forked from p04798526/LLaMA-Factory-Mirror
fix tol
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@ -213,6 +213,7 @@ def convert_pissa_adapter(
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safe_serialization=training_args.save_safetensors,
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convert_pissa_to_lora=pissa_init_dir,
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)
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# TODO: the model is applied pissa again unexpectedly
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unwrapped_model.load_adapter(pissa_backup_dir, "default", is_trainable=True)
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unwrapped_model.set_adapter("default")
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@ -41,7 +41,7 @@ def compare_model(model_a: "torch.nn.Module", model_b: "torch.nn.Module"):
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state_dict_b = model_b.state_dict()
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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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assert torch.allclose(state_dict_a[name], state_dict_b[name])
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assert torch.allclose(state_dict_a[name], state_dict_b[name], rtol=1e-4, atol=1e-5)
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@pytest.fixture
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@ -67,9 +67,9 @@ 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]) is False
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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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else:
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assert torch.allclose(state_dict_a[name], state_dict_b[name]) is True
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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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@pytest.fixture
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@ -59,7 +59,7 @@ def compare_model(model_a: "torch.nn.Module", model_b: "torch.nn.Module"):
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state_dict_b = model_b.state_dict()
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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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assert torch.allclose(state_dict_a[name], state_dict_b[name], rtol=1e-3, atol=1e-3)
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assert torch.allclose(state_dict_a[name], state_dict_b[name], rtol=1e-4, atol=1e-5)
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def test_pissa_init():
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