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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 "OperationResolver.h"
#include "OperationsUtils.h"
#include "Utils.h"
namespace android {
namespace nn {
namespace rank_op {
constexpr uint32_t kNumInputs = 1;
constexpr uint32_t kInputTensor = 0;
constexpr uint32_t kNumOutputs = 1;
constexpr uint32_t kOutputScalar = 0;
bool 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 ||
inputType == OperandType::TENSOR_INT32 ||
inputType == OperandType::TENSOR_QUANT8_ASYMM ||
inputType == OperandType::TENSOR_QUANT16_SYMM ||
inputType == OperandType::TENSOR_BOOL8 ||
inputType == OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL ||
inputType == OperandType::TENSOR_QUANT16_ASYMM ||
inputType == OperandType::TENSOR_QUANT8_SYMM ||
inputType == OperandType::TENSOR_QUANT8_ASYMM_SIGNED)
<< "Incorrect input type for a RANK op: " << inputType;
NN_RET_CHECK(validateOutputTypes(context, {OperandType::INT32}));
return validateVersion(context, Version::ANDROID_R);
}
bool prepare(IOperationExecutionContext* context) {
Shape output = context->getOutputShape(kOutputScalar);
return context->setOutputShape(kOutputScalar, output);
}
bool execute(IOperationExecutionContext* context) {
*context->getOutputBuffer<int32_t>(kOutputScalar) =
getNumberOfDimensions(context->getInputShape(kInputTensor));
return true;
}
} // namespace rank_op
NN_REGISTER_OPERATION(RANK, "RANK", rank_op::validate, rank_op::prepare, rank_op::execute);
} // namespace nn
} // namespace android
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