135 lines
4.7 KiB
C++
135 lines
4.7 KiB
C++
/* Copyright 2017 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 <algorithm>
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#include <complex>
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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 cast {
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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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// TODO(ahentz): these two checks would make the new implementation
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// incompatible with some existing models, where params is not specified. It
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// is OK not to have them because toco would have set input and output types
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// to match the parameters.
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// auto* params = reinterpret_cast<TfLiteCastParams*>(node->builtin_data);
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// TF_LITE_ENSURE_EQ(context, input->type, params->in_data_type);
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// TF_LITE_ENSURE_EQ(context, output->type, params->out_data_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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template <typename FromT, typename ToT>
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void copyCast(const FromT* in, ToT* out, int num_elements) {
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std::transform(in, in + num_elements, out,
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[](FromT a) { return static_cast<ToT>(a); });
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}
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template <typename ToT>
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void copyCast(const std::complex<float>* in, ToT* out, int num_elements) {
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std::transform(in, in + num_elements, out, [](std::complex<float> a) {
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return static_cast<ToT>(std::real(a));
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});
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}
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template <>
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void copyCast(const std::complex<float>* in, std::complex<float>* out,
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int num_elements) {
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std::transform(in, in + num_elements, out,
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[](std::complex<float> a) { return a; });
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}
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template <typename FromT>
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TfLiteStatus copyToTensor(const FromT* in, TfLiteTensor* out,
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int num_elements) {
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switch (out->type) {
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case kTfLiteInt64:
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copyCast(in, out->data.i64, num_elements);
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break;
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case kTfLiteInt32:
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copyCast(in, out->data.i32, num_elements);
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break;
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case kTfLiteUInt8:
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copyCast(in, out->data.uint8, num_elements);
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break;
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case kTfLiteFloat32:
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copyCast(in, GetTensorData<float>(out), num_elements);
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break;
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case kTfLiteBool:
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copyCast(in, out->data.b, num_elements);
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break;
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case kTfLiteComplex64:
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copyCast(in, reinterpret_cast<std::complex<float>*>(out->data.c64),
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num_elements);
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break;
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default:
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// Unsupported 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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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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const int num_elements = NumElements(input);
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TF_LITE_ENSURE_EQ(context, num_elements, NumElements(output));
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switch (input->type) {
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case kTfLiteInt64:
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return copyToTensor(input->data.i64, output, num_elements);
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case kTfLiteInt32:
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return copyToTensor(input->data.i32, output, num_elements);
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case kTfLiteUInt8:
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return copyToTensor(input->data.uint8, output, num_elements);
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case kTfLiteFloat32:
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return copyToTensor(GetTensorData<float>(input), output, num_elements);
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case kTfLiteBool:
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return copyToTensor(input->data.b, output, num_elements);
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case kTfLiteComplex64:
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return copyToTensor(
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reinterpret_cast<std::complex<float>*>(input->data.c64), output,
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num_elements);
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default:
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// Unsupported 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 cast
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TfLiteRegistration* Register_CAST() {
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static TfLiteRegistration r = {nullptr, nullptr, cast::Prepare, cast::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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