mirror of https://github.com/alibaba/MNN.git
75 lines
3.4 KiB
C++
75 lines
3.4 KiB
C++
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// CoreMLPool.cpp
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// MNN
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//
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// Created by MNN on 2021/03/25.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#include "CoreMLPool.hpp"
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namespace MNN {
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CoreMLPool::CoreMLPool(MNN::Backend *b, const MNN::Op *op, const std::vector<Tensor *> &inputs, const std::vector<MNN::Tensor *> &outputs) : CoreMLCommonExecution(b, op) {
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initLayer();
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}
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ErrorCode CoreMLPool::onResize(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
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MNN_ASSERT(inputs.size() == 1 && outputs.size() == 1);
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auto pool = mOp->main_as_Pool();
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auto strideX = pool->strideX();
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auto strideY = pool->strideY();
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auto kernelX = pool->kernelX();
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auto kernelY = pool->kernelY();
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auto padMod = pool->padType();
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auto global = pool->isGlobal();
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mLayer_->pooling = mCoreMLBackend->create<CoreML__Specification__PoolingLayerParams>();
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mLayer_->layer_case = CORE_ML__SPECIFICATION__NEURAL_NETWORK_LAYER__LAYER_POOLING;
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core_ml__specification__pooling_layer_params__init(mLayer_->pooling);
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mLayer_->pooling->globalpooling = global;
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mLayer_->pooling->n_stride = 2;
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mLayer_->pooling->stride = mCoreMLBackend->create<uint64_t>(mLayer_->pooling->n_stride);
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mLayer_->pooling->stride[0] = strideY;
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mLayer_->pooling->stride[1] = strideX;
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mLayer_->pooling->n_kernelsize = 2;
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mLayer_->pooling->kernelsize = mCoreMLBackend->create<uint64_t>(mLayer_->pooling->n_kernelsize);
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mLayer_->pooling->kernelsize[0] = kernelY;
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mLayer_->pooling->kernelsize[1] = kernelX;
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switch (padMod) {
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case PoolPadType_SAME:
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mLayer_->pooling->pooling_padding_type_case = CORE_ML__SPECIFICATION__POOLING_LAYER_PARAMS__POOLING_PADDING_TYPE_SAME;
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mLayer_->pooling->same = mCoreMLBackend->create<CoreML__Specification__SamePadding>();
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core_ml__specification__same_padding__init(mLayer_->pooling->same);
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break;
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case PoolPadType_VALID:
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mLayer_->pooling->pooling_padding_type_case = CORE_ML__SPECIFICATION__POOLING_LAYER_PARAMS__POOLING_PADDING_TYPE_VALID;
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mLayer_->pooling->valid = mCoreMLBackend->create<CoreML__Specification__ValidPadding>();
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core_ml__specification__valid_padding__init(mLayer_->pooling->valid);
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break;
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case PoolPadType_CAFFE:
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// TODO: deal caffe pad mode
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mLayer_->pooling->pooling_padding_type_case = CORE_ML__SPECIFICATION__POOLING_LAYER_PARAMS__POOLING_PADDING_TYPE_INCLUDE_LAST_PIXEL;
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mLayer_->pooling->includelastpixel = mCoreMLBackend->create<CoreML__Specification__PoolingLayerParams__ValidCompletePadding>();
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core_ml__specification__pooling_layer_params__valid_complete_padding__init(mLayer_->pooling->includelastpixel);
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break;
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default:
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break;
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}
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if (pool->type() == PoolType_AVEPOOL) {
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mLayer_->pooling->type = CORE_ML__SPECIFICATION__POOLING_LAYER_PARAMS__POOLING_TYPE__AVERAGE;
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mLayer_->pooling->avgpoolexcludepadding = true;
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} else {
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mLayer_->pooling->type = CORE_ML__SPECIFICATION__POOLING_LAYER_PARAMS__POOLING_TYPE__MAX;
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}
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setLayerInputsAndOutputs(mLayer_, {mCoreMLBackend->getTensorName(inputs[0])}, {mCoreMLBackend->getTensorName(outputs[0])});
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mCoreMLBackend->addLayer(mLayer_);
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return NO_ERROR;
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}
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CoreMLCreatorRegister<TypedCreator<CoreMLPool>> __pool_op(OpType_Pooling);
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} // namespace MNN
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