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replace tensorboard checks with helper function (#2120) [skip ci]

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* replace tensorboard checks with helper function

* move helper function

* use relative
This commit is contained in:
Wing Lian
2024-12-03 21:06:20 -05:00
committed by GitHub
parent 418ad2b586
commit a1790f2652
7 changed files with 50 additions and 74 deletions
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22
tests/e2e/test_embeddings_lr.py
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@@ -7,15 +7,13 @@ import os
import unittest
from pathlib import Path
from tbparse import SummaryReader
from axolotl.cli import load_datasets
from axolotl.common.cli import TrainerCliArgs
from axolotl.train import train
from axolotl.utils.config import normalize_config
from axolotl.utils.dict import DictDefault
from .utils import most_recent_subdir, with_temp_dir
from .utils import check_tensorboard, with_temp_dir
LOG = logging.getLogger("axolotl.tests.e2e")
os.environ["WANDB_DISABLED"] = "true"
@@ -66,12 +64,9 @@ class TestEmbeddingsLrScale(unittest.TestCase):
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
assert (Path(temp_dir) / "model.safetensors").exists()
tb_log_path = most_recent_subdir(temp_dir + "/runs")
event_file = os.path.join(tb_log_path, sorted(os.listdir(tb_log_path))[0])
reader = SummaryReader(event_file)
df = reader.scalars # pylint: disable=invalid-name
df = df[(df.tag == "train/train_loss")] # pylint: disable=invalid-name
assert df.value.values[-1] < 2.0, "Loss is too high"
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.0, "Loss is too high"
)
@with_temp_dir
def test_train_w_embedding_lr(self, temp_dir):
@@ -113,9 +108,6 @@ class TestEmbeddingsLrScale(unittest.TestCase):
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
assert (Path(temp_dir) / "model.safetensors").exists()
tb_log_path = most_recent_subdir(temp_dir + "/runs")
event_file = os.path.join(tb_log_path, sorted(os.listdir(tb_log_path))[0])
reader = SummaryReader(event_file)
df = reader.scalars # pylint: disable=invalid-name
df = df[(df.tag == "train/train_loss")] # pylint: disable=invalid-name
assert df.value.values[-1] < 2.0, "Loss is too high"
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.0, "Loss is too high"
)