(self, node: torch.fx.Node)
| 85 | return super().serialize_operator(target) |
| 86 | |
| 87 | def handle_call_function(self, node: torch.fx.Node) -> None: |
| 88 | assert node.op == "call_function" |
| 89 | |
| 90 | if node.target is memory.alloc: |
| 91 | ex_node = schema.Node( |
| 92 | name=node.name, |
| 93 | target="memory.alloc", |
| 94 | inputs=self.serialize_alloc_inputs(node.args), |
| 95 | outputs=self.serialize_arbitrary_outputs(node), |
| 96 | metadata=self.serialize_metadata(node), |
| 97 | ) |
| 98 | self.graph_state.nodes.append(ex_node) |
| 99 | return |
| 100 | elif isinstance(node.target, EdgeOpOverload): |
| 101 | assert node.target._op is not None |
| 102 | ex_node = schema.Node( |
| 103 | name=node.name, |
| 104 | target=self.serialize_operator(node.target), |
| 105 | # pyre-ignore Undefined attribute [16]: Item `typing.Callable` of |
| 106 | # `typing.Union[typing.Callable[..., typing.Any], str]` has no attribute `_op`. |
| 107 | inputs=self.serialize_inputs(node.target._op, node.args, node.kwargs), |
| 108 | outputs=self.serialize_outputs(node), |
| 109 | # TODO: create a new tensor_values here, meta might have faketensor info |
| 110 | metadata=self.serialize_metadata(node), |
| 111 | ) |
| 112 | self.graph_state.nodes.append(ex_node) |
| 113 | return |
| 114 | elif node.target is delegate.executorch_call_delegate: |
| 115 | ex_node = schema.Node( |
| 116 | name=node.name, |
| 117 | target=self.serialize_operator(node.target), |
| 118 | inputs=self.serialize_call_delegate_inputs(node.args), |
| 119 | outputs=self.serialize_arbitrary_outputs(node), |
| 120 | metadata=self.serialize_metadata(node), |
| 121 | ) |
| 122 | self.graph_state.nodes.append(ex_node) |
| 123 | return |
| 124 | |
| 125 | super().handle_call_function(node) |
| 126 | |
| 127 | def serialize_outputs(self, node: torch.fx.Node) -> List[schema.Argument]: |
| 128 | if isinstance(node.target, EdgeOpOverload): |
nothing calls this directly
no test coverage detected