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