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			46 lines
		
	
	
		
			1.4 KiB
		
	
	
	
		
			C++
		
	
	
	
		
		
			
		
	
	
			46 lines
		
	
	
		
			1.4 KiB
		
	
	
	
		
			C++
		
	
	
	
|  | //
 | ||
|  | //  ShapeSetDiff1D.cpp
 | ||
|  | //  MNN
 | ||
|  | //
 | ||
|  | //  Created by MNN on 2021/06/24.
 | ||
|  | //  Copyright © 2018, Alibaba Group Holding Limited
 | ||
|  | //
 | ||
|  | 
 | ||
|  | #include <unordered_set>
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|  | #include "shape/SizeComputer.hpp"
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|  | #include "core/Macro.h"
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|  | 
 | ||
|  | namespace MNN { | ||
|  | 
 | ||
|  | class ShapeUnique : public SizeComputer { | ||
|  |     virtual bool onComputeSize(const MNN::Op* op, const std::vector<Tensor*>& inputs, | ||
|  |                                const std::vector<Tensor*>& outputs) const override { | ||
|  |         MNN_ASSERT(1 == inputs.size()); | ||
|  |         if (inputs[0]->getType().code != halide_type_int) { | ||
|  |             return false; | ||
|  |         } | ||
|  |         auto& ib = inputs[0]->buffer(); | ||
|  |         auto& ob = outputs[0]->buffer(); | ||
|  |         ob.dimensions = 1; | ||
|  |         TensorUtils::getDescribe(outputs[0])->dimensionFormat = TensorUtils::getDescribe(inputs[0])->dimensionFormat; | ||
|  |         ob.type = ib.type; | ||
|  |         if (inputs[0]->host<int32_t>() == nullptr) { | ||
|  |             return false; | ||
|  |         } | ||
|  |         std::unordered_set<int> values; | ||
|  |         auto eleSize = inputs[0]->elementSize(); | ||
|  |         for (int i = 0; i < eleSize; i++) { | ||
|  |             values.insert(inputs[0]->host<int32_t>()[i]); | ||
|  |         } | ||
|  |         ob.dim[0].extent = values.size(); | ||
|  |         if (outputs.size() > 1) { | ||
|  |             TensorUtils::copyShape(outputs[0], outputs[1], true); | ||
|  |             outputs[1]->buffer().type = halide_type_of<int>(); | ||
|  |         } | ||
|  |         return true; | ||
|  |     } | ||
|  | }; | ||
|  | 
 | ||
|  | REGISTER_SHAPE_INPUTS(ShapeUnique, OpType_Unique, std::vector<int>({0})); | ||
|  | } // namespace MNN
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