Commit 7499148a authored by Nuullll's avatar Nuullll

Disable ipex autocast due to its bad perf

parent 8b40f475
...@@ -70,6 +70,7 @@ parser.add_argument("--opt-sdp-no-mem-attention", action='store_true', help="pre ...@@ -70,6 +70,7 @@ parser.add_argument("--opt-sdp-no-mem-attention", action='store_true', help="pre
parser.add_argument("--disable-opt-split-attention", action='store_true', help="prefer no cross-attention layer optimization for automatic choice of optimization") parser.add_argument("--disable-opt-split-attention", action='store_true', help="prefer no cross-attention layer optimization for automatic choice of optimization")
parser.add_argument("--disable-nan-check", action='store_true', help="do not check if produced images/latent spaces have nans; useful for running without a checkpoint in CI") parser.add_argument("--disable-nan-check", action='store_true', help="do not check if produced images/latent spaces have nans; useful for running without a checkpoint in CI")
parser.add_argument("--use-cpu", nargs='+', help="use CPU as torch device for specified modules", default=[], type=str.lower) parser.add_argument("--use-cpu", nargs='+', help="use CPU as torch device for specified modules", default=[], type=str.lower)
parser.add_argument("--use-ipex", action="store_true", help="use Intel XPU as torch device")
parser.add_argument("--disable-model-loading-ram-optimization", action='store_true', help="disable an optimization that reduces RAM use when loading a model") parser.add_argument("--disable-model-loading-ram-optimization", action='store_true', help="disable an optimization that reduces RAM use when loading a model")
parser.add_argument("--listen", action='store_true', help="launch gradio with 0.0.0.0 as server name, allowing to respond to network requests") parser.add_argument("--listen", action='store_true', help="launch gradio with 0.0.0.0 as server name, allowing to respond to network requests")
parser.add_argument("--port", type=int, help="launch gradio with given server port, you need root/admin rights for ports < 1024, defaults to 7860 if available", default=None) parser.add_argument("--port", type=int, help="launch gradio with given server port, you need root/admin rights for ports < 1024, defaults to 7860 if available", default=None)
......
...@@ -3,11 +3,18 @@ import contextlib ...@@ -3,11 +3,18 @@ import contextlib
from functools import lru_cache from functools import lru_cache
import torch import torch
from modules import errors, shared, xpu_specific from modules import errors, shared
if sys.platform == "darwin": if sys.platform == "darwin":
from modules import mac_specific from modules import mac_specific
if shared.cmd_opts.use_ipex:
from modules import xpu_specific
def has_xpu() -> bool:
return shared.cmd_opts.use_ipex and xpu_specific.has_xpu
def has_mps() -> bool: def has_mps() -> bool:
if sys.platform != "darwin": if sys.platform != "darwin":
...@@ -30,7 +37,7 @@ def get_optimal_device_name(): ...@@ -30,7 +37,7 @@ def get_optimal_device_name():
if has_mps(): if has_mps():
return "mps" return "mps"
if xpu_specific.has_ipex: if has_xpu():
return xpu_specific.get_xpu_device_string() return xpu_specific.get_xpu_device_string()
return "cpu" return "cpu"
...@@ -57,6 +64,9 @@ def torch_gc(): ...@@ -57,6 +64,9 @@ def torch_gc():
if has_mps(): if has_mps():
mac_specific.torch_mps_gc() mac_specific.torch_mps_gc()
if has_xpu():
xpu_specific.torch_xpu_gc()
def enable_tf32(): def enable_tf32():
if torch.cuda.is_available(): if torch.cuda.is_available():
...@@ -103,15 +113,11 @@ def autocast(disable=False): ...@@ -103,15 +113,11 @@ def autocast(disable=False):
if dtype == torch.float32 or shared.cmd_opts.precision == "full": if dtype == torch.float32 or shared.cmd_opts.precision == "full":
return contextlib.nullcontext() return contextlib.nullcontext()
if xpu_specific.has_xpu:
return torch.autocast("xpu")
return torch.autocast("cuda") return torch.autocast("cuda")
def without_autocast(disable=False): def without_autocast(disable=False):
device_type = "xpu" if xpu_specific.has_xpu else "cuda" return torch.autocast("cuda", enabled=False) if torch.is_autocast_enabled() and not disable else contextlib.nullcontext()
return torch.autocast(device_type, enabled=False) if torch.is_autocast_enabled() and not disable else contextlib.nullcontext()
class NansException(Exception): class NansException(Exception):
......
