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| import os |
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| import pytest |
| from transformers.utils import is_flash_attn_2_available, is_torch_sdpa_available |
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| from llamafactory.extras.packages import is_transformers_version_greater_than |
| from llamafactory.train.test_utils import load_infer_model |
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| TINY_LLAMA3 = os.getenv("TINY_LLAMA3", "llamafactory/tiny-random-Llama-3") |
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| INFER_ARGS = { |
| "model_name_or_path": TINY_LLAMA3, |
| "template": "llama3", |
| } |
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| @pytest.mark.xfail(is_transformers_version_greater_than("4.48"), reason="Attention refactor.") |
| def test_attention(): |
| attention_available = ["disabled"] |
| if is_torch_sdpa_available(): |
| attention_available.append("sdpa") |
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| if is_flash_attn_2_available(): |
| attention_available.append("fa2") |
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| llama_attention_classes = { |
| "disabled": "LlamaAttention", |
| "sdpa": "LlamaSdpaAttention", |
| "fa2": "LlamaFlashAttention2", |
| } |
| for requested_attention in attention_available: |
| model = load_infer_model(flash_attn=requested_attention, **INFER_ARGS) |
| for module in model.modules(): |
| if "Attention" in module.__class__.__name__: |
| assert module.__class__.__name__ == llama_attention_classes[requested_attention] |
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