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104 lines
3.7 KiB
104 lines
3.7 KiB
/*
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* Copyright (C) 2018 The Android Open Source Project
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*
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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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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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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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#define LOG_TAG "Operations"
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#include "Cast.h"
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#include <algorithm>
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#include "Operations.h"
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#include "Tracing.h"
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namespace android {
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namespace nn {
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namespace cast {
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namespace {
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template <typename FromT, typename ToT>
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void copyCast(const FromT* in, ToT* out, int numElements) {
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std::transform(in, in + numElements, out, [](FromT a) -> ToT {
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if constexpr (std::is_same_v<ToT, uint8_t>) {
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if (a < 0) return 0;
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if (a > 255) return 255;
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}
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return static_cast<ToT>(a);
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});
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}
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template <typename FromT>
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bool copyToTensor(const FromT* inputData, int numElements, uint8_t* outputData,
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const Shape& outputShape) {
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#define ANDROID_NN_COPY_CAST(operandType, dataType) \
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case operandType: { \
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NNTRACE_COMP("cast::copyCast::" #dataType); \
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copyCast(inputData, reinterpret_cast<dataType*>(outputData), numElements); \
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return true; \
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}
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switch (outputShape.type) {
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ANDROID_NN_COPY_CAST(OperandType::TENSOR_FLOAT16, _Float16);
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ANDROID_NN_COPY_CAST(OperandType::TENSOR_FLOAT32, float);
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ANDROID_NN_COPY_CAST(OperandType::TENSOR_INT32, int32_t);
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ANDROID_NN_COPY_CAST(OperandType::TENSOR_QUANT8_ASYMM, uint8_t);
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default:
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LOG(ERROR) << "Unsupported CAST output type";
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return false;
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}
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#undef ANDROID_NN_COPY_CAST
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}
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} // namespace
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bool prepare(const Shape& input, Shape* output) {
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output->dimensions = input.dimensions;
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return true;
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}
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bool eval(const uint8_t* inputData, const Shape& inputShape, uint8_t* outputData,
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const Shape& outputShape) {
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NNTRACE_TRANS("cast::eval");
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int numElements = getNumberOfElements(inputShape);
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#define ANDROID_NN_COPY_TO_TENSOR(operandType, dataType) \
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case operandType: { \
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NNTRACE_TRANS("cast::copyToTensor::" #dataType); \
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copyToTensor(reinterpret_cast<const dataType*>(inputData), numElements, outputData, \
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outputShape); \
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return true; \
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}
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switch (inputShape.type) {
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ANDROID_NN_COPY_TO_TENSOR(OperandType::TENSOR_FLOAT16, _Float16);
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ANDROID_NN_COPY_TO_TENSOR(OperandType::TENSOR_FLOAT32, float);
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ANDROID_NN_COPY_TO_TENSOR(OperandType::TENSOR_INT32, int32_t);
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ANDROID_NN_COPY_TO_TENSOR(OperandType::TENSOR_QUANT8_ASYMM, uint8_t);
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default:
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if (inputShape.type == outputShape.type) {
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return copyData(inputData, inputShape, outputData, outputShape);
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} else {
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LOG(ERROR) << "Unsupported CAST input type";
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return false;
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}
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}
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#undef ANDROID_NN_COPY_TO_TENSOR
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}
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} // namespace cast
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} // namespace nn
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} // namespace android
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