import torch
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from typeguard import check_argument_types
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class ForwardAdaptor(torch.nn.Module):
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"""Wrapped module to parallelize specified method
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torch.nn.DataParallel parallelizes only "forward()"
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and, maybe, the method having the other name can't be applied
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except for wrapping the module just like this class.
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Examples:
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>>> class A(torch.nn.Module):
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... def foo(self, x):
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... ...
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>>> model = A()
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>>> model = ForwardAdaptor(model, "foo")
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>>> model = torch.nn.DataParallel(model, device_ids=[0, 1])
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>>> x = torch.randn(2, 10)
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>>> model(x)
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"""
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def __init__(self, module: torch.nn.Module, name: str):
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assert check_argument_types()
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super().__init__()
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self.module = module
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self.name = name
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if not hasattr(module, name):
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raise ValueError(f"{module} doesn't have {name}")
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def forward(self, *args, **kwargs):
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func = getattr(self.module, self.name)
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return func(*args, **kwargs)
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