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# Owner(s): ["module: fx"]
from __future__ import annotations # type: ignore[attr-defined]
import torch
import typing
from torch.fx import symbolic_trace
class A:
def __call__(self, x: torch.Tensor):
return torch.add(x, x)
# No forward references
class M1(torch.nn.Module):
def forward(self, x: torch.Tensor, a: A) -> torch.Tensor:
return a(x)
# Forward references
class M2(torch.nn.Module):
def forward(self, x: 'torch.Tensor', a: 'A') -> 'torch.Tensor':
return a(x)
# Non-torch annotation with no internal forward references
class M3(torch.nn.Module):
def forward(self, x: typing.List[torch.Tensor], a: A) -> torch.Tensor:
return a(x[0])
# Non-torch annotation with internal forward references
class M4(torch.nn.Module):
def forward(self, x: typing.List['torch.Tensor'], a: A) -> 'torch.Tensor':
return a(x[0])
x = torch.rand(2, 3)
ref = torch.add(x, x)
traced1 = symbolic_trace(M1())
res1 = traced1(x, A())
assert torch.all(torch.eq(ref, res1))
traced2 = symbolic_trace(M2())
res2 = traced2(x, A())
assert torch.all(torch.eq(ref, res2))
traced3 = symbolic_trace(M3())
res3 = traced3([x], A())
assert torch.all(torch.eq(ref, res3))
traced4 = symbolic_trace(M4())
res4 = traced4([x], A())
assert torch.all(torch.eq(ref, res4))
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