disclaimer
below) provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice,
this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
* Neither the name of Qualcomm Innovation Center, Inc. nor the names of its
contributors may be used to endorse or promote products derived from this
software without specific prior written permission.
NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED BY
THIS LICENSE. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND
CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT
NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER
OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
==============================================================================*/
#ifndef _HEXAGON_TFLM_TRANSLATION_SVDF_H_
#define _HEXAGON_TFLM_TRANSLATION_SVDF_H_
#include "tensorflow/lite/c/builtin_op_data.h"
#include "tensorflow/lite/c/common.h"
#include "tensorflow/lite/kernels/internal/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/kernels/op_macros.h"
#include "tensorflow/lite/micro/kernels/activation_utils.h"
#include "tensorflow/lite/micro/kernels/kernel_util.h"
#include "tensorflow/lite/micro/micro_utils.h"
namespace tflite {
namespace hexagon_svdf {
void* HexagonInit(TfLiteContext* context, const char* buffer, size_t length);
TfLiteStatus HexagonPrepare(TfLiteContext* context, TfLiteNode* node);
void HexagonEvalIntegerSVDF(TfLiteContext* context, TfLiteNode* node,
const TfLiteEvalTensor* input_tensor,
const TfLiteEvalTensor* weights_feature_tensor,
const TfLiteEvalTensor* weights_time_tensor,
const TfLiteEvalTensor* bias_tensor,
const TfLiteSVDFParams* params,
TfLiteEvalTensor* activation_state_tensor,
TfLiteEvalTensor* output_tensor, void* op_data);
void HexagonOptimizationEvaluation(TfLiteContext* context, TfLiteNode* node);
bool HexagonOptimizable(TfLiteContext* context, TfLiteNode* node);
} // namespace hexagon_svdf
} // namespace tflite
#endif // _HEXAGON_TFLM_TRANSLATION_SVDF_H_