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130 lines
4.8 KiB
130 lines
4.8 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 "IndexedShapeWrapper.h"
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#include "OperationResolver.h"
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#include "OperationsUtils.h"
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namespace android {
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namespace nn {
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namespace select_op {
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constexpr uint32_t kNumInputs = 3;
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constexpr uint32_t kInputCondition = 0;
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constexpr uint32_t kInputTensor1 = 1;
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constexpr uint32_t kInputTensor2 = 2;
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constexpr uint32_t kNumOutputs = 1;
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constexpr uint32_t kOutputTensor = 0;
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namespace {
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template <typename T>
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bool compute(const bool8* conditionData, const Shape& conditionShape, const T* aData,
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const Shape& aShape, const T* bData, const Shape& bShape, T* outputData,
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const Shape& outputShape) {
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// The code assumes that condition has the same shape as all other tensors.
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// This should be checked during preparation stage.
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uint32_t size = getNumberOfElements(conditionShape);
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for (uint32_t i = 0; i < size; ++i) {
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T a = aData[i];
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T b = bData[i];
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if constexpr (std::is_same_v<T, uint8_t> || std::is_same_v<T, int8_t>) {
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a = requantize<T>(a, aShape, outputShape);
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b = requantize<T>(b, bShape, outputShape);
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}
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outputData[i] = conditionData[i] ? a : b;
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}
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return true;
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}
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template <typename T>
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bool executeTyped(IOperationExecutionContext* context) {
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return compute<T>(
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context->getInputBuffer<bool8>(kInputCondition),
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context->getInputShape(kInputCondition), context->getInputBuffer<T>(kInputTensor1),
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context->getInputShape(kInputTensor1), context->getInputBuffer<T>(kInputTensor2),
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context->getInputShape(kInputTensor2), context->getOutputBuffer<T>(kOutputTensor),
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context->getOutputShape(kOutputTensor));
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}
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} // namespace
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Result<Version> validate(const IOperationValidationContext* context) {
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NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs);
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NN_RET_CHECK_EQ(context->getNumOutputs(), kNumOutputs);
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OperandType inputType = context->getInputType(kInputTensor1);
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NN_RET_CHECK(inputType == OperandType::TENSOR_FLOAT16 ||
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inputType == OperandType::TENSOR_FLOAT32 ||
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inputType == OperandType::TENSOR_INT32 ||
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inputType == OperandType::TENSOR_QUANT8_ASYMM ||
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inputType == OperandType::TENSOR_QUANT8_ASYMM_SIGNED)
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<< "Unsupported input operand type for select op: " << inputType;
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NN_RET_CHECK(validateInputTypes(context, {OperandType::TENSOR_BOOL8, inputType, inputType}));
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NN_RET_CHECK(validateOutputTypes(context, {inputType}));
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return Version::ANDROID_Q;
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}
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bool prepare(IOperationExecutionContext* context) {
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Shape inputCondition = context->getInputShape(kInputCondition);
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Shape input1 = context->getInputShape(kInputTensor1);
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if (inputCondition.dimensions.size() != input1.dimensions.size()) {
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LOG(ERROR) << "Condition and input tensor dimensions are not equal";
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return false;
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}
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for (int i = 0; i < inputCondition.dimensions.size(); ++i) {
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if (inputCondition.dimensions[i] != input1.dimensions[i]) {
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LOG(ERROR) << "Condition and input tensor dimensions are not equal";
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return false;
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}
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}
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Shape input2 = context->getInputShape(kInputTensor2);
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NN_RET_CHECK(SameShape(input1, input2));
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Shape output = context->getOutputShape(kOutputTensor);
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NN_RET_CHECK(SetShape(input1, &output));
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return context->setOutputShape(kOutputTensor, output);
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}
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bool execute(IOperationExecutionContext* context) {
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switch (context->getInputType(kInputTensor1)) {
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case OperandType::TENSOR_FLOAT16:
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return executeTyped<_Float16>(context);
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case OperandType::TENSOR_FLOAT32:
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return executeTyped<float>(context);
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case OperandType::TENSOR_INT32:
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return executeTyped<int32_t>(context);
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case OperandType::TENSOR_QUANT8_ASYMM:
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return executeTyped<uint8_t>(context);
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case OperandType::TENSOR_QUANT8_ASYMM_SIGNED:
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return executeTyped<int8_t>(context);
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default:
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NN_RET_CHECK_FAIL() << "Unsupported tensor type for SELECT op.";
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}
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}
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} // namespace select_op
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NN_REGISTER_OPERATION(SELECT, "SELECT", select_op::validate, select_op::prepare,
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select_op::execute);
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} // namespace nn
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} // namespace android
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