mirror of https://github.com/alibaba/MNN.git
				
				
				
			
		
			
				
	
	
		
			112 lines
		
	
	
		
			4.4 KiB
		
	
	
	
		
			C++
		
	
	
	
			
		
		
	
	
			112 lines
		
	
	
		
			4.4 KiB
		
	
	
	
		
			C++
		
	
	
	
| //
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| //  CPUReshape.cpp
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| //  MNN
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| //
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| //  Created by MNN on 2018/07/18.
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| //  Copyright © 2018, Alibaba Group Holding Limited
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| //
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| 
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| #include "backend/cpu/CPUReshape.hpp"
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| #include "backend/cpu/CPUBackend.hpp"
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| #include "backend/cpu/compute/CommonOptFunction.h"
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| #include "core/Macro.h"
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| #include "core/TensorUtils.hpp"
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| 
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| namespace MNN {
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| 
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| CPUReshape::CPUReshape(Backend *b, MNN_DATA_FORMAT midFormat) : MNN::Execution(b), mStorage(2) {
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|     mMidFormat = midFormat;
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| }
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| 
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| ErrorCode CPUReshape::onResize(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
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|     MNN_ASSERT(1 == inputs.size() || 2 == inputs.size());
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|     MNN_ASSERT(1 == outputs.size());
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| 
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|     auto input    = inputs[0];
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|     auto output   = outputs[0];
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| 
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|     if (TensorUtils::getDescribe(input)->dimensionFormat != MNN_DATA_FORMAT_NC4HW4) {
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|         return NO_ERROR;
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|     }
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| 
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|     int totalSize = 1;
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|     for (int i = 0; i < input->buffer().dimensions; ++i) {
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|         totalSize *= input->buffer().dim[i].extent;
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|     }
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|     TensorUtils::getDescribe(&mStorage)->dimensionFormat = MNN_DATA_FORMAT_NCHW;
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|     mStorage.buffer().dim[0].extent = 1;
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|     mStorage.buffer().dim[1].extent = totalSize;
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|     mStorage.buffer().dimensions    = 2;
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|     mStorage.buffer().type          = input->getType();
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|     backend()->onAcquireBuffer(&mStorage, Backend::DYNAMIC);
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|     backend()->onReleaseBuffer(&mStorage, Backend::DYNAMIC);
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| 
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|     auto convertTensorMeta = [&](const Tensor* tensor, Tensor* wrapTensor) {
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|         wrapTensor->buffer().host       = mStorage.buffer().host;
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|         wrapTensor->buffer().dimensions = tensor->dimensions();
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|         wrapTensor->buffer().type       = tensor->buffer().type;
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|         TensorUtils::getDescribe(wrapTensor)->dimensionFormat = mMidFormat;
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|         auto tensorFormat      = TensorUtils::getDescribe(tensor)->dimensionFormat;
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|         bool originCaffeFormat = (tensorFormat == MNN_DATA_FORMAT_NCHW || tensorFormat == MNN_DATA_FORMAT_NC4HW4);
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|         bool wrapCaffeFormat   = (mMidFormat == MNN_DATA_FORMAT_NCHW || mMidFormat == MNN_DATA_FORMAT_NC4HW4);
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|         bool originTfFormat    = (tensorFormat == MNN_DATA_FORMAT_NHWC || tensorFormat == MNN_DATA_FORMAT_NHWC4);
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|         bool wrapTfFormat      = (mMidFormat == MNN_DATA_FORMAT_NHWC || mMidFormat == MNN_DATA_FORMAT_NHWC4);
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|         if ((originCaffeFormat && wrapCaffeFormat) || (originTfFormat && wrapTfFormat)) {
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|             TensorUtils::copyShape(tensor, wrapTensor);
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|         } else if (originCaffeFormat && wrapTfFormat) {
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|             for (int i = 1; i < wrapTensor->dimensions() - 1; ++i) {
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|                 wrapTensor->setLength(i, tensor->length(i + 1));
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|             }
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|             wrapTensor->setLength(0, tensor->length(0));
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|             wrapTensor->setLength(wrapTensor->dimensions() - 1, tensor->length(1));
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|         } else if (originTfFormat && wrapCaffeFormat) {
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|             for (int i = 2; i < wrapTensor->dimensions(); ++i) {
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|                 wrapTensor->setLength(i, tensor->length(i - 1));
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|             }
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|             wrapTensor->setLength(0, tensor->length(0));
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|             wrapTensor->setLength(1, tensor->length(tensor->dimensions() - 1));
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|         } else {
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|             // will not reach here
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|             MNN_ASSERT(false);
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|         }
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|         TensorUtils::setLinearLayout(wrapTensor);
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|     };
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| 
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|     convertTensorMeta(input, &mWrapTensorForInput);
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|     convertTensorMeta(output, &mWrapTensorForOutput);
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| 
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|     return NO_ERROR;
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| }
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| 
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| ErrorCode CPUReshape::onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
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|     MNN_ASSERT(1 == inputs.size() || 2 == inputs.size());
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|     MNN_ASSERT(1 == outputs.size());
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|     if (TensorUtils::getDescribe(inputs[0])->dimensionFormat != MNN_DATA_FORMAT_NC4HW4) {
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|         auto outputPtr = outputs[0]->host<uint8_t>();
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|         auto inputPtr = inputs[0]->host<uint8_t>();
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|         auto totalSize = inputs[0]->size();
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|         ::memcpy(outputPtr, inputPtr, totalSize);
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|         return NO_ERROR;
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|     }
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| 
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|     auto input  = inputs[0];
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|     auto output = outputs[0];
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| 
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|     backend()->onCopyBuffer(input, &mWrapTensorForInput);
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|     backend()->onCopyBuffer(&mWrapTensorForOutput, output);
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| 
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|     return NO_ERROR;
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| }
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| 
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| class CPUReshapeCreator : public CPUBackend::Creator {
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| public:
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|     virtual Execution *onCreate(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs,
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|                                 const MNN::Op *op, Backend *backend) const override {
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|         return new CPUReshape(backend, op->main_as_Reshape()->dimType());
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|     }
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| };
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| 
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| REGISTER_CPU_OP_CREATOR(CPUReshapeCreator, OpType_Reshape);
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| 
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| } // namespace MNN
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