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[v1] add sft (#9752)

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This commit is contained in:
Yaowei Zheng
2026-01-12 03:15:01 +08:00
committed by GitHub
parent 4d3621e3d3
commit 958b9c3468
29 changed files with 439 additions and 305 deletions
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8
tests_v1/plugins/data_plugins/test_converter.py
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@@ -24,8 +24,8 @@ from llamafactory.v1.plugins.data_plugins.converter import DataConverterPlugin
@pytest.mark.parametrize("num_samples", [16])
def test_alpaca_converter(num_samples: int):
data_args = DataArguments(dataset="llamafactory/v1-dataset-info/tiny-supervised-dataset.yaml")
data_engine = DataEngine(data_args)
data_args = DataArguments(train_dataset="llamafactory/v1-dataset-info/tiny-supervised-dataset.yaml")
data_engine = DataEngine(data_args.train_dataset)
original_data = load_dataset("llamafactory/tiny-supervised-dataset", split="train")
indexes = random.choices(range(len(data_engine)), k=num_samples)
for index in indexes:
@@ -73,8 +73,8 @@ def test_sharegpt_converter():
@pytest.mark.parametrize("num_samples", [16])
def test_pair_converter(num_samples: int):
data_args = DataArguments(dataset="llamafactory/v1-dataset-info/orca-dpo-pairs.yaml")
data_engine = DataEngine(data_args)
data_args = DataArguments(train_dataset="llamafactory/v1-dataset-info/orca-dpo-pairs.yaml")
data_engine = DataEngine(data_args.train_dataset)
original_data = load_dataset("HuggingFaceH4/orca_dpo_pairs", split="train_prefs")
indexes = random.choices(range(len(data_engine)), k=num_samples)
for index in indexes:

6
tests_v1/plugins/model_plugins/test_init_plugin.py
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@@ -19,7 +19,7 @@ from llamafactory.v1.core.model_engine import ModelEngine
def test_init_on_meta():
_, model_args, *_ = get_args(
model_args, *_ = get_args(
dict(
model="llamafactory/tiny-random-qwen3",
init_config={"name": "init_on_meta"},
@@ -30,7 +30,7 @@ def test_init_on_meta():
def test_init_on_rank0():
_, model_args, *_ = get_args(
model_args, *_ = get_args(
dict(
model="llamafactory/tiny-random-qwen3",
init_config={"name": "init_on_rank0"},
@@ -44,7 +44,7 @@ def test_init_on_rank0():
def test_init_on_default():
_, model_args, *_ = get_args(
model_args, *_ = get_args(
dict(
model="llamafactory/tiny-random-qwen3",
init_config={"name": "init_on_default"},

6
tests_v1/plugins/model_plugins/test_kernel_plugin.py
View File

@@ -43,7 +43,8 @@ def test_apply_kernel(mock_get_accelerator: MagicMock):
reload_kernels()
from llamafactory.v1.plugins.model_plugins.kernels.interface import apply_default_kernels
model = AutoModelForCausalLM.from_pretrained("llamafactory/tiny-random-qwen3")
# NOTE: use a special model to avoid contamination by other tests
model = AutoModelForCausalLM.from_pretrained("llamafactory/tiny-random-qwen2.5")
original_rmsnorm_forward = model.model.layers[0].input_layernorm.forward
original_swiglu_forward = model.model.layers[0].mlp.forward
model = apply_default_kernels(model=model, include_kernels="npu_fused_rmsnorm")
@@ -62,7 +63,8 @@ def test_apply_all_kernels(mock_get_accelerator: MagicMock):
reload_kernels()
from llamafactory.v1.plugins.model_plugins.kernels.interface import apply_default_kernels
model = AutoModelForCausalLM.from_pretrained("llamafactory/tiny-random-qwen3")
# NOTE: use a special model to avoid contamination by other tests
model = AutoModelForCausalLM.from_pretrained("llamafactory/tiny-random-qwen2.5")
original_rmsnorm_forward = model.model.layers[0].input_layernorm.forward
original_swiglu_forward = model.model.layers[0].mlp.forward