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Handle device init failures and record that as an error, if the GPU has less than 3 gb of VRAM

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cmdr2 2022-11-11 16:13:27 +05:30
parent c13bccc7ae
commit 3fdd8d91e2
2 changed files with 13 additions and 19 deletions
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26
ui/sd_internal/runtime.py
View File

@ -144,22 +144,21 @@ def device_init(device_selection):
thread_data.device = 'cpu' thread_data.device = 'cpu'
thread_data.device_name = get_processor_name() thread_data.device_name = get_processor_name()
print('Render device CPU available as', thread_data.device_name) print('Render device CPU available as', thread_data.device_name)
return return True
if not torch.cuda.is_available(): if not torch.cuda.is_available():
if device_selection == 'auto': if device_selection == 'auto':
print('WARNING: Could not find a compatible GPU. Using the CPU, but this will be very slow!') print('WARNING: Could not find a compatible GPU. Using the CPU, but this will be very slow!')
thread_data.device = 'cpu' thread_data.device = 'cpu'
thread_data.device_name = get_processor_name() thread_data.device_name = get_processor_name()
return return True
else: else:
raise EnvironmentError(f'Could not find a compatible GPU for the requested device_selection: {device_selection}!') raise EnvironmentError(f'Could not find a compatible GPU for the requested device_selection: {device_selection}!')
if device_selection == 'auto': if device_selection == 'auto':
device_count = torch.cuda.device_count() device_count = torch.cuda.device_count()
if device_count == 1: if device_count == 1 and device_select('cuda:0'):
device_select('cuda:0')
torch.cuda.device('cuda:0') torch.cuda.device('cuda:0')
return return True
print('Autoselecting GPU. Using most free memory.') print('Autoselecting GPU. Using most free memory.')
max_mem_free = 0 max_mem_free = 0
@ -177,23 +176,14 @@ def device_init(device_selection):
if best_device and device_select(best_device): if best_device and device_select(best_device):
print(f'Setting {device} as active') print(f'Setting {device} as active')
torch.cuda.device(device) torch.cuda.device(device)
return return True
if device_select(device_selection): if device_selection != 'auto' and device_select(device_selection):
print(f'Setting {device_selection} as active') print(f'Setting {device_selection} as active')
torch.cuda.device(device_selection) torch.cuda.device(device_selection)
return return True
# By default use current device. return False
print('Checking current GPU...')
device = f'cuda:{torch.cuda.current_device()}'
device_name = torch.cuda.get_device_name(device)
print(f'{device} detected: {device_name}')
if device_select(device):
return
print('WARNING: No compatible GPU found. Using the CPU, but this will be very slow!')
thread_data.device = 'cpu'
thread_data.device_name = get_processor_name()
def load_model_ckpt(): def load_model_ckpt():
if not thread_data.ckpt_file: raise ValueError(f'Thread ckpt_file is undefined.') if not thread_data.ckpt_file: raise ValueError(f'Thread ckpt_file is undefined.')

6
ui/sd_internal/task_manager.py
View File

@ -253,7 +253,11 @@ def thread_render(device):
global current_state, current_state_error, current_model_path, current_vae_path global current_state, current_state_error, current_model_path, current_vae_path
from . import runtime from . import runtime
try: try:
runtime.device_init(device) if not runtime.device_init(device):
weak_thread_data[threading.current_thread()] = {
'error': f'Could not start on the selected device: {device}'
}
return
except Exception as e: except Exception as e:
print(traceback.format_exc()) print(traceback.format_exc())
weak_thread_data[threading.current_thread()] = { weak_thread_data[threading.current_thread()] = {