""".detach()方法用于将张量从计算图中分离出来,得到一个新的张量。 在PyTorch中,计算图是用于自动求导的一种机制。当我们对张量进行操作时, PyTorch会自动构建一个计算图,用于跟踪张量之间的依赖关系,并计算梯度。计算图的构建过程会消耗一定的内存和计算资源。 使用.detach()方法可以将张量从计算图中分离出来,得...
deep-learningpytorchattention-mechanismneural-tensor-networkgraph-embeddingnode-embeddingpytorch-implementationgraph-similaritygraph-convolutionpytorch-geometricgnnsimgnn UpdatedApr 18, 2024 Python Add a description, image, and links to thesimgnntopic page so that developers can more easily learn about it. ...
A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019). - GitHub - benedekrozemberczki/SimGNN: A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computatio
The project structure is based on the PyTorch implementation[benedekrozemberczki/SimGNN]. A reference Tensorflow implementation is accessible[here]. Requirements The codebase is implemented in Python 3.6.9. package versions used for development are just below. ...
A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019). - GitHub - kazimierz-256/SimGNN: A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WS