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Running
on
Zero
Running
on
Zero
File size: 1,502 Bytes
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# ------------------------------------------------------------------------
# Copyright (c) 2023-present, BAAI. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ------------------------------------------------------------------------
# pyre-unsafe
"""Drop regularization layers."""
from torch import nn
class DropPathV(nn.Module):
"""Set examples to zero randomly."""
def __init__(self, p=0.1, inplace=False):
super(DropPathV, self).__init__()
self.p = p
self.inplace = inplace
def forward(self, input):
if not self.training or self.p <= 0:
return input
keep_p = 1 - self.p
shape = (input.shape[0],) + (1,) * (input.dim() - 1)
scale = input.new_empty(shape).bernoulli_(keep_p).div_(keep_p)
return input.mul_(scale) if self.inplace else input.mul(scale)
def extra_repr(self):
inplace_str = ", inplace" if self.inplace else ""
return "p={}{}".format(self.p, inplace_str)
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