tocmo0nlord/axolotl
1
0
Fork 0
Code Issues Pull Requests Actions 3 Packages Projects Releases Wiki Activity

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

Browse Source 
* 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
Download Patch File Download Diff File Expand all files Collapse all files

9
tests/e2e/test_optimizers.py
View File

@@ -5,7 +5,6 @@ E2E tests for custom optimizers using Llama
import logging
import os
import unittest
from pathlib import Path
from axolotl.cli import load_datasets
from axolotl.common.cli import TrainerCliArgs
@@ -13,7 +12,7 @@ from axolotl.train import train
from axolotl.utils.config import normalize_config
from axolotl.utils.dict import DictDefault
from .utils import require_torch_2_5_1, with_temp_dir
from .utils import check_model_output_exists, require_torch_2_5_1, with_temp_dir
LOG = logging.getLogger("axolotl.tests.e2e")
os.environ["WANDB_DISABLED"] = "true"
@@ -65,7 +64,7 @@ class TestCustomOptimizers(unittest.TestCase):
dataset_meta = load_datasets(cfg=cfg, cli_args=cli_args)
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
assert (Path(temp_dir) / "adapter_model.bin").exists()
check_model_output_exists(temp_dir, cfg)
@with_temp_dir
@require_torch_2_5_1
@@ -109,7 +108,7 @@ class TestCustomOptimizers(unittest.TestCase):
dataset_meta = load_datasets(cfg=cfg, cli_args=cli_args)
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
assert (Path(temp_dir) / "adapter_model.bin").exists()
check_model_output_exists(temp_dir, cfg)
@with_temp_dir
def test_fft_schedule_free_adamw(self, temp_dir):
@@ -145,4 +144,4 @@ class TestCustomOptimizers(unittest.TestCase):
dataset_meta = load_datasets(cfg=cfg, cli_args=cli_args)
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
assert (Path(temp_dir) / "model.safetensors").exists()
check_model_output_exists(temp_dir, cfg)