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[xpu] extend runs_on test markers to include xpu #10445

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[xpu] extend runs_on test markers to include xpu #10445

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c926777
[xpu] extend runs_on test markers to include xpu
Apr 29, 2026
477f57d
Merge branch 'main' into xpu-accelerate-configs-and-test-support
singhalshubham03 Jun 29, 2026
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2 changes: 1 addition & 1 deletion tests/data/processor/test_feedback.py
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Expand Up @@ -43,7 +43,7 @@
}


@pytest.mark.runs_on(["cpu", "mps"])
@pytest.mark.runs_on(["cpu", "mps", "xpu"])
@pytest.mark.parametrize("num_samples", [16])
def test_feedback_data(num_samples: int):
train_dataset = load_dataset_module(**TRAIN_ARGS)["train_dataset"]
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2 changes: 1 addition & 1 deletion tests/data/processor/test_pairwise.py
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Expand Up @@ -52,7 +52,7 @@ def _convert_sharegpt_to_openai(messages: list[dict[str, str]]) -> list[dict[str
return new_messages


@pytest.mark.runs_on(["cpu", "mps"])
@pytest.mark.runs_on(["cpu", "mps", "xpu"])
@pytest.mark.parametrize("num_samples", [16])
def test_pairwise_data(num_samples: int):
train_dataset = load_dataset_module(**TRAIN_ARGS)["train_dataset"]
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2 changes: 1 addition & 1 deletion tests/data/processor/test_processor_utils.py
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Expand Up @@ -18,7 +18,7 @@
from llamafactory.data.processor.processor_utils import infer_seqlen


@pytest.mark.runs_on(["cpu", "mps"])
@pytest.mark.runs_on(["cpu", "mps", "xpu"])
@pytest.mark.parametrize(
"test_input,test_output",
[
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8 changes: 4 additions & 4 deletions tests/data/processor/test_supervised.py
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Expand Up @@ -43,7 +43,7 @@
}


@pytest.mark.runs_on(["cpu", "mps"])
@pytest.mark.runs_on(["cpu", "mps", "xpu"])
@pytest.mark.parametrize("num_samples", [16])
def test_supervised_single_turn(num_samples: int):
train_dataset = load_dataset_module(dataset_dir="ONLINE", dataset=TINY_DATA, **TRAIN_ARGS)["train_dataset"]
Expand Down Expand Up @@ -72,7 +72,7 @@ def test_supervised_single_turn(num_samples: int):
assert train_dataset["labels"][index] == ref_label_ids


@pytest.mark.runs_on(["cpu", "mps"])
@pytest.mark.runs_on(["cpu", "mps", "xpu"])
@pytest.mark.parametrize("num_samples", [8])
def test_supervised_multi_turn(num_samples: int):
train_dataset = load_dataset_module(dataset_dir="REMOTE:" + DEMO_DATA, dataset="system_chat", **TRAIN_ARGS)[
Expand All @@ -90,7 +90,7 @@ def test_supervised_multi_turn(num_samples: int):
assert train_dataset["input_ids"][index] == ref_input_ids


@pytest.mark.runs_on(["cpu", "mps"])
@pytest.mark.runs_on(["cpu", "mps", "xpu"])
@pytest.mark.parametrize("num_samples", [4])
def test_supervised_train_on_prompt(num_samples: int):
train_dataset = load_dataset_module(
Expand All @@ -108,7 +108,7 @@ def test_supervised_train_on_prompt(num_samples: int):
assert train_dataset["labels"][index] == ref_input_ids


@pytest.mark.runs_on(["cpu", "mps"])
@pytest.mark.runs_on(["cpu", "mps", "xpu"])
@pytest.mark.parametrize("num_samples", [4])
def test_supervised_mask_history(num_samples: int):
train_dataset = load_dataset_module(
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2 changes: 1 addition & 1 deletion tests/data/processor/test_unsupervised.py
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Expand Up @@ -47,7 +47,7 @@
}


@pytest.mark.runs_on(["cpu", "mps"])
@pytest.mark.runs_on(["cpu", "mps", "xpu"])
@pytest.mark.parametrize("num_samples", [16])
def test_unsupervised_data(num_samples: int):
train_dataset = load_dataset_module(**TRAIN_ARGS)["train_dataset"]
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8 changes: 4 additions & 4 deletions tests/data/test_collator.py
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Expand Up @@ -32,7 +32,7 @@
TINY_LLAMA3 = os.getenv("TINY_LLAMA3", "llamafactory/tiny-random-Llama-3")


@pytest.mark.runs_on(["cpu", "mps"])
@pytest.mark.runs_on(["cpu", "mps", "xpu"])
def test_base_collator():
model_args, data_args, *_ = get_infer_args({"model_name_or_path": TINY_LLAMA3, "template": "default"})
tokenizer_module = load_tokenizer(model_args)
Expand Down Expand Up @@ -76,7 +76,7 @@ def test_base_collator():
assert batch_input[k].eq(torch.tensor(expected_input[k])).all()


@pytest.mark.runs_on(["cpu", "mps"])
@pytest.mark.runs_on(["cpu", "mps", "xpu"])
def test_multimodal_collator():
model_args, data_args, *_ = get_infer_args(
{"model_name_or_path": "Qwen/Qwen2-VL-2B-Instruct", "template": "qwen2_vl"}
Expand Down Expand Up @@ -270,7 +270,7 @@ def _get_expected_position_ids(
return torch.cat(all_position_ids, dim=-1)


@pytest.mark.runs_on(["cpu", "mps"])
@pytest.mark.runs_on(["cpu", "mps", "xpu"])
def test_multimodal_collator_with_packing():
model_args, data_args, *_ = get_infer_args(
{"model_name_or_path": "Qwen/Qwen2-VL-2B-Instruct", "template": "qwen2_vl"}
Expand Down Expand Up @@ -322,7 +322,7 @@ def test_multimodal_collator_with_packing():
assert batch_input["position_ids"][1:, :, :valid_len].eq(expected_position_ids).all()


@pytest.mark.runs_on(["cpu"])
@pytest.mark.runs_on(["cpu", "xpu"])
def test_4d_attention_mask():
o = 0.0
x = torch.finfo(torch.float16).min
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4 changes: 2 additions & 2 deletions tests/data/test_converter.py
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Expand Up @@ -20,7 +20,7 @@
from llamafactory.hparams import DataArguments


@pytest.mark.runs_on(["cpu", "mps"])
@pytest.mark.runs_on(["cpu", "mps", "xpu"])
def test_alpaca_converter():
dataset_attr = DatasetAttr("hf_hub", "llamafactory/tiny-supervised-dataset")
data_args = DataArguments()
Expand All @@ -41,7 +41,7 @@ def test_alpaca_converter():
}


@pytest.mark.runs_on(["cpu", "mps"])
@pytest.mark.runs_on(["cpu", "mps", "xpu"])
def test_sharegpt_converter():
dataset_attr = DatasetAttr("hf_hub", "llamafactory/tiny-supervised-dataset")
data_args = DataArguments()
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