IPEX remove the use of lambdas

modules/intel/ipex/__init__.py

@@ -16,6 +16,28 @@ torch_version[0], torch_version[1] = int(torch_version[0]), int(torch_version[1]
 
 # pylint: disable=protected-access, missing-function-docstring, line-too-long
 
+def return_true(*args, **kwargs):
+    return True
+
+def return_false(*args, **kwargs):
+    return False
+
+def return_none(*args, **kwargs):
+    return None
+
+def return_zero(*args, **kwargs):
+    return 0
+
+def return_cuda_version(*args, **kwargs):
+    return (12,1)
+
+def return_xpu_string(*args, **kwargs):
+    return "xpu"
+
+def return_arch_list(*args, **kwargs):
+    return ["pvc", "dg2", "ats-m150"]
+
+
 def ipex_init(): # pylint: disable=too-many-statements
     try:
         if hasattr(torch, "cuda") and hasattr(torch.cuda, "is_xpu_hijacked") and torch.cuda.is_xpu_hijacked:
@@ -26,9 +48,9 @@ def ipex_init(): # pylint: disable=too-many-statements
                 # import inductor utils to get around lazy import
                 from torch._inductor import utils as torch_inductor_utils # pylint: disable=import-error, unused-import # noqa: F401,RUF100
                 torch._inductor.utils.GPU_TYPES = ["xpu"]
-                torch._inductor.utils.get_gpu_type = lambda *args, **kwargs: "xpu"
+                torch._inductor.utils.get_gpu_type = return_xpu_string
                 from triton import backends as triton_backends # pylint: disable=import-error
-                triton_backends.backends["nvidia"].driver.is_active = lambda *args, **kwargs: False
+                triton_backends.backends["nvidia"].driver.is_active = return_false
             except Exception:
                 pass
             # Replace cuda with xpu:
@@ -56,7 +78,7 @@ def ipex_init(): # pylint: disable=too-many-statements
             torch.cuda._get_device_index = torch.xpu._get_device_index
             torch.cuda._lazy_init = torch.xpu._lazy_init
             torch.cuda._lazy_call = torch.xpu._lazy_call
-            torch.cuda.is_current_stream_capturing = lambda: False
+            torch.cuda.is_current_stream_capturing = return_false
 
             torch.cuda.__annotations__ = torch.xpu.__annotations__
             torch.cuda.__builtins__ = torch.xpu.__builtins__
@@ -145,7 +167,7 @@ def ipex_init(): # pylint: disable=too-many-statements
 
             # Memory:
             if "linux" in sys.platform and "WSL2" in os.popen("uname -a").read():
-                torch.xpu.empty_cache = lambda: None
+                torch.xpu.empty_cache = return_none
             torch.cuda.empty_cache = torch.xpu.empty_cache
 
             if torch_version[0] >= 2 and torch_version[1] >= 8:
@@ -180,21 +202,24 @@ def ipex_init(): # pylint: disable=too-many-statements
             torch.cuda.initial_seed = torch.xpu.initial_seed
 
             # Fix functions with ipex:
-            # torch.xpu.mem_get_info always returns the total memory as free memory
             torch.has_cuda = True
             torch.version.cuda = "12.1"
-            torch.backends.cuda.is_built = lambda *args, **kwargs: True
-            torch._utils._get_available_device_type = lambda: "xpu"
+            torch.backends.cuda.is_built = return_true
+            torch._utils._get_available_device_type = return_xpu_string
 
-            torch.xpu.mem_get_info = lambda device=None: [(torch.xpu.get_device_properties(device).total_memory - torch.xpu.memory_reserved(device)), torch.xpu.get_device_properties(device).total_memory]
+            # torch.xpu.mem_get_info always returns the total memory as free memory
+            def mem_get_info(device=None):
+                return [(torch.xpu.get_device_properties(device).total_memory - torch.xpu.memory_reserved(device)), torch.xpu.get_device_properties(device).total_memory]
+            torch.xpu.mem_get_info = mem_get_info
             torch.cuda.mem_get_info = torch.xpu.mem_get_info
+
             torch.cuda.has_half = True
-            torch.cuda.is_bf16_supported = getattr(torch.xpu, "is_bf16_supported", lambda *args, **kwargs: True)
-            torch.cuda.is_fp16_supported = lambda *args, **kwargs: True
-            torch.cuda.get_arch_list = getattr(torch.xpu, "get_arch_list", lambda: ["pvc", "dg2", "ats-m150"])
-            torch.cuda.get_device_capability = lambda *args, **kwargs: (12,1)
-            torch.cuda.ipc_collect = lambda *args, **kwargs: None
-            torch.cuda.utilization = lambda *args, **kwargs: 0
+            torch.cuda.is_bf16_supported = getattr(torch.xpu, "is_bf16_supported", return_true)
+            torch.cuda.is_fp16_supported = getattr(torch.xpu, "is_fp16_supported", return_true)
+            torch.cuda.get_arch_list = getattr(torch.xpu, "get_arch_list", return_arch_list)
+            torch.cuda.get_device_capability = return_cuda_version
+            torch.cuda.ipc_collect = return_none
+            torch.cuda.utilization = return_zero
 
             device_supports_fp64 = ipex_hijacks()
             try:

modules/intel/ipex/hijacks.py

@@ -15,8 +15,10 @@ torch_version[0], torch_version[1] = int(torch_version[0]), int(torch_version[1]
 
 device_supports_fp64 = torch.xpu.has_fp64_dtype() if hasattr(torch.xpu, "has_fp64_dtype") else torch.xpu.get_device_properties(devices.device).has_fp64
 
-# pylint: disable=protected-access, missing-function-docstring, line-too-long, unnecessary-lambda, no-else-return
+# pylint: disable=protected-access, missing-function-docstring, line-too-long, no-else-return
 
+def return_false(*args, **kwargs):
+    return False
 
 @property
 def is_cuda(self):
@@ -437,6 +439,6 @@ def ipex_hijacks():
 
     if not hasattr(torch.cuda.amp, "common"):
         torch.cuda.amp.common = nullcontext()
-    torch.cuda.amp.common.amp_definitely_not_available = lambda: False
+    torch.cuda.amp.common.amp_definitely_not_available = return_false
 
     return device_supports_fp64