add files

funasr_local/torch_utils/forward_adaptor.py

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