Merge pull request #1060 from akx/refactor-xpu-init

Deduplicate ipex initialization code

XTI_hijack.py

@@ -1,11 +1,7 @@
 import torch
-try:
-    import intel_extension_for_pytorch as ipex
-    if torch.xpu.is_available():
-        from library.ipex import ipex_init
-        ipex_init()
-except Exception:
-    pass
+from library.ipex_interop import init_ipex
+
+init_ipex()
 from typing import Union, List, Optional, Dict, Any, Tuple
 from diffusers.models.unet_2d_condition import UNet2DConditionOutput
 

fine_tune.py

@@ -11,15 +11,10 @@
 from tqdm import tqdm
 import torch
 
-try:
-    import intel_extension_for_pytorch as ipex
+from library.ipex_interop import init_ipex
 
-    if torch.xpu.is_available():
-        from library.ipex import ipex_init
+init_ipex()
 
-        ipex_init()
-except Exception:
-    pass
 from accelerate.utils import set_seed
 from diffusers import DDPMScheduler
 

gen_img_diffusers.py

@@ -66,15 +66,10 @@
 import numpy as np
 import torch
 
-try:
-    import intel_extension_for_pytorch as ipex
+from library.ipex_interop import init_ipex
 
-    if torch.xpu.is_available():
-        from library.ipex import ipex_init
+init_ipex()
 
-        ipex_init()
-except Exception:
-    pass
 import torchvision
 from diffusers import (
     AutoencoderKL,

library/ipex_interop.py

@@ -0,0 +1,24 @@
+import torch
+
+
+def init_ipex():
+    """
+    Try to import `intel_extension_for_pytorch`, and apply
+    the hijacks using `library.ipex.ipex_init`.
+
+    If IPEX is not installed, this function does nothing.
+    """
+    try:
+        import intel_extension_for_pytorch as ipex  # noqa
+    except ImportError:
+        return
+
+    try:
+        from library.ipex import ipex_init
+
+        if torch.xpu.is_available():
+            is_initialized, error_message = ipex_init()
+            if not is_initialized:
+                print("failed to initialize ipex:", error_message)
+    except Exception as e:
+        print("failed to initialize ipex:", e)

library/model_util.py

@@ -5,15 +5,9 @@
 import os
 import torch
 
-try:
-    import intel_extension_for_pytorch as ipex
+from library.ipex_interop import init_ipex
 
-    if torch.xpu.is_available():
-        from library.ipex import ipex_init
-
-        ipex_init()
-except Exception:
-    pass
+init_ipex()
 import diffusers
 from transformers import CLIPTextModel, CLIPTokenizer, CLIPTextConfig, logging
 from diffusers import AutoencoderKL, DDIMScheduler, StableDiffusionPipeline  # , UNet2DConditionModel

sdxl_gen_img.py

@@ -18,15 +18,10 @@
 import numpy as np
 import torch
 
-try:
-    import intel_extension_for_pytorch as ipex
+from library.ipex_interop import init_ipex
 
-    if torch.xpu.is_available():
-        from library.ipex import ipex_init
+init_ipex()
 
-        ipex_init()
-except Exception:
-    pass
 import torchvision
 from diffusers import (
     AutoencoderKL,

sdxl_minimal_inference.py

@@ -9,13 +9,11 @@
 from einops import repeat
 import numpy as np
 import torch
-try:
-    import intel_extension_for_pytorch as ipex
-    if torch.xpu.is_available():
-        from library.ipex import ipex_init
-        ipex_init()
-except Exception:
-    pass
+
+from library.ipex_interop import init_ipex
+
+init_ipex()
+
 from tqdm import tqdm
 from transformers import CLIPTokenizer
 from diffusers import EulerDiscreteScheduler

sdxl_train.py

@@ -11,15 +11,10 @@
 from tqdm import tqdm
 import torch
 
-try:
-    import intel_extension_for_pytorch as ipex
+from library.ipex_interop import init_ipex
 
-    if torch.xpu.is_available():
-        from library.ipex import ipex_init
+init_ipex()
 
