Merge pull request #2312 from kohya-ss/dev

Merge dev to main

README-ja.md

@@ -50,6 +50,9 @@ Stable Diffusion等の画像生成モデルの学習、モデルによる画像
 
 ### 更新履歴
 
+- 次のリリースに含まれる予定の主な変更点は以下の通りです。リリース前の変更点は予告なく変更される可能性があります。
+    - Intel GPUの互換性を向上しました。[PR #2307](https://github.com/kohya-ss/sd-scripts/pull/2307) WhitePr氏に感謝します。
+
 - **Version 0.10.3 (2026-04-02):**
     - Animaでfp16で学習する際の安定性をさらに改善しました。[PR #2302](https://github.com/kohya-ss/sd-scripts/pull/2302) 問題をご報告いただいた方々に深く感謝します。
 

README.md

@@ -47,6 +47,9 @@ If you find this project helpful, please consider supporting its development via
 
 ### Change History
 
+- The following are the main changes planned for the next release. Please note that these changes may be subject to change without notice before the release.
+    - Improved compatibility with Intel GPUs. Thanks to WhitePr for [PR #2307](https://github.com/kohya-ss/sd-scripts/pull/2307).
+
 - **Version 0.10.3 (2026-04-02):**
     - Stability when training with fp16 on Anima has been further improved. See [PR #2302](https://github.com/kohya-ss/sd-scripts/pull/2302) for details. We deeply appreciate those who reported the issue.
 

library/ipex/__init__.py

@@ -1,6 +1,7 @@
 import os
 import sys
 import torch
+from packaging import version
 try:
     import intel_extension_for_pytorch as ipex # pylint: disable=import-error, unused-import
     has_ipex = True
@@ -8,7 +9,7 @@ except Exception:
     has_ipex = False
 from .hijacks import ipex_hijacks
 
-torch_version = float(torch.__version__[:3])
+torch_version = version.parse(torch.__version__)
 
 # pylint: disable=protected-access, missing-function-docstring, line-too-long
 
@@ -56,7 +57,6 @@ def ipex_init(): # pylint: disable=too-many-statements
             torch.cuda.__path__ = torch.xpu.__path__
             torch.cuda.set_stream = torch.xpu.set_stream
             torch.cuda.torch = torch.xpu.torch
-            torch.cuda.Union = torch.xpu.Union
             torch.cuda.__annotations__ = torch.xpu.__annotations__
             torch.cuda.__package__ = torch.xpu.__package__
             torch.cuda.__builtins__ = torch.xpu.__builtins__
@@ -64,14 +64,12 @@ def ipex_init(): # pylint: disable=too-many-statements
             torch.cuda.StreamContext = torch.xpu.StreamContext
             torch.cuda._lazy_call = torch.xpu._lazy_call
             torch.cuda.random = torch.xpu.random
-            torch.cuda._device = torch.xpu._device
             torch.cuda.__name__ = torch.xpu.__name__
-            torch.cuda._device_t = torch.xpu._device_t
             torch.cuda.__spec__ = torch.xpu.__spec__
             torch.cuda.__file__ = torch.xpu.__file__
             # torch.cuda.is_current_stream_capturing = torch.xpu.is_current_stream_capturing
 
-            if torch_version < 2.3:
+            if torch_version < version.parse("2.3"):
                 torch.cuda._initialization_lock = torch.xpu.lazy_init._initialization_lock
                 torch.cuda._initialized = torch.xpu.lazy_init._initialized
                 torch.cuda._is_in_bad_fork = torch.xpu.lazy_init._is_in_bad_fork
@@ -114,17 +112,22 @@ def ipex_init(): # pylint: disable=too-many-statements
                 torch.cuda.threading = torch.xpu.threading
                 torch.cuda.traceback = torch.xpu.traceback
 
-            if torch_version < 2.5:
+            if torch_version < version.parse("2.5"):
                 torch.cuda.os = torch.xpu.os
                 torch.cuda.Device = torch.xpu.Device
                 torch.cuda.warnings = torch.xpu.warnings
                 torch.cuda.classproperty = torch.xpu.classproperty
                 torch.UntypedStorage.cuda = torch.UntypedStorage.xpu
 
-            if torch_version < 2.7:
+            if torch_version < version.parse("2.7"):
                 torch.cuda.Tuple = torch.xpu.Tuple
                 torch.cuda.List = torch.xpu.List
 
+            if torch_version < version.parse("2.11"):
+                torch.cuda._device_t = torch.xpu._device_t
+                torch.cuda._device = torch.xpu._device
+                torch.cuda.Union = torch.xpu.Union
+
 
             # Memory:
             if 'linux' in sys.platform and "WSL2" in os.popen("uname -a").read():
@@ -160,7 +163,7 @@ def ipex_init(): # pylint: disable=too-many-statements
             torch.cuda.initial_seed = torch.xpu.initial_seed
 
             # C
-            if torch_version < 2.3:
+            if torch_version < version.parse("2.3"):
                 torch._C._cuda_getCurrentRawStream = ipex._C._getCurrentRawStream
                 ipex._C._DeviceProperties.multi_processor_count = ipex._C._DeviceProperties.gpu_subslice_count
                 ipex._C._DeviceProperties.major = 12

networks/lora.py

@@ -465,10 +465,6 @@ def create_network(
         conv_block_dims = None
         conv_block_alphas = None
 
-    drop_keys = kwargs.get("drop_keys", None)
-    if drop_keys is not None:
-        drop_keys = drop_keys.split(',') 
-
     # rank/module dropout
     rank_dropout = kwargs.get("rank_dropout", None)
     if rank_dropout is not None:
@@ -493,7 +489,6 @@ def create_network(
         block_alphas=block_alphas,
         conv_block_dims=conv_block_dims,
         conv_block_alphas=conv_block_alphas,
-        drop_keys=drop_keys,
         varbose=True,
         is_sdxl=is_sdxl,
     )
@@ -898,7 +893,6 @@ class LoRANetwork(torch.nn.Module):
         modules_dim: Optional[Dict[str, int]] = None,
         modules_alpha: Optional[Dict[str, int]] = None,
         module_class: Type[object] = LoRAModule,
-        drop_keys: Optional[List[str]] = None,
         varbose: Optional[bool] = False,
         is_sdxl: Optional[bool] = False,
     ) -> None:
@@ -920,7 +914,6 @@ class LoRANetwork(torch.nn.Module):
         self.dropout = dropout
         self.rank_dropout = rank_dropout
         self.module_dropout = module_dropout
-        self.drop_keys = drop_keys
 
         self.loraplus_lr_ratio = None
         self.loraplus_unet_lr_ratio = None
@@ -948,9 +941,6 @@ class LoRANetwork(torch.nn.Module):
                     f"apply LoRA to Conv2d with kernel size (3,3). dim (rank): {self.conv_lora_dim}, alpha: {self.conv_alpha}"
                 )
 
-        if self.drop_keys:
-            print(f"Drop keys: {self.drop_keys}")
-
         # create module instances
         def create_modules(
             is_unet: bool,
@@ -980,12 +970,6 @@ class LoRANetwork(torch.nn.Module):
                             lora_name = prefix + "." + name + "." + child_name
                             lora_name = lora_name.replace(".", "_")
 
-                            if self.drop_keys:
-                                for key in self.drop_keys:
-                                    if key in lora_name:
-                                        skipped.append(lora_name)
-                                        continue
-
                             dim = None
                             alpha = None