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[NFC] polish colossalai/nn/layer/vanilla/layers.py code style (#1295)

pull/1298/head
XYE 2022-07-13 11:33:16 +08:00 committed by Frank Lee
parent 1000a41fd5
commit e83b2ce853
1 changed files with 3 additions and 3 deletions
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6
colossalai/nn/layer/vanilla/layers.py
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@ -29,9 +29,9 @@ def drop_path(x, drop_prob: float = 0., training: bool = False):
if drop_prob == 0. or not training:
return x
keep_prob = 1 - drop_prob
shape = (x.shape[0], ) + (1, ) * (x.ndim - 1) # work with diff dim tensors, not just 2D ConvNets
shape = (x.shape[0],) + (1,) * (x.ndim - 1) # work with diff dim tensors, not just 2D ConvNets
random_tensor = keep_prob + torch.rand(shape, dtype=x.dtype, device=x.device)
random_tensor.floor_() # binarize
random_tensor.floor_() # binarize
output = x.div(keep_prob) * random_tensor
return output
@ -190,7 +190,7 @@ class VanillaPatchEmbedding(nn.Module):
f"Input image size ({H}*{W}) doesn't match model ({self.img_size[0]}*{self.img_size[1]})."
output = F.conv2d(input_, self.weight, self.bias, stride=self.patch_size)
if self.flatten:
output = output.flatten(2).transpose(1, 2) # BCHW -> BNC
output = output.flatten(2).transpose(1, 2) # BCHW -> BNC
cls_token = self.cls_token.expand(output.shape[0], -1, -1)
output = torch.cat((cls_token, output), dim=1)