85 lines
2.9 KiB
C++
85 lines
2.9 KiB
C++
/* Copyright 2018 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 <stdint.h>
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#include "tensorflow/lite/c/common.h"
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#include "tensorflow/lite/kernels/internal/optimized/optimized_ops.h"
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#include "tensorflow/lite/kernels/internal/tensor.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 builtin {
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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 Prepare(TfLiteContext* context, TfLiteNode* node) {
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TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
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TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
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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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output->type = input->type;
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return context->ResizeTensor(context, output,
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TfLiteIntArrayCopy(input->dims));
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}
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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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case kTfLiteInt64:
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reference_ops::Negate(
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GetTensorShape(input), GetTensorData<int64_t>(input),
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GetTensorShape(output), GetTensorData<int64_t>(output));
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break;
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case kTfLiteInt32:
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reference_ops::Negate(
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GetTensorShape(input), GetTensorData<int32_t>(input),
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GetTensorShape(output), GetTensorData<int32_t>(output));
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break;
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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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context->ReportError(
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context,
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"Neg only currently supports int64, int32, and float32, got %d.",
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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, /*free=*/nullptr,
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neg::Prepare, neg::Eval};
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return &r;
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}
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} // namespace builtin
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} // namespace ops
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} // namespace tflite
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