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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.nn.Module.cuda = torch.nn.Module.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_subslice_count
ipex._C._DeviceProperties.major = 2024
ipex._C._DeviceProperties.minor = 0
# 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
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