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rename liger test so it properly runs in ci (#2246)

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This commit is contained in:
Wing Lian
2025-01-09 17:31:43 -05:00
committed by Sunny
parent 5eae134110
commit bd62d6e10a
8 changed files with 70 additions and 66 deletions
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47
tests/e2e/integrations/liger.py → tests/e2e/integrations/test_liger.py
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@@ -1,43 +1,40 @@
"""
Simple end-to-end test for Liger integration
"""
import unittest
from pathlib import Path
from e2e.utils import require_torch_2_4_1
from axolotl.cli import load_datasets
from axolotl.common.cli import TrainerCliArgs
from axolotl.train import train
from axolotl.utils.config import normalize_config, prepare_plugins
from axolotl.utils.dict import DictDefault
from ..utils import with_temp_dir
class LigerIntegrationTestCase(unittest.TestCase):
class LigerIntegrationTestCase:
"""
e2e tests for liger integration with Axolotl
"""
@with_temp_dir
@require_torch_2_4_1
def test_llama_wo_flce(self, temp_dir):
# pylint: disable=duplicate-code
cfg = DictDefault(
{
"base_model": "JackFram/llama-68m",
"tokenizer_type": "LlamaTokenizer",
"base_model": "HuggingFaceTB/SmolLM2-135M",
"plugins": [
"axolotl.integrations.liger.LigerPlugin",
],
"liger_rope": True,
"liger_rms_norm": True,
"liger_swiglu": True,
"liger_glu_activation": True,
"liger_cross_entropy": True,
"liger_fused_linear_cross_entropy": False,
"sequence_len": 1024,
"val_set_size": 0.1,
"val_set_size": 0.05,
"special_tokens": {
"unk_token": "<unk>",
"bos_token": "<s>",
"eos_token": "</s>",
"pad_token": "<|endoftext|>",
},
"datasets": [
{
@@ -46,15 +43,15 @@ class LigerIntegrationTestCase(unittest.TestCase):
},
],
"num_epochs": 1,
"micro_batch_size": 8,
"gradient_accumulation_steps": 1,
"micro_batch_size": 2,
"gradient_accumulation_steps": 2,
"output_dir": temp_dir,
"learning_rate": 0.00001,
"optimizer": "adamw_torch",
"lr_scheduler": "cosine",
"save_safetensors": True,
"bf16": "auto",
"max_steps": 10,
"max_steps": 5,
}
)
prepare_plugins(cfg)
@@ -65,26 +62,24 @@ class LigerIntegrationTestCase(unittest.TestCase):
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
assert (Path(temp_dir) / "model.safetensors").exists()
@with_temp_dir
@require_torch_2_4_1
def test_llama_w_flce(self, temp_dir):
# pylint: disable=duplicate-code
cfg = DictDefault(
{
"base_model": "JackFram/llama-68m",
"tokenizer_type": "LlamaTokenizer",
"base_model": "HuggingFaceTB/SmolLM2-135M",
"plugins": [
"axolotl.integrations.liger.LigerPlugin",
],
"liger_rope": True,
"liger_rms_norm": True,
"liger_swiglu": True,
"liger_glu_activation": True,
"liger_cross_entropy": False,
"liger_fused_linear_cross_entropy": True,
"sequence_len": 1024,
"val_set_size": 0.1,
"val_set_size": 0.05,
"special_tokens": {
"unk_token": "<unk>",
"bos_token": "<s>",
"eos_token": "</s>",
"pad_token": "<|endoftext|>",
},
"datasets": [
{
@@ -93,15 +88,15 @@ class LigerIntegrationTestCase(unittest.TestCase):
},
],
"num_epochs": 1,
"micro_batch_size": 8,
"gradient_accumulation_steps": 1,
"micro_batch_size": 2,
"gradient_accumulation_steps": 2,
"output_dir": temp_dir,
"learning_rate": 0.00001,
"optimizer": "adamw_torch",
"lr_scheduler": "cosine",
"save_safetensors": True,
"bf16": "auto",
"max_steps": 10,
"max_steps": 5,
}
)
prepare_plugins(cfg)

1
tests/e2e/test_optimizers.py
View File

@@ -113,6 +113,7 @@ class TestCustomOptimizers(unittest.TestCase):
@with_temp_dir
def test_fft_schedule_free_adamw(self, temp_dir):
# pylint: disable=duplicate-code
cfg = DictDefault(
{
"base_model": "HuggingFaceTB/SmolLM2-135M",

16
tests/e2e/utils.py
View File

@@ -49,7 +49,19 @@ def require_torch_2_3_1(test_case):
torch_version = version.parse(torch.__version__)
return torch_version >= version.parse("2.3.1")
return unittest.skipUnless(is_min_2_3_1(), "test torch 2.3.1")(test_case)
return unittest.skipUnless(is_min_2_3_1(), "test requires torch>=2.3.1")(test_case)
def require_torch_2_4_1(test_case):
"""
Decorator marking a test that requires torch >= 2.5.1
"""
def is_min_2_4_1():
torch_version = version.parse(torch.__version__)
return torch_version >= version.parse("2.4.1")
return unittest.skipUnless(is_min_2_4_1(), "test requires torch>=2.4.1")(test_case)
def require_torch_2_5_1(test_case):
@@ -61,7 +73,7 @@ def require_torch_2_5_1(test_case):
torch_version = version.parse(torch.__version__)
return torch_version >= version.parse("2.5.1")
return unittest.skipUnless(is_min_2_5_1(), "test torch 2.5.1")(test_case)
return unittest.skipUnless(is_min_2_5_1(), "test requires torch>=2.5.1")(test_case)
def is_hopper():