mirror of
https://github.com/openharmony/neural_network_runtime.git
synced 2026-07-20 23:57:10 -04:00
yangyongjie
221 lines
8.1 KiB
C++
221 lines
8.1 KiB
C++
/*
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* Copyright (c) 2022 Huawei Device Co., Ltd.
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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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#include "pooling_builder.h"
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#include "frameworks/native/transform.h"
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#include "frameworks/native/validation.h"
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namespace OHOS {
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namespace NeuralNetworkRuntime {
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namespace Ops {
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static const int INPUT_NUM = 1;
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static const int OUTPUT_NUM = 1;
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static const int NUM_ELEMENT_PAD_MODE = 1;
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static const int NUM_ELEMENT_PAD_LIST = 4;
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static const int ACTIVATION_LENGTH = 1;
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OH_NN_ReturnCode PoolingBuilder::PoolingBuild(const std::vector<uint32_t>& paramsIndex,
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const std::vector<uint32_t>& inputsIndex,
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const std::vector<uint32_t>& outputsIndex,
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const std::vector<std::shared_ptr<NNTensor>>& allTensors)
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{
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if (m_isBuild) {
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LOGE("[PoolingBuilder] PoolingBuild failed, operation has been build, cannot build again.");
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return OH_NN_OPERATION_FORBIDDEN;
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}
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// Set input and output
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OH_NN_ReturnCode returnCode = SetInputAndOutput(inputsIndex, outputsIndex, allTensors);
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if (returnCode != OH_NN_SUCCESS) {
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LOGE("[PoolingBuilder] PoolingBuild failed, the SetInputAndOutput failed.");
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return returnCode;
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}
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for (int i : paramsIndex) {
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std::shared_ptr<NNTensor> tensor = allTensors[i];
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switch (tensor->GetType()) {
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case OH_NN_AVG_POOL_KERNEL_SIZE:
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case OH_NN_MAX_POOL_KERNEL_SIZE:
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returnCode = SetKernel(tensor);
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break;
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case OH_NN_AVG_POOL_STRIDE:
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case OH_NN_MAX_POOL_STRIDE:
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returnCode = SetStrides(tensor);
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break;
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case OH_NN_AVG_POOL_PAD_MODE:
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case OH_NN_MAX_POOL_PAD_MODE:
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case OH_NN_MAX_POOL_PAD:
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case OH_NN_AVG_POOL_PAD:
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returnCode = SetPadModeOrPaddings(tensor);
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break;
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case OH_NN_AVG_POOL_ACTIVATION_TYPE:
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case OH_NN_MAX_POOL_ACTIVATION_TYPE:
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returnCode = SetActivation(tensor);
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break;
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default:
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LOGE("[PoolingBuilder] Build failed, param invalid, type = %d.", tensor->GetType());
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return OH_NN_INVALID_PARAMETER;
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}
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if (returnCode != OH_NN_SUCCESS) {
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LOGE("[PoolingBuilder] PoolingBuild failed, passed invalid param.");
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return returnCode;
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}
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}
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// The quantization type of the first output determinies that of the operator.
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SetQuantType(outputsIndex, allTensors);
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return OH_NN_SUCCESS;
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}
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OH_NN_ReturnCode PoolingBuilder::SetInputAndOutput(const std::vector<uint32_t>& inputsIndex,
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const std::vector<uint32_t>& outputsIndex,
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const std::vector<std::shared_ptr<NNTensor>>& allTensors)
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{
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OH_NN_ReturnCode returnCode = CheckIOIndex(inputsIndex, outputsIndex, allTensors, INPUT_NUM, OUTPUT_NUM);
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if (returnCode != OH_NN_SUCCESS) {
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LOGE("[PoolingBuilder] SetInputAndOutput failed, passed invalid input or output index.");
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return returnCode;
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}
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m_inputsIndex = inputsIndex;
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m_outputsIndex = outputsIndex;
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return OH_NN_SUCCESS;
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}
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OH_NN_ReturnCode PoolingBuilder::SetKernel(std::shared_ptr<NNTensor> tensor)
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{
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tensor->IdentifyOpParameter();
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// Set kernelSize
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if (tensor->GetDataType() != OH_NN_INT64) {
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LOGE("[PoolingBuilder] SetKernel failed, the KernelSize should be type OH_NN_INT64.");
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return OH_NN_INVALID_PARAMETER;
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}
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void* buffer = tensor->GetBuffer();
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if (buffer == nullptr) {
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LOGE("[PoolingBuilder] SetKernel GetBuffer return nullptr");
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return OH_NN_INVALID_PARAMETER;
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}
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const int64_t* pKernelSize = reinterpret_cast<const int64_t*>(buffer);
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int kernelSize = tensor->GetElementCount();