-        ipex_init()
-except Exception:
-    pass
 from accelerate.utils import set_seed
 from diffusers import DDPMScheduler
 from library import sdxl_model_util

sdxl_train_control_net_lllite.py

@@ -14,13 +14,11 @@
 
 from tqdm import tqdm
 import torch
-try:
-    import intel_extension_for_pytorch as ipex
-    if torch.xpu.is_available():
-        from library.ipex import ipex_init
-        ipex_init()
-except Exception:
-    pass
+
+from library.ipex_interop import init_ipex
+
+init_ipex()
+
 from torch.nn.parallel import DistributedDataParallel as DDP
 from accelerate.utils import set_seed
 import accelerate

sdxl_train_control_net_lllite_old.py

@@ -11,13 +11,11 @@
 
 from tqdm import tqdm
 import torch
-try:
-    import intel_extension_for_pytorch as ipex
-    if torch.xpu.is_available():
-        from library.ipex import ipex_init
-        ipex_init()
-except Exception:
-    pass
+
+from library.ipex_interop import init_ipex
+
+init_ipex()
+
 from torch.nn.parallel import DistributedDataParallel as DDP
 from accelerate.utils import set_seed
 from diffusers import DDPMScheduler, ControlNetModel

sdxl_train_network.py

@@ -1,15 +1,10 @@
 import argparse
 import torch
 
-try:
-    import intel_extension_for_pytorch as ipex
+from library.ipex_interop import init_ipex
 
-    if torch.xpu.is_available():
-        from library.ipex import ipex_init
+init_ipex()
 
-        ipex_init()
-except Exception:
-    pass
 from library import sdxl_model_util, sdxl_train_util, train_util
 import train_network
 

sdxl_train_textual_inversion.py

@@ -3,13 +3,9 @@
 
 import regex
 import torch
-try:
-    import intel_extension_for_pytorch as ipex
-    if torch.xpu.is_available():
-        from library.ipex import ipex_init
-        ipex_init()
-except Exception:
-    pass
+from library.ipex_interop import init_ipex
+
+init_ipex()
 import open_clip
 from library import sdxl_model_util, sdxl_train_util, train_util
 

train_controlnet.py

@@ -12,15 +12,10 @@
 from tqdm import tqdm
 import torch
 
-try:
-    import intel_extension_for_pytorch as ipex
+from library.ipex_interop import init_ipex
 
-    if torch.xpu.is_available():
-        from library.ipex import ipex_init
+init_ipex()
 
-        ipex_init()
-except Exception:
-    pass
 from torch.nn.parallel import DistributedDataParallel as DDP
 from accelerate.utils import set_seed
 from diffusers import DDPMScheduler, ControlNetModel

train_db.py

@@ -12,15 +12,10 @@
 from tqdm import tqdm
 import torch
 
-try:
-    import intel_extension_for_pytorch as ipex
+from library.ipex_interop import init_ipex
 
-    if torch.xpu.is_available():
-        from library.ipex import ipex_init
+init_ipex()
 
-        ipex_init()
-except Exception:
-    pass
 from accelerate.utils import set_seed
 from diffusers import DDPMScheduler
 

train_network.py

@@ -14,15 +14,10 @@
 import torch
 from torch.nn.parallel import DistributedDataParallel as DDP
 
-try:
-    import intel_extension_for_pytorch as ipex
+from library.ipex_interop import init_ipex
 
-    if torch.xpu.is_available():
-        from library.ipex import ipex_init
+init_ipex()
 
-        ipex_init()
-except Exception:
-    pass
 from accelerate.utils import set_seed
 from diffusers import DDPMScheduler
 from library import model_util

train_textual_inversion.py

@@ -8,15 +8,10 @@
 from tqdm import tqdm
 import torch
 
-try:
-    import intel_extension_for_pytorch as ipex
+from library.ipex_interop import init_ipex
 
-    if torch.xpu.is_available():
-        from library.ipex import ipex_init
+init_ipex()
 
-        ipex_init()
-except Exception:
-    pass
 from accelerate.utils import set_seed
 from diffusers import DDPMScheduler
 from transformers import CLIPTokenizer

train_textual_inversion_XTI.py

@@ -8,13 +8,11 @@
 
 from tqdm import tqdm
 import torch
-try:
-    import intel_extension_for_pytorch as ipex
-    if torch.xpu.is_available():
-        from library.ipex import ipex_init
-        ipex_init()
-except Exception:
-    pass
+
+from library.ipex_interop import init_ipex
+
+init_ipex()
+
 from accelerate.utils import set_seed
 import diffusers
 from diffusers import DDPMScheduler