aljaz/DALLE2-pytorch
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makes more sense for blur augmentation to happen before the upsampling

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Phil Wang
2022-04-22 11:10:36 -07:00
parent 2c6c91829d
commit 7f338319fd
2 changed files with 3 additions and 3 deletions
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4
dalle2_pytorch/dalle2_pytorch.py
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@@ -1075,14 +1075,14 @@ class LowresConditioner(nn.Module):
if self.training and self.downsample_first and exists(downsample_image_size): if self.training and self.downsample_first and exists(downsample_image_size):
cond_fmap = resize_image_to(cond_fmap, target_image_size, mode = self.cond_upsample_mode) cond_fmap = resize_image_to(cond_fmap, target_image_size, mode = self.cond_upsample_mode)
cond_fmap = resize_image_to(cond_fmap, target_image_size, mode = self.cond_upsample_mode)
if self.training: if self.training:
# when training, blur the low resolution conditional image # when training, blur the low resolution conditional image
blur_sigma = default(blur_sigma, self.blur_sigma) blur_sigma = default(blur_sigma, self.blur_sigma)
blur_kernel_size = default(blur_kernel_size, self.blur_kernel_size) blur_kernel_size = default(blur_kernel_size, self.blur_kernel_size)
cond_fmap = gaussian_blur2d(cond_fmap, cast_tuple(blur_kernel_size, 2), cast_tuple(blur_sigma, 2)) cond_fmap = gaussian_blur2d(cond_fmap, cast_tuple(blur_kernel_size, 2), cast_tuple(blur_sigma, 2))
cond_fmap = resize_image_to(cond_fmap, target_image_size, mode = self.cond_upsample_mode)
return cond_fmap return cond_fmap
class Decoder(nn.Module): class Decoder(nn.Module):

2
setup.py
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@@ -10,7 +10,7 @@ setup(
'dream = dalle2_pytorch.cli:dream' 'dream = dalle2_pytorch.cli:dream'
], ],
}, },
version = '0.0.32', version = '0.0.33',
license='MIT', license='MIT',
description = 'DALL-E 2', description = 'DALL-E 2',
author = 'Phil Wang', author = 'Phil Wang',