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m_kernelSize.assign(pKernelSize, pKernelSize + kernelSize);
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return OH_NN_SUCCESS;
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}
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OH_NN_ReturnCode PoolingBuilder::SetStrides(std::shared_ptr<NNTensor> tensor)
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{
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tensor->IdentifyOpParameter();
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// Set Strides
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if (tensor->GetDataType() != OH_NN_INT64) {
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LOGE("[PoolingBuilder] SetStrides failed, the Strides should be type OH_NN_INT64.");
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return OH_NN_INVALID_PARAMETER;
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}
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void* buffer = tensor->GetBuffer();
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if (buffer == nullptr) {
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LOGE("[PoolingBuilder] SetStrides GetBuffer return nullptr");
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return OH_NN_INVALID_PARAMETER;
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}
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const int64_t* pStrides = reinterpret_cast<const int64_t*>(buffer);
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int strideslSize = tensor->GetElementCount();
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m_strides.assign(pStrides, pStrides + strideslSize);
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return OH_NN_SUCCESS;
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}
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OH_NN_ReturnCode PoolingBuilder::SetPadModeOrPaddings(std::shared_ptr<NNTensor> tensor)
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{
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tensor->IdentifyOpParameter();
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void* buffer = tensor->GetBuffer();
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if (buffer == nullptr) {
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LOGE("[PoolingBuilder] SetPadModeOrPaddings GetBuffer return nullptr");
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return OH_NN_INVALID_PARAMETER;
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}
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size_t tensorElementCount = tensor->GetElementCount();
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// Set PadMode or PadList
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if (tensorElementCount == NUM_ELEMENT_PAD_MODE) {
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// PadMode
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if (tensor->GetDataType() != OH_NN_INT8) {
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LOGE("[PoolingBuilder] SetPadModeOrPaddings failed, the type of padMode should be OH_NN_INT8.");
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return OH_NN_INVALID_PARAMETER;
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}
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int8_t* pPadMode = static_cast<int8_t*>(buffer);
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if (!OHOS::NeuralNetworkRuntime::Validation::ValidatePadMode(*pPadMode)) {
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LOGE("[PoolingBuilder] SetPadModeOrPaddings failed, invalid pad mode.");
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return OH_NN_INVALID_PARAMETER;
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}
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m_padMode = NNToMS::TransformPadModeValue(*pPadMode);
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} else if (tensorElementCount == NUM_ELEMENT_PAD_LIST) {
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if (tensor->GetDataType() != OH_NN_INT64) {
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LOGE("[PoolingBuilder] SetPadModeOrPaddings failed, the type of padList should be OH_NN_INT64.");
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return OH_NN_INVALID_PARAMETER;
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}
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int64_t* pPad = static_cast<int64_t*>(buffer);
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// PadList
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m_pad.clear();
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for (int i = 0; i < NUM_ELEMENT_PAD_LIST; i++) {
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m_pad.emplace_back(static_cast<int64_t>(pPad[i]));
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}
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} else {
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LOGE("[PoolingBuilder] SetPadModeOrPaddings failed, invalid element size of padMode or padList,"
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"padMode should be single value, and padList should be 4.");
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return OH_NN_INVALID_PARAMETER;
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}
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return OH_NN_SUCCESS;
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}
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OH_NN_ReturnCode PoolingBuilder::SetActivation(std::shared_ptr<NNTensor> tensor)
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{
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tensor->IdentifyOpParameter();
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// Set ActivationType
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if (tensor->GetElementCount() != ACTIVATION_LENGTH) {
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LOGE("[PoolingBuilder] SetActivation failed, the Activation shoule be a scalar");
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return OH_NN_INVALID_PARAMETER;
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}
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if (tensor->GetDataType() != OH_NN_INT8) {
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LOGE("[PoolingBuilder] SetActivation failed, the ActivationType should be type OH_NN_INT8.");
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return OH_NN_INVALID_PARAMETER;
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}
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void* buffer = tensor->GetBuffer();
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if (buffer == nullptr) {
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LOGE("[PoolingBuilder] SetActivation GetBuffer return nullptr");
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return OH_NN_INVALID_PARAMETER;
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}
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int8_t* pFuseData = static_cast<int8_t*>(buffer);
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if (!OHOS::NeuralNetworkRuntime::Validation::ValidateFuseType(static_cast<OH_NN_FuseType>(*pFuseData))) {
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LOGE("[PoolingBuilder] SetActivation failed, activation input is invalid.");
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return OH_NN_INVALID_PARAMETER;
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}
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auto fuseType = (OH_NN_FuseType)(*pFuseData);
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m_activationType = NNToMS::TransfromFusionType(fuseType);
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return OH_NN_SUCCESS;
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}
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} // namespace Ops
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} // namespace NeuralNetworkRuntime
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} // namespace OHOS
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