add is_torchvision_available

src/diffusers/training_utils.py

@@ -5,14 +5,14 @@
 
 import numpy as np
 import torch
-from transformers import is_torchvision_available
 
 from .models import UNet2DConditionModel
 from .utils import (
     convert_state_dict_to_diffusers,
     convert_state_dict_to_peft,
     deprecate,
     is_peft_available,
+    is_torchvision_available,
     is_transformers_available,
 )
 

src/diffusers/utils/__init__.py

@@ -75,6 +75,7 @@
     is_torch_version,
     is_torch_xla_available,
     is_torchsde_available,
+    is_torchvision_available,
     is_transformers_available,
     is_transformers_version,
     is_unidecode_available,

src/diffusers/utils/import_utils.py

@@ -278,6 +278,13 @@
 except importlib_metadata.PackageNotFoundError:
     _peft_available = False
 
+_torchvision_available = importlib.util.find_spec("torchvision") is not None
+try:
+    _torchvision_version = importlib_metadata.version("torchvision")
+    logger.debug(f"Successfully imported torchvision version {_torchvision_version}")
+except importlib_metadata.PackageNotFoundError:
+    _torchvision_available = False
+
 
 def is_torch_available():
     return _torch_available
@@ -367,6 +374,10 @@ def is_peft_available():
     return _peft_available
 
 
+def is_torchvision_available():
+    return _torchvision_available
+
+
 # docstyle-ignore
 FLAX_IMPORT_ERROR = """
 {0} requires the FLAX library but it was not found in your environment. Checkout the instructions on the