aljaz/DALLE2-pytorch
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default number of resnet blocks per layer in unet to 2 (in imagen it was 3 for base 64x64)

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Phil Wang
2022-05-30 10:06:48 -07:00
parent a0bed30a84
commit b693e0be03
2 changed files with 2 additions and 2 deletions
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2
dalle2_pytorch/dalle2_pytorch.py
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@@ -1347,7 +1347,7 @@ class Unet(nn.Module):
init_dim = None, init_dim = None,
init_conv_kernel_size = 7, init_conv_kernel_size = 7,
resnet_groups = 8, resnet_groups = 8,
num_resnet_blocks = 1, num_resnet_blocks = 2,
init_cross_embed_kernel_sizes = (3, 7, 15), init_cross_embed_kernel_sizes = (3, 7, 15),
cross_embed_downsample = False, cross_embed_downsample = False,
cross_embed_downsample_kernel_sizes = (2, 4), cross_embed_downsample_kernel_sizes = (2, 4),

2
setup.py
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@@ -10,7 +10,7 @@ setup(
'dream = dalle2_pytorch.cli:dream' 'dream = dalle2_pytorch.cli:dream'
], ],
}, },
version = '0.6.0', version = '0.6.1',
license='MIT', license='MIT',
description = 'DALL-E 2', description = 'DALL-E 2',
author = 'Phil Wang', author = 'Phil Wang',