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https://github.com/hiyouga/LLaMA-Factory.git
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fix ci
Former-commit-id: 1173f7fc1dbdcf814650bfdf854ade5212fc4738
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2
.github/workflows/tests.yml
vendored
2
.github/workflows/tests.yml
vendored
@ -29,7 +29,7 @@ jobs:
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os:
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- "ubuntu-latest"
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- "windows-latest"
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- "macos-12"
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- "macos-13"
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runs-on: ${{ matrix.os }}
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@ -37,9 +37,9 @@ def compare_model(model_a: "torch.nn.Module", model_b: "torch.nn.Module", diff_k
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assert set(state_dict_a.keys()) == set(state_dict_b.keys())
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for name in state_dict_a.keys():
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if any(key in name for key in diff_keys):
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assert torch.allclose(state_dict_a[name], state_dict_b[name], rtol=1e-4, atol=1e-5) is False
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assert torch.allclose(state_dict_a[name], state_dict_b[name], rtol=1e-3, atol=1e-4) is False
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else:
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assert torch.allclose(state_dict_a[name], state_dict_b[name], rtol=1e-4, atol=1e-5) is True
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assert torch.allclose(state_dict_a[name], state_dict_b[name], rtol=1e-3, atol=1e-4) is True
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def check_lora_model(model: "LoraModel") -> Tuple[Set[str], Set[str]]:
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@ -52,6 +52,7 @@ INFER_ARGS = {
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CI_OS = os.environ.get("CI_OS", "")
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@pytest.mark.skipif(CI_OS.startswith("windows"), reason="Skip for windows.")
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def test_pissa_train():
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model = load_train_model(**TRAIN_ARGS)
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ref_model = load_reference_model(TINY_LLAMA_PISSA, TINY_LLAMA_PISSA, use_pissa=True, is_trainable=True)
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