mirror of https://github.com/alibaba/MNN.git
				
				
				
			
		
			
				
	
	
		
			78 lines
		
	
	
		
			2.5 KiB
		
	
	
	
		
			C++
		
	
	
	
			
		
		
	
	
			78 lines
		
	
	
		
			2.5 KiB
		
	
	
	
		
			C++
		
	
	
	
| //
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| //  CPUOneHot.cpp
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| //  MNN
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| //
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| //  Created by MNN on 2019/11/29.
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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/CPUOneHot.hpp"
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| #include "backend/cpu/CPUBackend.hpp"
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| 
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| namespace MNN {
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| 
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| template <typename T>
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| void OneHotImpl(int depth, int outerSize, int innerSize, const int* indices, const Tensor* onValueTensor,
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|                 const Tensor* offValueTensor, Tensor* outputTensor) {
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|     const T onValue  = onValueTensor->host<T>()[0];
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|     const T offValue = offValueTensor->host<T>()[0];
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|     T* outputPtr     = outputTensor->host<T>();
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| 
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|     for (int i = 0; i < outerSize; ++i) {
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|         for (int j = 0; j < depth; ++j) {
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|             for (int k = 0; k < innerSize; ++k) {
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|                 auto index = indices[i * innerSize + k];
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|                 if (index == j) {
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|                     *outputPtr = onValue;
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|                 } else {
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|                     *outputPtr = offValue;
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|                 }
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|                 outputPtr++;
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|             }
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|         }
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|     }
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| }
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| 
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| ErrorCode CPUOneHot::onExecute(const std::vector<Tensor*>& inputs, const std::vector<Tensor*>& outputs) {
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|     auto indices        = inputs[0];
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|     auto depthTensor    = inputs[1];
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|     auto onValueTensor  = inputs[2];
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|     auto offValueTensor = inputs[3];
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| 
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|     int axis = mAxis;
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|     if (axis < 0) {
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|         axis += outputs[0]->dimensions();
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|     }
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|     int outerSize = 1;
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|     for (int i = 0; i < axis; ++i) {
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|         outerSize *= indices->length(i);
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|     }
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|     const int depth       = depthTensor->host<int>()[0];
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|     const int innerSize   = indices->elementSize() / outerSize;
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|     const auto indicesPtr = indices->host<int>();
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| 
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|     auto dataType    = onValueTensor->getType();
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|     MNN_ASSERT(offValueTensor->getType() == dataType);
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| 
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|     if (dataType == halide_type_of<float>()) {
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|         OneHotImpl<float>(depth, outerSize, innerSize, indicesPtr, onValueTensor, offValueTensor, outputs[0]);
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|     } else if (dataType == halide_type_of<int>()) {
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|         OneHotImpl<int>(depth, outerSize, innerSize, indicesPtr, onValueTensor, offValueTensor, outputs[0]);
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|     } else {
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|         return NOT_SUPPORT;
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|     }
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|     return NO_ERROR;
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| }
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| 
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| class CPUOneHotCreator : 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 CPUOneHot(backend, op->main_as_OneHotParam()->axis());
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|     }
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| };
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| 
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| REGISTER_CPU_OP_CREATOR(CPUOneHotCreator, OpType_OneHot);
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| 
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| } // namespace MNN
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