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enable arrow_multitask example on Intel XPU #2867

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Merged
merged 3 commits into from
Oct 27, 2025
+12 −4
Merged

enable arrow_multitask example on Intel XPU #2867

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eb43892
enable arrow_multitask example on Intel XPU
kaixuanliu Oct 24, 2025
2e4bf2f
add device setting:
kaixuanliu Oct 24, 2025
403a499
fix style issue
kaixuanliu Oct 27, 2025
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16 changes: 12 additions & 4 deletions examples/arrow_multitask/arrow_phi3_mini.py
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Original file line number Diff line number Diff line change
Expand Up @@ -186,7 +186,10 @@ def set_seed(seed: int):
random.seed(seed)
np.random.seed(seed)
torch.manual_seed(seed)
torch.cuda.manual_seed_all(seed)
if torch.cuda.is_available():
torch.cuda.manual_seed_all(seed)
elif hasattr(torch, "xpu") and torch.xpu.is_available():
torch.xpu.manual_seed_all(seed)


def compute_loglike_loss(logits, labels, reduction="none"):
Expand Down Expand Up @@ -215,11 +218,16 @@ def compute_loglike_loss(logits, labels, reduction="none"):


def evaluate_on_multi_choice_batched(
eval_dataset, model, tokenizer, ds_name, labels, predictions, args, batch_size=32, max_length=512, device="cuda"
eval_dataset, model, tokenizer, ds_name, labels, predictions, args, batch_size=32, max_length=512, device="auto"
):
# Local import to mirror your original function
model.eval()

if device == "auto":
device = torch.accelerator.current_accelerator().type if hasattr(torch, "accelerator") else "cuda"
else:
device = torch.device(device)

for start in tqdm(
range(0, len(eval_dataset), batch_size), total=(len(eval_dataset) + batch_size - 1) // batch_size
):
Expand Down Expand Up @@ -326,7 +334,7 @@ def evaluate_on_multi_choice_batched(
args,
batch_size=64, # tune this
max_length=512, # tune if options are long
device="cuda",
device="auto",
)
else:
general_adapter_paths = []
Expand Down Expand Up @@ -371,5 +379,5 @@ def evaluate_on_multi_choice_batched(
args,
batch_size=32, # tune this
max_length=512, # tune if options are long
device="cuda",
device="auto",
)
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