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Remove omegaconf dependency and some ci changes.

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This commit is contained in:
comfyanonymous
2023-03-13 14:49:18 -04:00
parent 80665081e0
commit 54dbfaf2ec
8 changed files with 26 additions and 22 deletions
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5
comfy/ldm/models/diffusion/ddpm.py
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@@ -18,7 +18,6 @@ import itertools
from tqdm import tqdm
from torchvision.utils import make_grid
# from pytorch_lightning.utilities.distributed import rank_zero_only
from omegaconf import ListConfig
from ldm.util import log_txt_as_img, exists, default, ismap, isimage, mean_flat, count_params, instantiate_from_config
from ldm.modules.ema import LitEma
@@ -1124,8 +1123,8 @@ class LatentDiffusion(DDPM):
def get_unconditional_conditioning(self, batch_size, null_label=None):
if null_label is not None:
xc = null_label
if isinstance(xc, ListConfig):
xc = list(xc)
# if isinstance(xc, ListConfig):
# xc = list(xc)
if isinstance(xc, dict) or isinstance(xc, list):
c = self.get_learned_conditioning(xc)
else:

6
comfy/ldm/modules/diffusionmodules/openaimodel.py
View File

@@ -477,9 +477,9 @@ class UNetModel(nn.Module):
if context_dim is not None:
assert use_spatial_transformer, 'Fool!! You forgot to use the spatial transformer for your cross-attention conditioning...'
from omegaconf.listconfig import ListConfig
if type(context_dim) == ListConfig:
context_dim = list(context_dim)
# from omegaconf.listconfig import ListConfig
# if type(context_dim) == ListConfig:
# context_dim = list(context_dim)
if num_heads_upsample == -1:
num_heads_upsample = num_heads