wehub-resource-sync
111 lines
3.9 KiB
C++
111 lines
3.9 KiB
C++
/* Copyright 2018 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/neg.h"
|
|
|
|
#include <stdint.h>
|
|
|
|
#include "tensorflow/lite/core/c/common.h"
|
|
#include "tensorflow/lite/kernels/internal/optimized/optimized_ops.h"
|
|
#include "tensorflow/lite/kernels/internal/tensor.h"
|
|
#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
|
|
#include "tensorflow/lite/kernels/kernel_util.h"
|
|
|
|
namespace tflite {
|
|
namespace ops {
|
|
namespace builtin {
|
|
namespace neg {
|
|
|
|
constexpr int kInputTensor = 0;
|
|
constexpr int kOutputTensor = 0;
|
|
|
|
TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
|
|
TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
|
|
TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
|
|
const TfLiteTensor* input;
|
|
TF_LITE_ENSURE_OK(context, GetInputSafe(context, node, kInputTensor, &input));
|
|
TfLiteTensor* output;
|
|
TF_LITE_ENSURE_OK(context,
|
|
GetOutputSafe(context, node, kOutputTensor, &output));
|
|
|
|
output->type = input->type;
|
|
return context->ResizeTensor(context, output,
|
|
TfLiteIntArrayCopy(input->dims));
|
|
}
|
|
|
|
TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
|
|
const TfLiteTensor* input;
|
|
TF_LITE_ENSURE_OK(context, GetInputSafe(context, node, kInputTensor, &input));
|
|
TfLiteTensor* output;
|
|
TF_LITE_ENSURE_OK(context,
|
|
GetOutputSafe(context, node, kOutputTensor, &output));
|
|
switch (input->type) {
|
|
case kTfLiteInt64:
|
|
reference_ops::Negate(
|
|
GetTensorShape(input), GetTensorData<int64_t>(input),
|
|
GetTensorShape(output), GetTensorData<int64_t>(output));
|
|
break;
|
|
case kTfLiteInt32:
|
|
reference_ops::Negate(
|
|
GetTensorShape(input), GetTensorData<int32_t>(input),
|
|
GetTensorShape(output), GetTensorData<int32_t>(output));
|
|
break;
|
|
case kTfLiteFloat32:
|
|
reference_ops::Negate(GetTensorShape(input), GetTensorData<float>(input),
|
|
GetTensorShape(output),
|
|
GetTensorData<float>(output));
|
|
break;
|
|
case kTfLiteInt8:
|
|
reference_ops::Negate(GetTensorShape(input), GetTensorData<int8_t>(input),
|
|
GetTensorShape(output),
|
|
GetTensorData<int8_t>(output));
|
|
break;
|
|
case kTfLiteInt16:
|
|
reference_ops::Negate(
|
|
GetTensorShape(input), GetTensorData<int16_t>(input),
|
|
GetTensorShape(output), GetTensorData<int16_t>(output));
|
|
break;
|
|
case kTfLiteFloat16:
|
|
reference_ops::Negate(
|
|
GetTensorShape(input), GetTensorData<Eigen::half>(input),
|
|
GetTensorShape(output), GetTensorData<Eigen::half>(output));
|
|
break;
|
|
case kTfLiteBFloat16:
|
|
reference_ops::Negate(
|
|
GetTensorShape(input), GetTensorData<Eigen::half>(input),
|
|
GetTensorShape(output), GetTensorData<Eigen::half>(output));
|
|
break;
|
|
default:
|
|
TF_LITE_KERNEL_LOG(
|
|
context,
|
|
"Neg only currently supports int64, int32, and float32, got %d.",
|
|
input->type);
|
|
return kTfLiteError;
|
|
}
|
|
return kTfLiteOk;
|
|
}
|
|
|
|
} // namespace neg
|
|
|
|
TfLiteRegistration* Register_NEG() {
|
|
static TfLiteRegistration r = {/*init=*/nullptr, /*free=*/nullptr,
|
|
neg::Prepare, neg::Eval};
|
|
return &r;
|
|
}
|
|
|
|
} // namespace builtin
|
|
} // namespace ops
|
|
} // namespace tflite
|