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/*
* Copyright (C) 2019 The Android Open Source Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#define LOG_TAG "Operations"
#include <algorithm>
#include <cmath>
#include <vector>
#include "IndexedShapeWrapper.h"
#include "OperationResolver.h"
#include "OperationsUtils.h"
#include "Tracing.h"
namespace android {
namespace nn {
namespace elu {
constexpr uint32_t kNumInputs = 2;
constexpr uint32_t kInputTensor = 0;
constexpr uint32_t kAlphaScalar = 1;
constexpr uint32_t kNumOutputs = 1;
constexpr uint32_t kOutputTensor = 0;
namespace {
template <typename T>
bool eluFloat(const T* inputData, const Shape& inputShape, const T alpha, T* outputData,
const Shape& outputShape) {
NNTRACE_COMP("ELU");
int numElements = getNumberOfElements(inputShape);
for (int i = 0; i < numElements; ++i) {
float x = static_cast<float>(inputData[i]);
outputData[i] = static_cast<T>(std::max(0.f, x) + std::min(0.f, alpha * (std::exp(x) - 1)));
}
return true;
}
} // namespace
Result<Version> validate(const IOperationValidationContext* context) {
NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs);
NN_RET_CHECK_EQ(context->getNumOutputs(), kNumOutputs);
auto inputType = context->getInputType(kInputTensor);
auto minSupportedVersion = Version::ANDROID_OC_MR1;
if (inputType == OperandType::TENSOR_FLOAT16 || inputType == OperandType::TENSOR_FLOAT32) {
minSupportedVersion = Version::ANDROID_R;
} else {
NN_RET_CHECK_FAIL() << "Unsupported tensor type for operation ELU";
}
auto scalarType =
inputType == OperandType::TENSOR_FLOAT16 ? OperandType::FLOAT16 : OperandType::FLOAT32;
NN_RET_CHECK(validateInputTypes(context, {inputType, scalarType}));
NN_RET_CHECK(validateOutputTypes(context, {inputType}));
return minSupportedVersion;
}
bool prepare(IOperationExecutionContext* context) {
Shape inputShape = context->getInputShape(kInputTensor);
return context->setOutputShape(kOutputTensor, inputShape);
}
bool execute(IOperationExecutionContext* context) {
// Bypass execution in the case of zero-sized input.
if (getNumberOfElements(context->getOutputShape(kOutputTensor)) == 0) return true;
switch (context->getInputType(kInputTensor)) {
case OperandType::TENSOR_FLOAT16:
return eluFloat(context->getInputBuffer<_Float16>(kInputTensor),
context->getInputShape(kInputTensor),
context->getInputValue<_Float16>(kAlphaScalar),
context->getOutputBuffer<_Float16>(kOutputTensor),
context->getOutputShape(kOutputTensor));
case OperandType::TENSOR_FLOAT32:
return eluFloat(context->getInputBuffer<float>(kInputTensor),
context->getInputShape(kInputTensor),
context->getInputValue<float>(kAlphaScalar),
context->getOutputBuffer<float>(kOutputTensor),
context->getOutputShape(kOutputTensor));
default:
NN_RET_CHECK_FAIL() << "Unsupported tensor type for operation ELU";
}
}
} // namespace elu
NN_REGISTER_OPERATION(ELU, "ELU", elu::validate, elu::prepare, elu::execute);
} // namespace nn
} // namespace android