wehub-resource-sync
97 lines
3.4 KiB
C++
97 lines
3.4 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/round.h"
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#include "Eigen/Core"
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#include "tensorflow/lite/core/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 round {
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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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const TfLiteTensor* input;
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TF_LITE_ENSURE_OK(context, GetInputSafe(context, node, kInputTensor, &input));
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TfLiteTensor* output;
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TF_LITE_ENSURE_OK(context,
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GetOutputSafe(context, node, kOutputTensor, &output));
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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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if (input->type != kTfLiteFloat32 && input->type != kTfLiteFloat16 &&
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input->type != kTfLiteBFloat16) {
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TF_LITE_KERNEL_LOG(context, "Type '%s' is not supported by round.",
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TfLiteTypeGetName(input->type));
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return kTfLiteError;
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}
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output->type = input->type;
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TfLiteIntArray* output_size = TfLiteIntArrayCopy(input->dims);
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return context->ResizeTensor(context, output, output_size);
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}
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TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
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const TfLiteTensor* input;
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TF_LITE_ENSURE_OK(context, GetInputSafe(context, node, kInputTensor, &input));
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TfLiteTensor* output;
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TF_LITE_ENSURE_OK(context,
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GetOutputSafe(context, node, kOutputTensor, &output));
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switch (output->type) {
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case kTfLiteFloat32: {
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optimized_ops::Round<float>(
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GetTensorShape(input), GetTensorData<float>(input),
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GetTensorShape(output), GetTensorData<float>(output));
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break;
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}
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case kTfLiteFloat16: {
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optimized_ops::Round<Eigen::half>(
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GetTensorShape(input), GetTensorData<Eigen::half>(input),
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GetTensorShape(output), GetTensorData<Eigen::half>(output));
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break;
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}
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case kTfLiteBFloat16: {
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optimized_ops::Round<Eigen::bfloat16>(
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GetTensorShape(input), GetTensorData<Eigen::bfloat16>(input),
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GetTensorShape(output), GetTensorData<Eigen::bfloat16>(output));
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break;
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}
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default: {
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TF_LITE_KERNEL_LOG(context, "Type '%s' is not supported by round.",
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TfLiteTypeGetName(output->type));
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return kTfLiteError;
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}
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}
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return kTfLiteOk;
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}
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} // namespace round
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TfLiteRegistration* Register_ROUND() {
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static TfLiteRegistration r = {/*init=*/nullptr,
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/*free=*/nullptr, round::Prepare, round::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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