Conditionally import torchvision in Cosmos transformer (#11524)

fix

src/diffusers/models/transformers/transformer_cosmos.py

@@ -18,9 +18,9 @@ import numpy as np
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
-from torchvision import transforms
 
 from ...configuration_utils import ConfigMixin, register_to_config
+from ...utils import is_torchvision_available
 from ..attention import FeedForward
 from ..attention_processor import Attention
 from ..embeddings import Timesteps
@@ -29,6 +29,10 @@ from ..modeling_utils import ModelMixin
 from ..normalization import RMSNorm
 
 
+if is_torchvision_available():
+    from torchvision import transforms
+
+
 class CosmosPatchEmbed(nn.Module):
     def __init__(
         self, in_channels: int, out_channels: int, patch_size: Tuple[int, int, int], bias: bool = True