import contextlib
from modules import shared from modules import shared
from modules.sd_hijack_utils import CondFunc from modules.sd_hijack_utils import CondFunc
...@@ -10,33 +9,42 @@ try: ...@@ -10,33 +9,42 @@ try:
except Exception: except Exception:
pass pass
def check_for_xpu():
if not has_ipex:
return False
return hasattr(torch, 'xpu') and torch.xpu.is_available() def check_for_xpu():
return has_ipex and hasattr(torch, 'xpu') and torch.xpu.is_available()
has_xpu = check_for_xpu()
def get_xpu_device_string(): def get_xpu_device_string():
if shared.cmd_opts.device_id is not None: if shared.cmd_opts.device_id is not None:
return f"xpu:{shared.cmd_opts.device_id}" return f"xpu:{shared.cmd_opts.device_id}"
return "xpu" return "xpu"
def return_null_context(*args, **kwargs): # pylint: disable=unused-argument
return contextlib.nullcontext() def torch_xpu_gc():
with torch.xpu.device(get_xpu_device_string()):
torch.xpu.empty_cache()
has_xpu = check_for_xpu()
if has_xpu: if has_xpu:
# W/A for https://github.com/intel/intel-extension-for-pytorch/issues/452: torch.Generator API doesn't support XPU device
CondFunc('torch.Generator', CondFunc('torch.Generator',
lambda orig_func, device=None: torch.xpu.Generator(device), lambda orig_func, device=None: torch.xpu.Generator(device),
lambda orig_func, device=None: device is not None and device != torch.device("cpu") and device != "cpu") lambda orig_func, device=None: device is not None and device.type == "xpu")
# W/A for some OPs that could not handle different input dtypes
CondFunc('torch.nn.functional.layer_norm', CondFunc('torch.nn.functional.layer_norm',
lambda orig_func, input, normalized_shape=None, weight=None, *args, **kwargs: lambda orig_func, input, normalized_shape=None, weight=None, *args, **kwargs:
orig_func(input.to(weight.data.dtype), normalized_shape, weight, *args, **kwargs), orig_func(input.to(weight.data.dtype), normalized_shape, weight, *args, **kwargs),
lambda orig_func, input, normalized_shape=None, weight=None, *args, **kwargs: lambda orig_func, input, normalized_shape=None, weight=None, *args, **kwargs:
weight is not None and input.dtype != weight.data.dtype) weight is not None and input.dtype != weight.data.dtype)
CondFunc('torch.nn.modules.GroupNorm.forward', CondFunc('torch.nn.modules.GroupNorm.forward',
lambda orig_func, self, input: orig_func(self, input.to(self.weight.data.dtype)), lambda orig_func, self, input: orig_func(self, input.to(self.weight.data.dtype)),
lambda orig_func, self, input: input.dtype != self.weight.data.dtype) lambda orig_func, self, input: input.dtype != self.weight.data.dtype)
CondFunc('torch.nn.modules.linear.Linear.forward',
lambda orig_func, self, input: orig_func(self, input.to(self.weight.data.dtype)),
lambda orig_func, self, input: input.dtype != self.weight.data.dtype)
CondFunc('torch.nn.modules.conv.Conv2d.forward',
lambda orig_func, self, input: orig_func(self, input.to(self.weight.data.dtype)),
lambda orig_func, self, input: input.dtype != self.weight.data.dtype)
@echo off
set PYTHON=
@REM The "Nuullll/intel-extension-for-pytorch" wheels were built from IPEX source for Intel Arc GPU: https://github.com/intel/intel-extension-for-pytorch/tree/xpu-main
@REM This is NOT an Intel official release so please use it at your own risk!!
@REM See https://github.com/Nuullll/intel-extension-for-pytorch/releases/tag/v2.0.110%2Bxpu-master%2Bdll-bundle for details.
@REM
@REM Strengths (over official IPEX 2.0.110 windows release):
@REM - AOT build (for Arc GPU only) to eliminate JIT compilation overhead: https://github.com/intel/intel-extension-for-pytorch/issues/399
@REM - Bundles minimal oneAPI 2023.2 dependencies into the python wheels, so users don't need to install oneAPI for the whole system.
@REM - Provides a compatible torchvision wheel: https://github.com/intel/intel-extension-for-pytorch/issues/465
@REM Limitation:
@REM - Only works for python 3.10
set "TORCH_COMMAND=pip install https://github.com/Nuullll/intel-extension-for-pytorch/releases/download/v2.0.110%%2Bxpu-master%%2Bdll-bundle/torch-2.0.0a0+gite9ebda2-cp310-cp310-win_amd64.whl https://github.com/Nuullll/intel-extension-for-pytorch/releases/download/v2.0.110%%2Bxpu-master%%2Bdll-bundle/torchvision-0.15.2a0+fa99a53-cp310-cp310-win_amd64.whl https://github.com/Nuullll/intel-extension-for-pytorch/releases/download/v2.0.110%%2Bxpu-master%%2Bdll-bundle/intel_extension_for_pytorch-2.0.110+gitc6ea20b-cp310-cp310-win_amd64.whl"
set GIT=
set VENV_DIR=
set "COMMANDLINE_ARGS=--use-ipex --skip-torch-cuda-test --skip-version-check --opt-sdp-attention"
call webui.bat
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