82 lines
2.8 KiB
C++
82 lines
2.8 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/floor.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 floor {
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constexpr int kInputTensor = 0;
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constexpr int kOutputTensor = 0;
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enum KernelType {
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kReference,
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kGenericOptimized,
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};
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TfLiteStatus Prepare(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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TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
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TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
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TF_LITE_ENSURE_TYPES_EQ(context, input->type, kTfLiteFloat32);
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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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template <KernelType type>
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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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if (type == kGenericOptimized) {
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optimized_ops::Floor(GetTensorShape(input), GetTensorData<float>(input),
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GetTensorShape(output), GetTensorData<float>(output));
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} else {
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reference_ops::Floor(GetTensorShape(input), GetTensorData<float>(input),
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GetTensorShape(output), GetTensorData<float>(output));
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}
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return kTfLiteOk;
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}
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} // namespace floor
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TfLiteRegistration* Register_FLOOR_REF() {
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static TfLiteRegistration r = {/*init=*/nullptr,
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/*free=*/nullptr, floor::Prepare,
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floor::Eval<floor::kReference>};
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return &r;
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}
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TfLiteRegistration* Register_FLOOR() {
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static TfLiteRegistration r = {/*init=*/nullptr,
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/*free=*/nullptr, floor::Prepare,
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floor::Eval<floor::kGenericOptimized>};
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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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