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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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