mirror of https://github.com/vladmandic/automatic
63 lines
2.6 KiB
Python
63 lines
2.6 KiB
Python
import sys
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from typing import Union
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import torch
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from torch._prims_common import DeviceLikeType
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from modules import shared, devices, zluda_installer
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from modules.zluda_installer import core, default_agent # pylint: disable=unused-import
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from modules.onnx_impl.execution_providers import available_execution_providers, ExecutionProvider
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PLATFORM = sys.platform
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do_nothing = lambda _: None # pylint: disable=unnecessary-lambda-assignment
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def test(device: DeviceLikeType) -> Union[Exception, None]:
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device = torch.device(device)
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try:
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ten1 = torch.randn((2, 4,), device=device)
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ten2 = torch.randn((4, 8,), device=device)
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out = torch.mm(ten1, ten2)
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assert out.sum().is_nonzero()
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return None
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except Exception as e:
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return e
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def initialize_zluda():
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shared.cmd_opts.device_id = None
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if not devices.cuda_ok or not devices.has_zluda():
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return
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torch.backends.cudnn.enabled = zluda_installer.MIOpen_enabled
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if hasattr(torch.backends.cuda, "enable_cudnn_sdp"):
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if not zluda_installer.MIOpen_enabled:
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torch.backends.cuda.enable_cudnn_sdp(False)
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torch.backends.cuda.enable_cudnn_sdp = do_nothing
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else:
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torch.backends.cuda.enable_cudnn_sdp = do_nothing
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torch.backends.cuda.enable_flash_sdp(False)
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torch.backends.cuda.enable_flash_sdp = torch.backends.cuda.enable_cudnn_sdp
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torch.backends.cuda.enable_mem_efficient_sdp(False)
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torch.backends.cuda.enable_mem_efficient_sdp = do_nothing
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# ONNX Runtime is not supported
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try:
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import onnxruntime as ort
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ort.capi._pybind_state.get_available_providers = lambda: [v for v in available_execution_providers if v != ExecutionProvider.CUDA] # pylint: disable=protected-access
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ort.get_available_providers = ort.capi._pybind_state.get_available_providers # pylint: disable=protected-access
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if shared.opts.onnx_execution_provider == ExecutionProvider.CUDA:
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shared.opts.onnx_execution_provider = ExecutionProvider.CPU
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except Exception as e:
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shared.log.warning(f'ZLUDA ONNX runtime: {e}')
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shared.opts.onnx_execution_provider = ExecutionProvider.CPU
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device = devices.get_optimal_device()
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result = test(device)
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if result is not None:
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shared.log.warning(f'ZLUDA device failed to pass basic operation test: index={device.index}, device_name={torch.cuda.get_device_name(device)}')
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shared.log.error(result)
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torch.cuda.is_available = lambda: False
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devices.cuda_ok = False
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devices.backend = 'cpu'
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devices.device = devices.cpu
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