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Autodetect IPEX

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Disty0
2023-07-04 23:37:36 +03:00
parent 875d0db103
commit 966eed8dd9
15 changed files with 55 additions and 55 deletions
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modules/hypernetworks/hypernetwork.py
+3 -3
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@@ -589,7 +589,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
print("Cannot resume from saved optimizer!")
print(e)
if shared.cmd_opts.use_ipex:
if devices.backend == 'ipex':
scaler = torch.xpu.amp.GradScaler()
else:
scaler = torch.cuda.amp.GradScaler()
@@ -706,7 +706,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
hypernetwork.eval()
rng_state = torch.get_rng_state()
cuda_rng_state = None
if shared.cmd_opts.use_ipex:
if devices.backend == 'ipex':
cuda_rng_state = torch.xpu.get_rng_state_all()
elif torch.cuda.is_available():
cuda_rng_state = torch.cuda.get_rng_state_all()
@@ -745,7 +745,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
shared.sd_model.cond_stage_model.to(devices.cpu)
shared.sd_model.first_stage_model.to(devices.cpu)
torch.set_rng_state(rng_state)
if shared.cmd_opts.use_ipex:
if devices.backend == 'ipex':
torch.xpu.set_rng_state_all(cuda_rng_state)
elif torch.cuda.is_available():
torch.cuda.set_rng_state_all(cuda_rng_state)