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add helper to verify the correct model output file exists (#2245)

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* add helper to verify the correct model output file exists

* more checks using helper

* chore: lint

* fix import and relora model check

* workaround for trl trainer saves

* remove stray print
This commit is contained in:
Wing Lian
2025-01-13 10:43:29 -05:00
committed by GitHub
parent d8b4027200
commit dd26cc3c0f
29 changed files with 116 additions and 111 deletions
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16
tests/e2e/test_dpo.py
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@@ -15,7 +15,7 @@ from axolotl.train import train
from axolotl.utils.config import normalize_config
from axolotl.utils.dict import DictDefault
from .utils import with_temp_dir
from .utils import check_model_output_exists, with_temp_dir
LOG = logging.getLogger("axolotl.tests.e2e")
os.environ["WANDB_DISABLED"] = "true"
@@ -68,7 +68,7 @@ class TestDPOLlamaLora(unittest.TestCase):
dataset_meta = load_rl_datasets(cfg=cfg, cli_args=cli_args)
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
assert (Path(temp_dir) / "checkpoint-20/adapter_model.safetensors").exists()
check_model_output_exists(Path(temp_dir) / "checkpoint-20", cfg)
@with_temp_dir
def test_dpo_nll_lora(self, temp_dir):
@@ -113,7 +113,7 @@ class TestDPOLlamaLora(unittest.TestCase):
dataset_meta = load_rl_datasets(cfg=cfg, cli_args=cli_args)
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
assert (Path(temp_dir) / "checkpoint-20/adapter_model.safetensors").exists()
check_model_output_exists(Path(temp_dir) / "checkpoint-20", cfg)
@with_temp_dir
def test_dpo_use_weighting(self, temp_dir):
@@ -158,7 +158,7 @@ class TestDPOLlamaLora(unittest.TestCase):
dataset_meta = load_rl_datasets(cfg=cfg, cli_args=cli_args)
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
assert (Path(temp_dir) / "checkpoint-20/adapter_model.safetensors").exists()
check_model_output_exists(Path(temp_dir) / "checkpoint-20", cfg)
@pytest.mark.skip("kto_pair no longer supported in trl")
@with_temp_dir
@@ -203,7 +203,7 @@ class TestDPOLlamaLora(unittest.TestCase):
dataset_meta = load_rl_datasets(cfg=cfg, cli_args=cli_args)
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
assert (Path(temp_dir) / "checkpoint-20/adapter_model.safetensors").exists()
check_model_output_exists(Path(temp_dir) / "checkpoint-20", cfg)
@with_temp_dir
def test_ipo_lora(self, temp_dir):
@@ -247,7 +247,7 @@ class TestDPOLlamaLora(unittest.TestCase):
dataset_meta = load_rl_datasets(cfg=cfg, cli_args=cli_args)
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
assert (Path(temp_dir) / "checkpoint-20/adapter_model.safetensors").exists()
check_model_output_exists(Path(temp_dir) / "checkpoint-20", cfg)
@with_temp_dir
def test_orpo_lora(self, temp_dir):
@@ -294,7 +294,7 @@ class TestDPOLlamaLora(unittest.TestCase):
dataset_meta = load_rl_datasets(cfg=cfg, cli_args=cli_args)
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
assert (Path(temp_dir) / "checkpoint-20/adapter_model.safetensors").exists()
check_model_output_exists(Path(temp_dir) / "checkpoint-20", cfg)
@pytest.mark.skip(reason="Fix the implementation")
@with_temp_dir
@@ -358,4 +358,4 @@ class TestDPOLlamaLora(unittest.TestCase):
dataset_meta = load_rl_datasets(cfg=cfg, cli_args=cli_args)
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
assert (Path(temp_dir) / "checkpoint-20/adapter_model.safetensors").exists()
check_model_output_exists(Path(temp_dir) / "checkpoint-20", cfg)