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https://github.com/hiyouga/LLaMA-Factory.git
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fix ci
Former-commit-id: 2f939b708f7f183f87aca67aa076db33a3c8a610
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2
.github/workflows/tests.yml
vendored
2
.github/workflows/tests.yml
vendored
@ -38,7 +38,7 @@ jobs:
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env:
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env:
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HF_TOKEN: ${{ secrets.HF_TOKEN }}
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HF_TOKEN: ${{ secrets.HF_TOKEN }}
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CI_OS: ${{ matrix.os }}
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OS_NAME: ${{ matrix.os }}
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steps:
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steps:
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- name: Checkout
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- name: Checkout
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@ -158,7 +158,7 @@ def test_qwen_template():
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_check_template("Qwen/Qwen2-7B-Instruct", "qwen", prompt_str, answer_str, extra_str="\n")
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_check_template("Qwen/Qwen2-7B-Instruct", "qwen", prompt_str, answer_str, extra_str="\n")
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@pytest.mark.skip(reason="The fast tokenizer of Yi model is corrupted.")
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@pytest.mark.xfail(reason="The fast tokenizer of Yi model is corrupted.")
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def test_yi_template():
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def test_yi_template():
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prompt_str = (
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prompt_str = (
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"<|im_start|>user\nHow are you<|im_end|>\n"
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"<|im_start|>user\nHow are you<|im_end|>\n"
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@ -36,7 +36,6 @@ TRAIN_ARGS = {
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"overwrite_output_dir": True,
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"overwrite_output_dir": True,
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"per_device_train_batch_size": 1,
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"per_device_train_batch_size": 1,
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"max_steps": 1,
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"max_steps": 1,
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"fp16": True,
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}
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}
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INFER_ARGS = {
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INFER_ARGS = {
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@ -48,18 +47,20 @@ INFER_ARGS = {
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"export_dir": "llama3_export",
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"export_dir": "llama3_export",
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}
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}
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OS_NAME = os.environ.get("OS_NAME", "")
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@pytest.mark.parametrize(
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@pytest.mark.parametrize(
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"stage,dataset",
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"stage,dataset",
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[
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[
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("pt", "c4_demo"),
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("pt", "c4_demo"),
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("sft", "alpaca_en_demo"),
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("sft", "alpaca_en_demo"),
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("rm", "dpo_en_demo"),
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pytest.param("rm", "dpo_en_demo", marks=pytest.mark.xfail(OS_NAME.startswith("windows"), reason="OS error.")),
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("dpo", "dpo_en_demo"),
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("dpo", "dpo_en_demo"),
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("kto", "kto_en_demo"),
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("kto", "kto_en_demo"),
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],
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],
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)
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)
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def test_train(stage: str, dataset: str):
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def test_run_exp(stage: str, dataset: str):
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output_dir = "train_{}".format(stage)
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output_dir = "train_{}".format(stage)
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run_exp({"stage": stage, "dataset": dataset, "output_dir": output_dir, **TRAIN_ARGS})
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run_exp({"stage": stage, "dataset": dataset, "output_dir": output_dir, **TRAIN_ARGS})
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assert os.path.exists(output_dir)
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assert os.path.exists(output_dir)
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@ -49,17 +49,17 @@ INFER_ARGS = {
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"infer_dtype": "float16",
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"infer_dtype": "float16",
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}
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}
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CI_OS = os.environ.get("CI_OS", "")
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OS_NAME = os.environ.get("OS_NAME", "")
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@pytest.mark.skipif(CI_OS.startswith("windows"), reason="Skip for windows.")
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@pytest.mark.xfail(OS_NAME.startswith("windows"), reason="Known connection error on Windows.")
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def test_pissa_train():
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def test_pissa_train():
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model = load_train_model(**TRAIN_ARGS)
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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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ref_model = load_reference_model(TINY_LLAMA_PISSA, TINY_LLAMA_PISSA, use_pissa=True, is_trainable=True)
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compare_model(model, ref_model)
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compare_model(model, ref_model)
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@pytest.mark.skipif(CI_OS.startswith("windows"), reason="Skip for windows.")
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@pytest.mark.xfail(OS_NAME.startswith("windows"), reason="Known connection error on Windows.")
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def test_pissa_inference():
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def test_pissa_inference():
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model = load_infer_model(**INFER_ARGS)
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model = load_infer_model(**INFER_ARGS)
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ref_model = load_reference_model(TINY_LLAMA_PISSA, TINY_LLAMA_PISSA, use_pissa=True, is_trainable=False)
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ref_model = load_reference_model(TINY_LLAMA_PISSA, TINY_LLAMA_PISSA, use_pissa=True, is_trainable=False)
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