Source code for physicsnemo.nn.module.drop
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from torch import nn
from physicsnemo.nn.functional import drop_path
[docs]
class DropPath(nn.Module):
"""Cut & paste from timm master
Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks).
"""
def __init__(self, drop_prob: float = 0.0, scale_by_keep: bool = True):
super(DropPath, self).__init__()
self.drop_prob = drop_prob
self.scale_by_keep = scale_by_keep
[docs]
def forward(self, x):
return drop_path(x, self.drop_prob, self.training, self.scale_by_keep)