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| import os | |
| import sys | |
| import contextlib | |
| import torch | |
| import intel_extension_for_pytorch as ipex # pylint: disable=import-error, unused-import | |
| from .hijacks import ipex_hijacks | |
| # pylint: disable=protected-access, missing-function-docstring, line-too-long | |
| 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: | |
| return True, "Skipping IPEX hijack" | |
| else: | |
| # Replace cuda with xpu: | |
| torch.cuda.current_device = torch.xpu.current_device | |
| torch.cuda.current_stream = torch.xpu.current_stream | |
| torch.cuda.device = torch.xpu.device | |
| torch.cuda.device_count = torch.xpu.device_count | |
| torch.cuda.device_of = torch.xpu.device_of | |
| torch.cuda.get_device_name = torch.xpu.get_device_name | |
| torch.cuda.get_device_properties = torch.xpu.get_device_properties | |
| torch.cuda.init = torch.xpu.init | |
| torch.cuda.is_available = torch.xpu.is_available | |
| torch.cuda.is_initialized = torch.xpu.is_initialized | |
| torch.cuda.is_current_stream_capturing = lambda: False | |
| torch.cuda.set_device = torch.xpu.set_device | |
| torch.cuda.stream = torch.xpu.stream | |
| torch.cuda.synchronize = torch.xpu.synchronize | |
| torch.cuda.Event = torch.xpu.Event | |
| torch.cuda.Stream = torch.xpu.Stream | |
| torch.cuda.FloatTensor = torch.xpu.FloatTensor | |
| torch.Tensor.cuda = torch.Tensor.xpu | |
| torch.Tensor.is_cuda = torch.Tensor.is_xpu | |
| torch.UntypedStorage.cuda = torch.UntypedStorage.xpu | |
| torch.cuda._initialization_lock = torch.xpu.lazy_init._initialization_lock | |
| torch.cuda._initialized = torch.xpu.lazy_init._initialized | |
| torch.cuda._lazy_seed_tracker = torch.xpu.lazy_init._lazy_seed_tracker | |
| torch.cuda._queued_calls = torch.xpu.lazy_init._queued_calls | |
| torch.cuda._tls = torch.xpu.lazy_init._tls | |
| torch.cuda.threading = torch.xpu.lazy_init.threading | |
| torch.cuda.traceback = torch.xpu.lazy_init.traceback | |
| torch.cuda.Optional = torch.xpu.Optional | |
| torch.cuda.__cached__ = torch.xpu.__cached__ | |
| torch.cuda.__loader__ = torch.xpu.__loader__ | |
| torch.cuda.ComplexFloatStorage = torch.xpu.ComplexFloatStorage | |
| torch.cuda.Tuple = torch.xpu.Tuple | |
| torch.cuda.streams = torch.xpu.streams | |
| torch.cuda._lazy_new = torch.xpu._lazy_new | |
| torch.cuda.FloatStorage = torch.xpu.FloatStorage | |
| torch.cuda.Any = torch.xpu.Any | |
| torch.cuda.__doc__ = torch.xpu.__doc__ | |
| torch.cuda.default_generators = torch.xpu.default_generators | |
| torch.cuda.HalfTensor = torch.xpu.HalfTensor | |
| torch.cuda._get_device_index = torch.xpu._get_device_index | |
| torch.cuda.__path__ = torch.xpu.__path__ | |
| torch.cuda.Device = torch.xpu.Device | |
| torch.cuda.IntTensor = torch.xpu.IntTensor | |
| torch.cuda.ByteStorage = torch.xpu.ByteStorage | |
| torch.cuda.set_stream = torch.xpu.set_stream | |
| torch.cuda.BoolStorage = torch.xpu.BoolStorage | |
| torch.cuda.os = torch.xpu.os | |
| torch.cuda.torch = torch.xpu.torch | |
| torch.cuda.BFloat16Storage = torch.xpu.BFloat16Storage | |
| torch.cuda.Union = torch.xpu.Union | |
| torch.cuda.DoubleTensor = torch.xpu.DoubleTensor | |
| torch.cuda.ShortTensor = torch.xpu.ShortTensor | |
| torch.cuda.LongTensor = torch.xpu.LongTensor | |
| torch.cuda.IntStorage = torch.xpu.IntStorage | |
| torch.cuda.LongStorage = torch.xpu.LongStorage | |
| torch.cuda.__annotations__ = torch.xpu.__annotations__ | |
| torch.cuda.__package__ = torch.xpu.__package__ | |
| torch.cuda.__builtins__ = torch.xpu.__builtins__ | |
| torch.cuda.CharTensor = torch.xpu.CharTensor | |
| torch.cuda.List = torch.xpu.List | |
| torch.cuda._lazy_init = torch.xpu._lazy_init | |
| torch.cuda.BFloat16Tensor = torch.xpu.BFloat16Tensor | |
| torch.cuda.DoubleStorage = torch.xpu.DoubleStorage | |
| torch.cuda.ByteTensor = torch.xpu.ByteTensor | |
| torch.cuda.StreamContext = torch.xpu.StreamContext | |
| torch.cuda.ComplexDoubleStorage = torch.xpu.ComplexDoubleStorage | |
| torch.cuda.ShortStorage = torch.xpu.ShortStorage | |
| torch.cuda._lazy_call = torch.xpu._lazy_call | |
| torch.cuda.HalfStorage = torch.xpu.HalfStorage | |
| torch.cuda.random = torch.xpu.random | |
| torch.cuda._device = torch.xpu._device | |
| torch.cuda.classproperty = torch.xpu.classproperty | |
| torch.cuda.__name__ = torch.xpu.__name__ | |
