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/*
* Copyright (C) 2018 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 <cmath>
#include "OperationResolver.h"
#include "OperationsUtils.h"
#include "Tracing.h"
namespace android {
namespace nn {
namespace elementwise {
constexpr uint32_t kNumInputs = 1;
constexpr uint32_t kInputTensor = 0;
constexpr uint32_t kNumOutputs = 1;
constexpr uint32_t kOutputTensor = 0;
namespace {
template <typename IntermediateType, typename T>
inline bool compute(IntermediateType func(IntermediateType), const T* input, const Shape& shape,
T* output) {
const auto size = getNumberOfElements(shape);
for (uint32_t i = 0; i < size; ++i) {
output[i] = static_cast<T>(func(static_cast<IntermediateType>(input[i])));
}
return true;
}
bool execute(IOperationExecutionContext* context, float func(float)) {
switch (context->getInputType(kInputTensor)) {
case OperandType::TENSOR_FLOAT16:
return compute<float, _Float16>(func, context->getInputBuffer<_Float16>(kInputTensor),
context->getInputShape(kInputTensor),
context->getOutputBuffer<_Float16>(kOutputTensor));
case OperandType::TENSOR_FLOAT32:
return compute<float, float>(func, context->getInputBuffer<float>(kInputTensor),
context->getInputShape(kInputTensor),
context->getOutputBuffer<float>(kOutputTensor));
default:
NN_RET_CHECK_FAIL() << "Unsupported tensor type for elementwise operation";
}
}
} // namespace
bool executeAbs(IOperationExecutionContext* context) {
switch (context->getInputType(kInputTensor)) {
case OperandType::TENSOR_FLOAT16:
return compute<float, _Float16>(std::abs,
context->getInputBuffer<_Float16>(kInputTensor),
context->getInputShape(kInputTensor),
context->getOutputBuffer<_Float16>(kOutputTensor));
case OperandType::TENSOR_FLOAT32:
return compute<float, float>(std::abs, context->getInputBuffer<float>(kInputTensor),
context->getInputShape(kInputTensor),
context->getOutputBuffer<float>(kOutputTensor));
case OperandType::TENSOR_INT32:
return compute<int32_t, int32_t>(std::abs,
context->getInputBuffer<int32_t>(kInputTensor),
context->getInputShape(kInputTensor),
context->getOutputBuffer<int32_t>(kOutputTensor));
default:
NN_RET_CHECK_FAIL() << "Unsupported tensor type for operation ABS";
}
}
Result<Version> validate(const IOperationValidationContext* context) {
NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs);
NN_RET_CHECK_EQ(context->getNumOutputs(), kNumOutputs);
OperandType inputType = context->getInputType(kInputTensor);
NN_RET_CHECK(inputType == OperandType::TENSOR_FLOAT16 ||
inputType == OperandType::TENSOR_FLOAT32)
<< "Unsupported tensor type for elementwise operation";
NN_RET_CHECK(validateInputTypes(context, {inputType}));
NN_RET_CHECK(validateOutputTypes(context, {inputType}));
return Version::ANDROID_Q;
}
Result<Version> validateAbs(const IOperationValidationContext* context) {
NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs);
NN_RET_CHECK_EQ(context->getNumOutputs(), kNumOutputs);
OperandType inputType = context->getInputType(kInputTensor);
NN_RET_CHECK(inputType == OperandType::TENSOR_FLOAT16 ||
inputType == OperandType::TENSOR_FLOAT32 || inputType == OperandType::TENSOR_INT32)
<< "Unsupported tensor type for operation ABS";
NN_RET_CHECK(validateInputTypes(context, {inputType}));
NN_RET_CHECK(validateOutputTypes(context, {inputType}));
return inputType == OperandType::TENSOR_INT32 ? Version::ANDROID_R : Version::ANDROID_Q;
}
Result<Version> validateFloor(const IOperationValidationContext* context) {
NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs);
NN_RET_CHECK_EQ(context->getNumOutputs(), kNumOutputs);
OperandType inputType = context->getInputType(kInputTensor);
NN_RET_CHECK(inputType == OperandType::TENSOR_FLOAT16 ||
inputType == OperandType::TENSOR_FLOAT32)
<< "Unsupported tensor type for operation FLOOR";
NN_RET_CHECK(validateInputTypes(context, {inputType}));
NN_RET_CHECK(validateOutputTypes(context, {inputType}));
const Shape& input = context->getInputShape(kInputTensor);
if (hasKnownRank(input)) {
NN_RET_CHECK_LE(getNumberOfDimensions(input), 4);
}
return inputType == OperandType::TENSOR_FLOAT16 ? Version::ANDROID_Q : Version::ANDROID_OC_MR1;
}
bool prepare(IOperationExecutionContext* context) {
Shape input = context->getInputShape(kInputTensor);
Shape output = context->getOutputShape(kOutputTensor);
NN_RET_CHECK(SetShape(input, &output));
return context->setOutputShape(kOutputTensor, output);
}
bool prepareFloor(IOperationExecutionContext* context) {
Shape input = context->getInputShape(kInputTensor);
Shape output = context->getOutputShape(kOutputTensor);
NN_RET_CHECK_LE(getNumberOfDimensions(input), 4);
NN_RET_CHECK(SetShape(input, &output));
return context->setOutputShape(kOutputTensor, output);
}
bool executeExp(IOperationExecutionContext* context) {
return execute(context, std::exp);
}
bool executeFloor(IOperationExecutionContext* context) {
return execute(context, std::floor);
}
bool executeLog(IOperationExecutionContext* context) {
return execute(context, std::log);
}
bool executeRsqrt(IOperationExecutionContext* context) {
return execute(context, [](float x) { return 1.f / std::sqrt(x); });
}
bool executeSin(IOperationExecutionContext* context) {
return execute(context, std::sin);
}
bool executeSqrt(IOperationExecutionContext* context) {
return execute(context, std::sqrt);
}
} // namespace elementwise
NN_REGISTER_OPERATION(ABS, "ABS", elementwise::validateAbs, elementwise::prepare,
elementwise::executeAbs);
NN_REGISTER_OPERATION(EXP, "EXP", elementwise::validate, elementwise::prepare,
elementwise::executeExp);
NN_REGISTER_OPERATION(FLOOR, "FLOOR", elementwise::validateFloor, elementwise::prepareFloor,
elementwise::executeFloor);
NN_REGISTER_OPERATION(LOG, "LOG", elementwise::validate, elementwise::prepare,
elementwise::executeLog);
NN_REGISTER_OPERATION(RSQRT, "RSQRT", elementwise::validate, elementwise::prepare,
elementwise::executeRsqrt);
NN_REGISTER_OPERATION(SIN, "SIN", elementwise::validate, elementwise::prepare,
elementwise::executeSin);
NN_REGISTER_OPERATION(SQRT, "SQRT", elementwise::validate, elementwise::prepare,
elementwise::executeSqrt);
} // namespace nn
} // namespace android
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