mirror of https://github.com/alibaba/MNN.git
				
				
				
			
		
			
				
	
	
		
			42 lines
		
	
	
		
			1.4 KiB
		
	
	
	
		
			C++
		
	
	
	
			
		
		
	
	
			42 lines
		
	
	
		
			1.4 KiB
		
	
	
	
		
			C++
		
	
	
	
| //
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| //  ShapePadding.cpp
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| //  MNN
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| //
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| //  Created by MNN on 2019/6/24.
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| //  Copyright © 2018, Alibaba Group Holding Limited
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| //
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| 
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| #include "core/SizeComputer.hpp"
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| #include "core/TensorUtils.hpp"
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| 
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| namespace MNN {
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| class PaddingComputer : public SizeComputer {
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|     virtual bool onComputeSize(const MNN::Op* op, const std::vector<Tensor*>& inputs,
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|                                const std::vector<Tensor*>& outputs) const override {
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|         if ((2 != inputs.size() && 3 != inputs.size()) || 1 != outputs.size()) {
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|             MNN_ERROR("Padding inputs or outputs number error: %d -> %d\n", (int)inputs.size(), (int)outputs.size());
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|             return false;
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|         }
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|         auto input            = inputs[0];
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|         auto paddings         = inputs[1];
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|         auto output           = outputs[0];
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|         output->buffer().type = input->buffer().type;
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|         TensorUtils::copyShape(input, output, true);
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| 
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|         auto size = paddings->elementSize();
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|         if (size < output->dimensions() * 2) {
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|             MNN_ERROR("Padding blob size not match output's dimension\n");
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|             return false;
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|         }
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|         auto paddingPtr = paddings->host<int32_t>();
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|         auto dimensions = input->dimensions();
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|         for (int i = 0; i < dimensions; ++i) {
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|             output->setLength(i, input->length(i) + paddingPtr[2 * i] + paddingPtr[2 * i + 1]);
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|         }
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|         return true;
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|     }
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| };
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| 
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| REGISTER_SHAPE_INPUTS(PaddingComputer, OpType_Padding, {1});
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| } // namespace MNN
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