chromium/third_party/tflite/src/tensorflow/lite/kernels/div.cc

/* Copyright 2017 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 <stddef.h>
#include <stdint.h>

#include "tensorflow/lite/core/c/builtin_op_data.h"
#include "tensorflow/lite/core/c/common.h"
#include "tensorflow/lite/kernels/internal/compatibility.h"
#include "tensorflow/lite/kernels/internal/optimized/cpu_check.h"
#include "tensorflow/lite/kernels/internal/optimized/neon_check.h"
#include "tensorflow/lite/kernels/internal/optimized/optimized_ops.h"
#include "tensorflow/lite/kernels/internal/quantization_util.h"
#include "tensorflow/lite/kernels/internal/reference/process_broadcast_shapes.h"
#include "tensorflow/lite/kernels/internal/reference/reference_ops.h"
#include "tensorflow/lite/kernels/internal/tensor.h"
#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
#include "tensorflow/lite/kernels/internal/types.h"
#include "tensorflow/lite/kernels/kernel_util.h"

#ifdef TFLITE_KERNEL_USE_XNNPACK
#include <algorithm>
#include <array>
#include <limits>

#include "xnnpack.h"  // from @XNNPACK
#include "tensorflow/lite/kernels/cpu_backend_context.h"
#include "tensorflow/lite/minimal_logging.h"
#endif  // TFLITE_KERNEL_USE_XNNPACK

namespace tflite {
namespace ops {
namespace builtin {
namespace div {

// This file has three implementation of Div.
enum KernelType {};

constexpr int kInputTensor1 =;
constexpr int kInputTensor2 =;
constexpr int kOutputTensor =;

struct OpData {};

void* Init(TfLiteContext* context, const char* buffer, size_t length) {}

void Free(TfLiteContext* context, void* buffer) {}

TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {}

template <KernelType kernel_type>
void EvalDiv(TfLiteContext* context, TfLiteNode* node, TfLiteDivParams* params,
             const OpData* data, const TfLiteTensor* input1,
             const TfLiteTensor* input2, TfLiteTensor* output) {}

template <KernelType kernel_type>
TfLiteStatus EvalQuantized(TfLiteContext* context, TfLiteNode* node,
                           TfLiteDivParams* params, const OpData* data,
                           const TfLiteTensor* input1,
                           const TfLiteTensor* input2, TfLiteTensor* output) {}

template <typename T>
TfLiteStatus CheckNonZero(TfLiteContext* context, const TfLiteTensor* tensor) {}

template <KernelType kernel_type>
TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {}

}  // namespace div

TfLiteRegistration* Register_DIV_REF() {}

TfLiteRegistration* Register_DIV_GENERIC_OPT() {}

TfLiteRegistration* Register_DIV_NEON_OPT() {}

TfLiteRegistration* Register_DIV() {}

}  // namespace builtin
}  // namespace ops
}  // namespace tflite