From 6f68f91efe9d79f3890f5f7e87d092d869c04c0a Mon Sep 17 00:00:00 2001 From: Disty0 Date: Wed, 5 Mar 2025 22:27:29 +0300 Subject: [PATCH] IPEX cleanup hijacks and add torch.eye --- modules/intel/ipex/hijacks.py | 79 ++++++++++++++++++++--------------- 1 file changed, 46 insertions(+), 33 deletions(-) diff --git a/modules/intel/ipex/hijacks.py b/modules/intel/ipex/hijacks.py index a1be40916..8a4138d04 100644 --- a/modules/intel/ipex/hijacks.py +++ b/modules/intel/ipex/hijacks.py @@ -5,10 +5,10 @@ import torch import numpy as np from modules import devices, errors -device_supports_fp64 = torch.xpu.has_fp64_dtype() if hasattr(torch.xpu, "has_fp64_dtype") else torch.xpu.get_device_properties("xpu").has_fp64 -if os.environ.get('IPEX_FORCE_ATTENTION_SLICE', '0') == '0' and (torch.xpu.get_device_properties("xpu").total_memory / 1024 / 1024 / 1024) > 4.1: +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 +if os.environ.get('IPEX_FORCE_ATTENTION_SLICE', '0') == '0' and (torch.xpu.get_device_properties(devices.device).total_memory / 1024 / 1024 / 1024) > 4.1: try: - x = torch.ones((33000,33000), dtype=torch.float32, device="xpu") + x = torch.ones((33000,33000), dtype=torch.float32, device=devices.device) del x torch.xpu.empty_cache() can_allocate_plus_4gb = True @@ -30,13 +30,22 @@ def return_null_context(*args, **kwargs): # pylint: disable=unused-argument @property def is_cuda(self): - return self.device.type == 'xpu' or self.device.type == 'cuda' + return self.device.type == "xpu" or self.device.type == "cuda" -def check_device(device): - return bool((isinstance(device, torch.device) and device.type == "cuda") or (isinstance(device, str) and "cuda" in device) or isinstance(device, int)) +def check_device_type(device, device_type: str) -> bool: + if device is None or isinstance(device, torch.dtype): # torch.Tensor.to can get a dtype as input + return False + else: + if hasattr(device, "device"): # torch.Tensor.to can get a tensor as input + return bool(torch.device(device.device).type == device_type) + else: + return bool(torch.device(device).type == device_type) -def return_xpu(device): - return f"xpu:{device.split(':')[-1]}" if isinstance(device, str) and ":" in device else f"xpu:{device}" if isinstance(device, int) else torch.device(f"xpu:{device.index}" if device.index is not None else "xpu") if isinstance(device, torch.device) else "xpu" +def check_cuda(device) -> bool: + return bool(isinstance(device, int) or check_device_type(device, "cuda")) + +def return_xpu(device): # keep the device instance type, aka return string if the input is string + return devices.device if device is None else f"xpu:{device.split(':')[-1]}" if isinstance(device, str) and ":" in device else f"xpu:{device}" if isinstance(device, int) else torch.device(f"xpu:{device.index}" if device.index is not None else "xpu") if isinstance(device, torch.device) else "xpu" # Autocast @@ -69,17 +78,16 @@ original_from_numpy = torch.from_numpy @wraps(torch.from_numpy) def from_numpy(ndarray): if ndarray.dtype == float: - return original_from_numpy(ndarray.astype('float32')) + return original_from_numpy(ndarray.astype("float32")) else: return original_from_numpy(ndarray) original_as_tensor = torch.as_tensor @wraps(torch.as_tensor) def as_tensor(data, dtype=None, device=None): - if check_device(device): + if check_cuda(device): device = return_xpu(device) - if isinstance(data, np.ndarray) and data.dtype == float and not ( - (isinstance(device, torch.device) and device.type == "cpu") or (isinstance(device, str) and "cpu" in device)): + if isinstance(data, np.ndarray) and data.dtype == float and not check_device_type(device, "cpu"): return original_as_tensor(data, dtype=torch.float32, device=device) else: return original_as_tensor(data, dtype=dtype, device=device) @@ -198,10 +206,10 @@ original_torch_tensor = torch.tensor @wraps(torch.tensor) def torch_tensor(data, *args, dtype=None, device=None, **kwargs): global device_supports_fp64 - if check_device(device): + if check_cuda(device): device = return_xpu(device) if not device_supports_fp64: - if (isinstance(device, torch.device) and device.type == "xpu") or (isinstance(device, str) and "xpu" in device): + if check_device_type(device, "xpu"): if dtype == torch.float64: dtype = torch.float32 elif dtype is None and (hasattr(data, "dtype") and (data.dtype == torch.float64 or data.dtype == float)): @@ -211,7 +219,7 @@ def torch_tensor(data, *args, dtype=None, device=None, **kwargs): original_Tensor_to = torch.Tensor.to @wraps(torch.Tensor.to) def Tensor_to(self, device=None, *args, **kwargs): - if check_device(device): + if check_cuda(device): return original_Tensor_to(self, return_xpu(device), *args, **kwargs) else: return original_Tensor_to(self, device, *args, **kwargs) @@ -219,17 +227,15 @@ def Tensor_to(self, device=None, *args, **kwargs): original_Tensor_cuda = torch.Tensor.cuda @wraps(torch.Tensor.cuda) def Tensor_cuda(self, device=None, *args, **kwargs): - if check_device(device): - return original_Tensor_cuda(self, return_xpu(device), *args, **kwargs) + if device is None or check_cuda(device): + return self.to(return_xpu(device), *args, **kwargs) else: return original_Tensor_cuda(self, device, *args, **kwargs) original_Tensor_pin_memory = torch.Tensor.pin_memory @wraps(torch.Tensor.pin_memory) def Tensor_pin_memory(self, device=None, *args, **kwargs): - if device is None: - device = "xpu" - if check_device(device): + if device is None or check_cuda(device): return original_Tensor_pin_memory(self, return_xpu(device), *args, **kwargs) else: return original_Tensor_pin_memory(self, device, *args, **kwargs) @@ -237,7 +243,7 @@ def Tensor_pin_memory(self, device=None, *args, **kwargs): original_UntypedStorage_init = torch.UntypedStorage.