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import torch |
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__all__ = ['Dropout'] |
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class Dropout(torch.nn.Dropout): |
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r"""This is the quantized equivalent of :class:`~torch.nn.Dropout`. |
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And this is a placeholder to enable models where fp32 tensors |
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had dropout to work with quantized tensors in train and eval mode. |
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Args: |
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p: probability of an element to be zeroed |
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inplace: can optionally do the operation in-place. Default: ``False`` |
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""" |
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def forward(self, input): |
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return input |
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def _get_name(self): |
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return 'QuantizedDropout' |
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@classmethod |
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def from_float(cls, mod): |
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return cls(mod.p, mod.inplace) |
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@classmethod |
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def from_reference(cls, mod, scale, zero_point): |
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return cls(mod.p, mod.inplace) |
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