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make sure to cleanup tmp output_dir for e2e tests

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This commit is contained in:
Wing Lian
2023-11-05 08:02:31 -05:00
parent b2430ce670
commit 0402d19759
6 changed files with 52 additions and 25 deletions
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6
tests/e2e/test_fused_llama.py
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@@ -4,7 +4,6 @@ E2E tests for lora llama
import logging
import os
import tempfile
import unittest
from pathlib import Path
@@ -15,6 +14,7 @@ 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 tests.utils import with_temp_dir
LOG = logging.getLogger("axolotl.tests.e2e")
os.environ["WANDB_DISABLED"] = "true"
@@ -25,9 +25,9 @@ class TestFusedLlama(unittest.TestCase):
Test case for Llama models using Fused layers
"""
def test_fft_packing(self):
@with_temp_dir
def test_fft_packing(self, output_dir):
# pylint: disable=duplicate-code
output_dir = tempfile.mkdtemp()
cfg = DictDefault(
{
"base_model": "JackFram/llama-68m",

14
tests/e2e/test_lora_llama.py
View File

@@ -4,7 +4,6 @@ E2E tests for lora llama
import logging
import os
import tempfile
import unittest
from pathlib import Path
@@ -13,6 +12,7 @@ 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 tests.utils import with_temp_dir
LOG = logging.getLogger("axolotl.tests.e2e")
os.environ["WANDB_DISABLED"] = "true"
@@ -23,9 +23,9 @@ class TestLoraLlama(unittest.TestCase):
Test case for Llama models using LoRA
"""
def test_lora(self):
@with_temp_dir
def test_lora(self, output_dir):
# pylint: disable=duplicate-code
output_dir = tempfile.mkdtemp()
cfg = DictDefault(
{
"base_model": "JackFram/llama-68m",
@@ -65,9 +65,9 @@ class TestLoraLlama(unittest.TestCase):
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
assert (Path(output_dir) / "adapter_model.bin").exists()
def test_lora_packing(self):
@with_temp_dir
def test_lora_packing(self, output_dir):
# pylint: disable=duplicate-code
output_dir = tempfile.mkdtemp()
cfg = DictDefault(
{
"base_model": "JackFram/llama-68m",
@@ -109,9 +109,9 @@ class TestLoraLlama(unittest.TestCase):
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
assert (Path(output_dir) / "adapter_model.bin").exists()
def test_lora_gptq(self):
@with_temp_dir
def test_lora_gptq(self, output_dir):
# pylint: disable=duplicate-code
output_dir = tempfile.mkdtemp()
cfg = DictDefault(
{
"base_model": "TheBlokeAI/jackfram_llama-68m-GPTQ",

10
tests/e2e/test_mistral.py
View File

@@ -4,7 +4,6 @@ E2E tests for lora llama
import logging
import os
import tempfile
import unittest
from pathlib import Path
@@ -15,6 +14,7 @@ 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 tests.utils import with_temp_dir
LOG = logging.getLogger("axolotl.tests.e2e")
os.environ["WANDB_DISABLED"] = "true"
@@ -25,9 +25,9 @@ class TestMistral(unittest.TestCase):
Test case for Llama models using LoRA
"""
def test_lora(self):
@with_temp_dir
def test_lora(self, output_dir):
# pylint: disable=duplicate-code
output_dir = tempfile.mkdtemp()
cfg = DictDefault(
{
"base_model": "openaccess-ai-collective/tiny-mistral",
@@ -70,9 +70,9 @@ class TestMistral(unittest.TestCase):
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
assert (Path(output_dir) / "adapter_model.bin").exists()
def test_ft(self):
@with_temp_dir
def test_ft(self, output_dir):
# pylint: disable=duplicate-code
output_dir = tempfile.mkdtemp()
cfg = DictDefault(
{
"base_model": "openaccess-ai-collective/tiny-mistral",

10
tests/e2e/test_mistral_samplepack.py
View File

@@ -4,7 +4,6 @@ E2E tests for lora llama
import logging
import os
import tempfile
import unittest
from pathlib import Path
@@ -15,6 +14,7 @@ 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 tests.utils import with_temp_dir
LOG = logging.getLogger("axolotl.tests.e2e")
os.environ["WANDB_DISABLED"] = "true"
@@ -25,9 +25,9 @@ class TestMistral(unittest.TestCase):
Test case for Llama models using LoRA
"""
def test_lora_packing(self):
@with_temp_dir
def test_lora_packing(self, output_dir):
# pylint: disable=duplicate-code
output_dir = tempfile.mkdtemp()
cfg = DictDefault(
{
"base_model": "openaccess-ai-collective/tiny-mistral",
@@ -71,9 +71,9 @@ class TestMistral(unittest.TestCase):
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
assert (Path(output_dir) / "adapter_model.bin").exists()
def test_ft_packing(self):
@with_temp_dir
def test_ft_packing(self, output_dir):
# pylint: disable=duplicate-code
output_dir = tempfile.mkdtemp()
cfg = DictDefault(
{
"base_model": "openaccess-ai-collective/tiny-mistral",

15
tests/e2e/test_phi.py
View File

@@ -4,14 +4,15 @@ E2E tests for lora llama
import logging
import os
import tempfile
import unittest
from pathlib import Path
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 tests.utils import with_temp_dir
LOG = logging.getLogger("axolotl.tests.e2e")
os.environ["WANDB_DISABLED"] = "true"
@@ -22,7 +23,8 @@ class TestPhi(unittest.TestCase):
Test case for Llama models using LoRA
"""
def test_ft(self):
@with_temp_dir
def test_ft(self, output_dir):
# pylint: disable=duplicate-code
cfg = DictDefault(
{
@@ -52,7 +54,7 @@ class TestPhi(unittest.TestCase):
"num_epochs": 1,
"micro_batch_size": 1,
"gradient_accumulation_steps": 1,
"output_dir": tempfile.mkdtemp(),
"output_dir": output_dir,
"learning_rate": 0.00001,
"optimizer": "adamw_bnb_8bit",
"lr_scheduler": "cosine",
@@ -64,8 +66,10 @@ class TestPhi(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(output_dir) / "pytorch_model.bin").exists()
def test_ft_packed(self):
@with_temp_dir
def test_ft_packed(self, output_dir):
# pylint: disable=duplicate-code
cfg = DictDefault(
{
@@ -95,7 +99,7 @@ class TestPhi(unittest.TestCase):
"num_epochs": 1,
"micro_batch_size": 1,
"gradient_accumulation_steps": 1,
"output_dir": tempfile.mkdtemp(),
"output_dir": output_dir,
"learning_rate": 0.00001,
"optimizer": "adamw_bnb_8bit",
"lr_scheduler": "cosine",
@@ -107,3 +111,4 @@ class TestPhi(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(output_dir) / "pytorch_model.bin").exists()

22
tests/utils.py Normal file
View File

@@ -0,0 +1,22 @@
"""
helper utils for tests
"""
import shutil
import tempfile
from functools import wraps
def with_temp_dir(test_func):
@wraps(test_func)
def wrapper(*args, **kwargs):
# Create a temporary directory
temp_dir = tempfile.mkdtemp()
try:
# Pass the temporary directory to the test function
test_func(temp_dir, *args, **kwargs)
finally:
# Clean up the directory after the test
shutil.rmtree(temp_dir)
return wrapper