update

src/diffusers/models/model_loading_utils.py

@@ -41,8 +41,6 @@ from ..utils import (
     is_gguf_available,
     is_torch_available,
     is_torch_version,
-    is_torchao_available,
-    is_torchao_version,
     logging,
 )
 
@@ -61,38 +59,6 @@ if is_accelerate_available():
     from accelerate.utils import get_balanced_memory, get_max_memory, offload_weight, set_module_tensor_to_device
 
 
-def _update_torch_safe_globals():
-    safe_globals = [
-        (torch.uint1, "torch.uint1"),
-        (torch.uint2, "torch.uint2"),
-        (torch.uint3, "torch.uint3"),
-        (torch.uint4, "torch.uint4"),
-        (torch.uint5, "torch.uint5"),
-        (torch.uint6, "torch.uint6"),
-        (torch.uint7, "torch.uint7"),
-    ]
-    try:
-        from torchao.dtypes import NF4Tensor
-        from torchao.dtypes.floatx.float8_layout import Float8AQTTensorImpl
-        from torchao.dtypes.uintx.uint4_layout import UInt4Tensor
-        from torchao.dtypes.uintx.uintx_layout import UintxAQTTensorImpl, UintxTensor
-
-        safe_globals.extend([UintxTensor, UInt4Tensor, UintxAQTTensorImpl, Float8AQTTensorImpl, NF4Tensor])
-
-    except (ImportError, ModuleNotFoundError) as e:
-        logger.warning(
-            "Unable to import `torchao` Tensor objects. This may affect loading checkpoints serialized with `torchao`"
-        )
-        logger.debug(e)
-
-    finally:
-        torch.serialization.add_safe_globals(safe_globals=safe_globals)
-
-
-if is_torch_version(">=", "2.6") and is_torchao_available() and is_torchao_version(">=", "0.7.0"):
-    _update_torch_safe_globals()
-
-
 # Adapted from `transformers` (see modeling_utils.py)
 def _determine_device_map(
     model: torch.nn.Module, device_map, max_memory, torch_dtype, keep_in_fp32_modules=[], hf_quantizer=None

src/diffusers/quantizers/torchao/torchao_quantizer.py

@@ -23,7 +23,14 @@ from typing import TYPE_CHECKING, Any, Dict, List, Union
 
 from packaging import version
 
-from ...utils import get_module_from_name, is_torch_available, is_torch_version, is_torchao_available, logging
+from ...utils import (
+    get_module_from_name,
+    is_torch_available,
+    is_torch_version,
+    is_torchao_version,
+    is_torchao_available,
+    logging,
+)
 from ..base import DiffusersQuantizer
 
 
@@ -62,6 +69,38 @@ if is_torchao_available():
     from torchao.quantization import quantize_
 
 
+def _update_torch_safe_globals():
+    safe_globals = [
+        (torch.uint1, "torch.uint1"),
+        (torch.uint2, "torch.uint2"),
+        (torch.uint3, "torch.uint3"),
+        (torch.uint4, "torch.uint4"),
+        (torch.uint5, "torch.uint5"),
+        (torch.uint6, "torch.uint6"),
+        (torch.uint7, "torch.uint7"),
+    ]
+    try:
+        from torchao.dtypes import NF4Tensor
+        from torchao.dtypes.floatx.float8_layout import Float8AQTTensorImpl
+        from torchao.dtypes.uintx.uint4_layout import UInt4Tensor
+        from torchao.dtypes.uintx.uintx_layout import UintxAQTTensorImpl, UintxTensor
+
+        safe_globals.extend([UintxTensor, UInt4Tensor, UintxAQTTensorImpl, Float8AQTTensorImpl, NF4Tensor])
+
+    except (ImportError, ModuleNotFoundError) as e:
+        logger.warning(
+            "Unable to import `torchao` Tensor objects. This may affect loading checkpoints serialized with `torchao`"
+        )
+        logger.debug(e)
+
+    finally:
+        torch.serialization.add_safe_globals(safe_globals=safe_globals)
+
+
+if is_torch_version(">=", "2.6") and is_torchao_available() and is_torchao_version(">=", "0.7.0"):
+    _update_torch_safe_globals()
+
+
 logger = logging.get_logger(__name__)