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https://github.com/hiyouga/LLaMA-Factory.git
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[xpu] add Intel XPU support to test infrastructure and runs_on markers (#10835)
Co-authored-by: Claude Opus 5 <noreply@anthropic.com>
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@@ -32,7 +32,7 @@ from llamafactory.model import load_tokenizer
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TINY_LLAMA3 = os.getenv("TINY_LLAMA3", "llamafactory/tiny-random-Llama-3")
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@pytest.mark.runs_on(["cpu", "mps"])
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@pytest.mark.runs_on(["cpu", "mps", "xpu"])
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def test_base_collator():
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model_args, data_args, *_ = get_infer_args({"model_name_or_path": TINY_LLAMA3, "template": "default"})
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tokenizer_module = load_tokenizer(model_args)
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@@ -76,7 +76,7 @@ def test_base_collator():
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assert batch_input[k].eq(torch.tensor(expected_input[k])).all()
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@pytest.mark.runs_on(["cpu", "mps"])
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@pytest.mark.runs_on(["cpu", "mps", "xpu"])
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def test_multimodal_collator():
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model_args, data_args, *_ = get_infer_args(
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{"model_name_or_path": "Qwen/Qwen2-VL-2B-Instruct", "template": "qwen2_vl"}
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@@ -270,7 +270,7 @@ def _get_expected_position_ids(
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return torch.cat(all_position_ids, dim=-1)
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@pytest.mark.runs_on(["cpu", "mps"])
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@pytest.mark.runs_on(["cpu", "mps", "xpu"])
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def test_multimodal_collator_with_packing():
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model_args, data_args, *_ = get_infer_args(
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{"model_name_or_path": "Qwen/Qwen2-VL-2B-Instruct", "template": "qwen2_vl"}
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@@ -322,7 +322,7 @@ def test_multimodal_collator_with_packing():
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assert batch_input["position_ids"][1:, :, :valid_len].eq(expected_position_ids).all()
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@pytest.mark.runs_on(["cpu"])
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@pytest.mark.runs_on(["cpu", "xpu"])
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def test_4d_attention_mask():
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o = 0.0
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x = torch.finfo(torch.float16).min
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