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stable-diffusion-finetune
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do not fix num_heads to one in legacy mode

This commit is contained in:
rromb 2022-04-15 17:24:11 +02:00
parent 8381e5e557
commit 71ebe40791
1 changed files with 4 additions and 4 deletions
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8
ldm/modules/diffusionmodules/openaimodel.py
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@ -464,7 +464,7 @@ class UNetModel(nn.Module):
use_spatial_transformer=False, # custom transformer support
transformer_depth=1, # custom transformer support
context_dim=None, # custom transformer support
n_embed=None, # custom support for prediction of discrete ids into codebook of first stage vq model
n_embed=None, # custom support for prediction of discrete ids into codebook of first stage vq model
legacy=True,
):
super().__init__()
@ -545,7 +545,7 @@ class UNetModel(nn.Module):
num_heads = ch // num_head_channels
dim_head = num_head_channels
if legacy:
num_heads = 1
#num_heads = 1
dim_head = ch // num_heads if use_spatial_transformer else num_head_channels
layers.append(
AttentionBlock(
@ -592,7 +592,7 @@ class UNetModel(nn.Module):
num_heads = ch // num_head_channels
dim_head = num_head_channels
if legacy:
num_heads = 1
#num_heads = 1
dim_head = ch // num_heads if use_spatial_transformer else num_head_channels
self.middle_block = TimestepEmbedSequential(
ResBlock(
@ -646,7 +646,7 @@ class UNetModel(nn.Module):
num_heads = ch // num_head_channels
dim_head = num_head_channels
if legacy:
num_heads = 1
#num_heads = 1
dim_head = ch // num_heads if use_spatial_transformer else num_head_channels
layers.append(
AttentionBlock(