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18 lines
716 B
18 lines
716 B
1 year ago
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import torch
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class Linear(torch.nn.Module):
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def __init__(self, in_features: int, out_features: int, bias: bool = True,
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device=None, dtype=None) -> None:
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factory_kwargs = {'device': device, 'dtype': dtype}
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super().__init__()
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self.in_features = in_features
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self.out_features = out_features
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self.weight = torch.nn.Parameter(torch.empty((out_features, in_features), **factory_kwargs))
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if bias:
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self.bias = torch.nn.Parameter(torch.empty(out_features, **factory_kwargs))
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else:
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self.register_parameter('bias', None)
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def forward(self, input):
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return torch.nn.functional.linear(input, self.weight, self.bias)
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