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[v1] add batch generator (#9744)

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This commit is contained in:
Yaowei Zheng
2026-01-10 04:24:09 +08:00
committed by GitHub
parent d7d734d54c
commit b2effbd77c
26 changed files with 604 additions and 850 deletions
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6
tests_v1/plugins/model_plugins/test_init_plugin.py
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@@ -21,7 +21,7 @@ from llamafactory.v1.core.model_engine import ModelEngine
def test_init_on_meta():
_, model_args, *_ = get_args(
dict(
model="llamafactory/tiny-random-qwen2.5",
model="llamafactory/tiny-random-qwen3",
init_config={"name": "init_on_meta"},
)
)
@@ -32,7 +32,7 @@ def test_init_on_meta():
def test_init_on_rank0():
_, model_args, *_ = get_args(
dict(
model="llamafactory/tiny-random-qwen2.5",
model="llamafactory/tiny-random-qwen3",
init_config={"name": "init_on_rank0"},
)
)
@@ -46,7 +46,7 @@ def test_init_on_rank0():
def test_init_on_default():
_, model_args, *_ = get_args(
dict(
model="llamafactory/tiny-random-qwen2.5",
model="llamafactory/tiny-random-qwen3",
init_config={"name": "init_on_default"},
)
)

4
tests_v1/plugins/model_plugins/test_kernel_plugin.py
View File

@@ -43,7 +43,7 @@ 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-qwen2.5")
model = AutoModelForCausalLM.from_pretrained("llamafactory/tiny-random-qwen3")
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 +62,7 @@ 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-qwen2.5")
model = AutoModelForCausalLM.from_pretrained("llamafactory/tiny-random-qwen3")
original_rmsnorm_forward = model.model.layers[0].input_layernorm.forward
original_swiglu_forward = model.model.layers[0].mlp.forward