65 lines
2.2 KiB
C++
65 lines
2.2 KiB
C++
/* Copyright 2019 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/kernels/internal/reference/neg.h"
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#include "tensorflow/lite/c/common.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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namespace tflite {
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namespace ops {
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namespace micro {
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namespace neg {
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constexpr int kInputTensor = 0;
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constexpr int kOutputTensor = 0;
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TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
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const TfLiteTensor* input = GetInput(context, node, kInputTensor);
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TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
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switch (input->type) {
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// TODO(wangtz): handle for kTfLiteInt8
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case kTfLiteFloat32:
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reference_ops::Negate(GetTensorShape(input), GetTensorData<float>(input),
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GetTensorShape(output),
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GetTensorData<float>(output));
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break;
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default:
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TF_LITE_KERNEL_LOG(context, "Type %s (%d) not supported.",
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TfLiteTypeGetName(input->type), input->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 neg
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TfLiteRegistration* Register_NEG() {
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static TfLiteRegistration r = {/*init=*/nullptr,
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/*free=*/nullptr,
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/*prepare=*/nullptr,
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/*invoke=*/neg::Eval,
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/*profiling_string=*/nullptr,
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/*builtin_code=*/0,
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/*custom_name=*/nullptr,
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/*version=*/0};
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return &r;
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}
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} // namespace micro
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} // namespace ops
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} // namespace tflite
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