updated

torch_patch.py

@@ -0,0 +1,66 @@
+"""
+Patch for torch module to make it compatible with newer diffusers versions 
+while using PyTorch 2.0.1
+"""
+import torch
+import sys
+import warnings
+import types
+import functools
+
+# Check if the attributes already exist
+if not hasattr(torch, 'float8_e4m3fn'):
+    # Add missing attributes for compatibility
+    # These won't actually function, but they'll allow imports to succeed
+    torch.float8_e4m3fn = torch.float16  # Use float16 as a placeholder type
+    warnings.warn(
+        "Added placeholder for torch.float8_e4m3fn. Actual 8-bit operations won't work, "
+        "but imports should succeed. Using PyTorch 2.0.1 with newer diffusers."
+    )
+
+if not hasattr(torch, 'float8_e5m2'):
+    torch.float8_e5m2 = torch.float16  # Use float16 as a placeholder type
+
+# Add other missing torch types that might be referenced
+for type_name in ['bfloat16', 'bfloat8', 'float8_e4m3fnuz']:
+    if not hasattr(torch, type_name):
+        setattr(torch, type_name, torch.float16)
+        
+# Create a placeholder for torch._dynamo if it doesn't exist
+if not hasattr(torch, '_dynamo'):
+    torch._dynamo = types.ModuleType('torch._dynamo')
+    sys.modules['torch._dynamo'] = torch._dynamo
+    
+    # Add common attributes/functions used by torch._dynamo
+    torch._dynamo.config = types.SimpleNamespace(suppress_errors=True)
+    torch._dynamo.optimize = lambda *args, **kwargs: lambda f: f
+    torch._dynamo.disable = lambda: None
+    torch._dynamo.reset_repro_cache = lambda: None
+
+# Add torch.compile if it doesn't exist
+if not hasattr(torch, 'compile'):
+    # Just return the function unchanged
+    torch.compile = lambda fn, **kwargs: fn
+
+# Create a placeholder for torch.cuda.amp if it doesn't exist
+if not hasattr(torch.cuda, 'amp'):
+    torch.cuda.amp = types.ModuleType('torch.cuda.amp')
+    sys.modules['torch.cuda.amp'] = torch.cuda.amp
+    
+    # Mock autocast
+    class MockAutocast:
+        def __init__(self, *args, **kwargs):
+            pass
+        def __enter__(self):
+            return self
+        def __exit__(self, *args):
+            pass
+        def __call__(self, func):
+            @functools.wraps(func)
+            def wrapper(*args, **kwargs):
+                return func(*args, **kwargs)
+            return wrapper
+    
+    torch.cuda.amp.autocast = MockAutocast
+
+print("PyTorch patched for compatibility with newer diffusers - using latest diffusers with PyTorch 2.0.1")