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continued cleanup and documentation

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This commit is contained in:
Dan Saunders
2025-01-08 19:15:03 +00:00
parent 929ee15cc3
commit 6e72baf287
42 changed files with 280 additions and 300 deletions
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16
tests/e2e/test_dpo.py
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@@ -9,8 +9,8 @@ from pathlib import Path
import pytest
from axolotl.cli.datasets import load_rl_datasets
from axolotl.common.cli import TrainerCliArgs
from axolotl.common.datasets import load_rl_datasets
from axolotl.train import train
from axolotl.utils.config import normalize_config
from axolotl.utils.dict import DictDefault
@@ -67,7 +67,7 @@ class TestDPOLlamaLora(unittest.TestCase):
cli_args = TrainerCliArgs()
dataset_meta = load_rl_datasets(cfg=cfg, cli_args=cli_args)
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
train(cfg=cfg, dataset_meta=dataset_meta)
check_model_output_exists(Path(temp_dir) / "checkpoint-20", cfg)
@with_temp_dir
@@ -112,7 +112,7 @@ class TestDPOLlamaLora(unittest.TestCase):
cli_args = TrainerCliArgs()
dataset_meta = load_rl_datasets(cfg=cfg, cli_args=cli_args)
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
train(cfg=cfg, dataset_meta=dataset_meta)
check_model_output_exists(Path(temp_dir) / "checkpoint-20", cfg)
@with_temp_dir
@@ -157,7 +157,7 @@ class TestDPOLlamaLora(unittest.TestCase):
cli_args = TrainerCliArgs()
dataset_meta = load_rl_datasets(cfg=cfg, cli_args=cli_args)
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
train(cfg=cfg, dataset_meta=dataset_meta)
check_model_output_exists(Path(temp_dir) / "checkpoint-20", cfg)
@pytest.mark.skip("kto_pair no longer supported in trl")
@@ -202,7 +202,7 @@ class TestDPOLlamaLora(unittest.TestCase):
cli_args = TrainerCliArgs()
dataset_meta = load_rl_datasets(cfg=cfg, cli_args=cli_args)
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
train(cfg=cfg, dataset_meta=dataset_meta)
check_model_output_exists(Path(temp_dir) / "checkpoint-20", cfg)
@with_temp_dir
@@ -246,7 +246,7 @@ class TestDPOLlamaLora(unittest.TestCase):
cli_args = TrainerCliArgs()
dataset_meta = load_rl_datasets(cfg=cfg, cli_args=cli_args)
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
train(cfg=cfg, dataset_meta=dataset_meta)
check_model_output_exists(Path(temp_dir) / "checkpoint-20", cfg)
@with_temp_dir
@@ -293,7 +293,7 @@ class TestDPOLlamaLora(unittest.TestCase):
cli_args = TrainerCliArgs()
dataset_meta = load_rl_datasets(cfg=cfg, cli_args=cli_args)
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
train(cfg=cfg, dataset_meta=dataset_meta)
check_model_output_exists(Path(temp_dir) / "checkpoint-20", cfg)
@pytest.mark.skip(reason="Fix the implementation")
@@ -357,5 +357,5 @@ class TestDPOLlamaLora(unittest.TestCase):
cli_args = TrainerCliArgs()
dataset_meta = load_rl_datasets(cfg=cfg, cli_args=cli_args)
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
train(cfg=cfg, dataset_meta=dataset_meta)
check_model_output_exists(Path(temp_dir) / "checkpoint-20", cfg)