1# Fusion Pattern Format 2The patterns are we matching against is float modules types, functional operators and pytorch operators in reverse order: 3``` 4operator = module_type | functional | torch op | native op | MatchAllNode 5Pattern = (operator, Pattern, Pattern, ...) | operator 6``` 7where the first item for Pattern is the operator we want to match, and the rest are the patterns for the arguments of the operator. 8For example, pattern (nn.ReLU, (operator.add, MatchAllNode, (nn.BatchNorm2d, nn.Conv2d))) would match the following graph: 9``` 10tensor_1 tensor_2 11 | | 12 *(MatchAllNode) nn.Conv2d 13 | | 14 | nn.BatchNorm2d 15 \ / 16 -- operator.add -- 17 | 18 nn.ReLU 19``` 20 21we’ll match the last node as the anchor point of the match, and we can retrieve the whole graph by tracing back from the node, e.g. in the example above, we matched nn.ReLU node, then node.args[0] is the operator.add node. 22