fix: Add a fallback definition for `is_torch_fx_available` in `transformers.utils.import_utils`.

app.py

@@ -17,6 +17,20 @@ try:
 except Exception:
     pass
 
+try:
+    from transformers.utils import import_utils as _import_utils
+    if not hasattr(_import_utils, "is_torch_fx_available"):
+        def is_torch_fx_available():
+            try:
+                import torch as _torch
+                return hasattr(_torch, "fx")
+            except Exception:
+                return False
+
+        _import_utils.is_torch_fx_available = is_torch_fx_available
+except Exception:
+    pass
+
 # Suppress annoying warnings
 warnings.filterwarnings("ignore", message="The parameters have been moved from the Blocks constructor to the launch()")
 warnings.filterwarnings("ignore", message="CUDA is not available or torch_xla is imported")

app_hf.py

@@ -27,6 +27,20 @@ try:
 except Exception:
     pass
 
+try:
+    from transformers.utils import import_utils as _import_utils
+    if not hasattr(_import_utils, "is_torch_fx_available"):
+        def is_torch_fx_available():
+            try:
+                import torch as _torch
+                return hasattr(_torch, "fx")
+            except Exception:
+                return False
+
+        _import_utils.is_torch_fx_available = is_torch_fx_available
+except Exception:
+    pass
+
 # Suppress annoying warnings
 warnings.filterwarnings("ignore", message="The parameters have been moved from the Blocks constructor to the launch()")
 warnings.filterwarnings("ignore", message="CUDA is not available or torch_xla is imported")