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author | AUTOMATIC1111 <16777216c@gmail.com> | 2023-05-10 18:24:18 +0000 |
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committer | GitHub <noreply@github.com> | 2023-05-10 18:24:18 +0000 |
commit | 5abecea34cd98537f006c5e9a197acd1fe9db023 (patch) | |
tree | 98248bc21aa4ad9715205f0a65a654532c6cfcc0 /modules/codeformer/vqgan_arch.py | |
parent | f5ea1e9d928e0d45b3ebcd8ddd1cacbc6a96e184 (diff) | |
parent | 3ec7b705c78b7aca9569c92a419837352c7a4ec6 (diff) | |
download | stable-diffusion-webui-gfx803-5abecea34cd98537f006c5e9a197acd1fe9db023.tar.gz stable-diffusion-webui-gfx803-5abecea34cd98537f006c5e9a197acd1fe9db023.tar.bz2 stable-diffusion-webui-gfx803-5abecea34cd98537f006c5e9a197acd1fe9db023.zip |
Merge pull request #10259 from AUTOMATIC1111/ruff
Ruff
Diffstat (limited to 'modules/codeformer/vqgan_arch.py')
-rw-r--r-- | modules/codeformer/vqgan_arch.py | 6 |
1 files changed, 2 insertions, 4 deletions
diff --git a/modules/codeformer/vqgan_arch.py b/modules/codeformer/vqgan_arch.py index e7293683..b24a0394 100644 --- a/modules/codeformer/vqgan_arch.py +++ b/modules/codeformer/vqgan_arch.py @@ -5,11 +5,9 @@ VQGAN code, adapted from the original created by the Unleashing Transformers aut https://github.com/samb-t/unleashing-transformers/blob/master/models/vqgan.py ''' -import numpy as np import torch import torch.nn as nn import torch.nn.functional as F -import copy from basicsr.utils import get_root_logger from basicsr.utils.registry import ARCH_REGISTRY @@ -328,7 +326,7 @@ class Generator(nn.Module): @ARCH_REGISTRY.register() class VQAutoEncoder(nn.Module): - def __init__(self, img_size, nf, ch_mult, quantizer="nearest", res_blocks=2, attn_resolutions=[16], codebook_size=1024, emb_dim=256, + def __init__(self, img_size, nf, ch_mult, quantizer="nearest", res_blocks=2, attn_resolutions=None, codebook_size=1024, emb_dim=256, beta=0.25, gumbel_straight_through=False, gumbel_kl_weight=1e-8, model_path=None): super().__init__() logger = get_root_logger() @@ -339,7 +337,7 @@ class VQAutoEncoder(nn.Module): self.embed_dim = emb_dim self.ch_mult = ch_mult self.resolution = img_size - self.attn_resolutions = attn_resolutions + self.attn_resolutions = attn_resolutions or [16] self.quantizer_type = quantizer self.encoder = Encoder( self.in_channels, |