__init__ @wraps(torch.UntypedStorage.__init__) def UntypedStorage_init(*args, device=None, **kwargs): - if check_device(device): + if check_cuda(device): return original_UntypedStorage_init(*args, device=return_xpu(device), **kwargs) else: return original_UntypedStorage_init(*args, device=device, **kwargs) @@ -245,7 +251,7 @@ def UntypedStorage_init(*args, device=None, **kwargs): original_UntypedStorage_cuda = torch.UntypedStorage.cuda @wraps(torch.UntypedStorage.cuda) def UntypedStorage_cuda(self, device=None, *args, **kwargs): - if check_device(device): + if check_cuda(device): return original_UntypedStorage_cuda(self, return_xpu(device), *args, **kwargs) else: return original_UntypedStorage_cuda(self, device, *args, **kwargs) @@ -253,7 +259,7 @@ def UntypedStorage_cuda(self, device=None, *args, **kwargs): original_torch_empty = torch.empty @wraps(torch.empty) def torch_empty(*args, device=None, **kwargs): - if check_device(device): + if check_cuda(device): return original_torch_empty(*args, device=return_xpu(device), **kwargs) else: return original_torch_empty(*args, device=device, **kwargs) @@ -263,7 +269,7 @@ original_torch_randn = torch.randn def torch_randn(*args, device=None, dtype=None, **kwargs): if dtype is bytes: dtype = None - if check_device(device): + if check_cuda(device): return original_torch_randn(*args, device=return_xpu(device), **kwargs) else: return original_torch_randn(*args, device=device, **kwargs) @@ -271,7 +277,7 @@ def torch_randn(*args, device=None, dtype=None, **kwargs): original_torch_ones = torch.ones @wraps(torch.ones) def torch_ones(*args, device=None, **kwargs): - if check_device(device): + if check_cuda(device): return original_torch_ones(*args, device=return_xpu(device), **kwargs) else: return original_torch_ones(*args, device=device, **kwargs) @@ -279,7 +285,7 @@ def torch_ones(*args, device=None, **kwargs): original_torch_zeros = torch.zeros @wraps(torch.zeros) def torch_zeros(*args, device=None, **kwargs): - if check_device(device): + if check_cuda(device): return original_torch_zeros(*args, device=return_xpu(device), **kwargs) else: return original_torch_zeros(*args, device=device, **kwargs) @@ -287,7 +293,7 @@ def torch_zeros(*args, device=None, **kwargs): original_torch_full = torch.full @wraps(torch.full) def torch_full(*args, device=None, **kwargs): - if check_device(device): + if check_cuda(device): return original_torch_full(*args, device=return_xpu(device), **kwargs) else: return original_torch_full(*args, device=device, **kwargs) @@ -295,17 +301,23 @@ def torch_full(*args, device=None, **kwargs): original_torch_linspace = torch.linspace @wraps(torch.linspace) def torch_linspace(*args, device=None, **kwargs): - if check_device(device): + if check_cuda(device): return original_torch_linspace(*args, device=return_xpu(device), **kwargs) else: return original_torch_linspace(*args, device=device, **kwargs) +original_torch_eye = torch.eye +@wraps(torch.eye) +def torch_eye(*args, device=None, **kwargs): + if check_cuda(device): + return original_torch_eye(*args, device=return_xpu(device), **kwargs) + else: + return original_torch_eye(*args, device=device, **kwargs) + original_torch_load = torch.load @wraps(torch.load) def torch_load(f, map_location=None, *args, **kwargs): - if map_location is None: - map_location = "xpu" - if check_device(map_location): + if map_location is None or check_cuda(map_location): return original_torch_load(f, *args, map_location=return_xpu(map_location), **kwargs) else: return original_torch_load(f, *args, map_location=map_location, **kwargs) @@ -313,14 +325,14 @@ def torch_load(f, map_location=None, *args, **kwargs): original_torch_Generator = torch.Generator @wraps(torch.Generator) def torch_Generator(device=None): - if check_device(device): + if check_cuda(device): return original_torch_Generator(return_xpu(device)) else: return original_torch_Generator(device) @wraps(torch.cuda.synchronize) def torch_cuda_synchronize(device=None): - if check_device(device): + if check_cuda(device): return torch.xpu.synchronize(return_xpu(device)) else: return torch.xpu.synchronize(device) @@ -343,6 +355,7 @@ def ipex_hijacks(legacy=True): torch.zeros = torch_zeros torch.full = torch_full torch.linspace = torch_linspace + torch.eye = torch_eye torch.load = torch_load torch.Generator = torch_Generator torch.cuda.synchronize = torch_cuda_synchronize