| torch.cuda._device_t = torch.xpu._device_t | |
| torch.cuda.warnings = torch.xpu.warnings | |
| torch.cuda.__spec__ = torch.xpu.__spec__ | |
| torch.cuda.BoolTensor = torch.xpu.BoolTensor | |
| torch.cuda.CharStorage = torch.xpu.CharStorage | |
| torch.cuda.__file__ = torch.xpu.__file__ | |
| torch.cuda._is_in_bad_fork = torch.xpu.lazy_init._is_in_bad_fork | |
| # torch.cuda.is_current_stream_capturing = torch.xpu.is_current_stream_capturing | |
| # Memory: | |
| torch.cuda.memory = torch.xpu.memory | |
| if 'linux' in sys.platform and "WSL2" in os.popen("uname -a").read(): | |
| torch.xpu.empty_cache = lambda: None | |
| torch.cuda.empty_cache = torch.xpu.empty_cache | |
| torch.cuda.memory_stats = torch.xpu.memory_stats | |
| torch.cuda.memory_summary = torch.xpu.memory_summary | |
| torch.cuda.memory_snapshot = torch.xpu.memory_snapshot | |
| torch.cuda.memory_allocated = torch.xpu.memory_allocated | |
| torch.cuda.max_memory_allocated = torch.xpu.max_memory_allocated | |
| torch.cuda.memory_reserved = torch.xpu.memory_reserved | |
| torch.cuda.memory_cached = torch.xpu.memory_reserved | |
| torch.cuda.max_memory_reserved = torch.xpu.max_memory_reserved | |
| torch.cuda.max_memory_cached = torch.xpu.max_memory_reserved | |
| torch.cuda.reset_peak_memory_stats = torch.xpu.reset_peak_memory_stats | |
| torch.cuda.reset_max_memory_cached = torch.xpu.reset_peak_memory_stats | |
| torch.cuda.reset_max_memory_allocated = torch.xpu.reset_peak_memory_stats | |
| torch.cuda.memory_stats_as_nested_dict = torch.xpu.memory_stats_as_nested_dict | |
| torch.cuda.reset_accumulated_memory_stats = torch.xpu.reset_accumulated_memory_stats | |
| # RNG: | |
| torch.cuda.get_rng_state = torch.xpu.get_rng_state | |
| torch.cuda.get_rng_state_all = torch.xpu.get_rng_state_all | |
| torch.cuda.set_rng_state = torch.xpu.set_rng_state | |
| torch.cuda.set_rng_state_all = torch.xpu.set_rng_state_all | |
| torch.cuda.manual_seed = torch.xpu.manual_seed | |
| torch.cuda.manual_seed_all = torch.xpu.manual_seed_all | |
| torch.cuda.seed = torch.xpu.seed | |
| torch.cuda.seed_all = torch.xpu.seed_all | |
| torch.cuda.initial_seed = torch.xpu.initial_seed | |
| # AMP: | |
| torch.cuda.amp = torch.xpu.amp | |
| torch.is_autocast_enabled = torch.xpu.is_autocast_xpu_enabled | |
| torch.get_autocast_gpu_dtype = torch.xpu.get_autocast_xpu_dtype | |
| if not hasattr(torch.cuda.amp, "common"): | |
| torch.cuda.amp.common = contextlib.nullcontext() | |
| torch.cuda.amp.common.amp_definitely_not_available = lambda: False | |
| try: | |
| torch.cuda.amp.GradScaler = torch.xpu.amp.GradScaler | |
| except Exception: # pylint: disable=broad-exception-caught | |
| try: | |
| from .gradscaler import gradscaler_init # pylint: disable=import-outside-toplevel, import-error | |
| gradscaler_init() | |
| torch.cuda.amp.GradScaler = torch.xpu.amp.GradScaler | |
| except Exception: # pylint: disable=broad-exception-caught | |
| torch.cuda.amp.GradScaler = ipex.cpu.autocast._grad_scaler.GradScaler | |
| # C | |
| torch._C._cuda_getCurrentRawStream = ipex._C._getCurrentStream | |
| ipex._C._DeviceProperties.multi_processor_count = ipex._C._DeviceProperties.gpu_eu_count | |
| ipex._C._DeviceProperties.major = 2023 | |
| ipex._C._DeviceProperties.minor = 2 | |
| # Fix functions with ipex: | |
| torch.cuda.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._utils._get_available_device_type = lambda: "xpu" | |
| torch.has_cuda = True | |
| torch.cuda.has_half = True | |
| torch.cuda.is_bf16_supported = lambda *args, **kwargs: True | |
| torch.cuda.is_fp16_supported = lambda *args, **kwargs: True | |
| torch.backends.cuda.is_built = lambda *args, **kwargs: True | |
| torch.version.cuda = "12.1" | |
| torch.cuda.get_device_capability = lambda *args, **kwargs: [12,1] | |
| torch.cuda.get_device_properties.major = 12 | |
| torch.cuda.get_device_properties.minor = 1 | |
| torch.cuda.ipc_collect = lambda *args, **kwargs: None | |
| torch.cuda.utilization = lambda *args, **kwargs: 0 | |
| ipex_hijacks() | |
| if not torch.xpu.has_fp64_dtype() or os.environ.get('IPEX_FORCE_ATTENTION_SLICE', None) is not None: | |
| try: | |
| from .diffusers import ipex_diffusers | |
| ipex_diffusers() | |
| except Exception: # pylint: disable=broad-exception-caught | |
| pass | |
| torch.cuda.is_xpu_hijacked = True | |
| except Exception as e: | |
| return False, e | |
| return True, None | |