Files
axolotl/tests/test_lora.py
Dan Saunders 79ddaebe9a Add ruff, remove black, isort, flake8, pylint (#3092)
* black, isort, flake8 -> ruff

* remove unused

* add back needed import

* fix
2025-08-23 23:37:33 -04:00

70 lines
1.9 KiB
Python

"""
tests for loading loras
"""
from axolotl.loaders import ModelLoader, load_tokenizer
from axolotl.utils.config import normalize_config, validate_config
from axolotl.utils.dict import DictDefault
minimal_config = DictDefault(
{
"base_model": "HuggingFaceTB/SmolLM2-135M",
"learning_rate": 0.000001,
"datasets": [
{
"path": "mhenrichsen/alpaca_2k_test",
"type": "alpaca",
}
],
"micro_batch_size": 1,
"gradient_accumulation_steps": 1,
}
)
class TestLoRALoad:
"""
Test class for loading LoRA weights
"""
def test_load_lora_weights(self):
cfg = DictDefault(
{
"base_model": "HuggingFaceTB/SmolLM2-135M",
"adapter": "lora",
"lora_r": 8,
"lora_alpha": 16,
"lora_dropout": 0.0,
"lora_target_linear": True,
"micro_batch_size": 1,
"gradient_accumulation_steps": 1,
"sequence_len": 1024,
}
| minimal_config
)
cfg = validate_config(cfg)
normalize_config(cfg)
tokenizer = load_tokenizer(cfg)
ModelLoader(cfg, tokenizer).load()
def test_load_lora_weights_empty_dropout(self):
cfg = DictDefault(
{
"base_model": "HuggingFaceTB/SmolLM2-135M",
"adapter": "lora",
"lora_r": 8,
"lora_alpha": 16,
"lora_dropout": None,
"lora_target_linear": True,
"micro_batch_size": 1,
"gradient_accumulation_steps": 1,
"sequence_len": 1024,
}
| minimal_config
)
cfg = validate_config(cfg)
normalize_config(cfg)
assert cfg.lora_dropout == 0.0
tokenizer = load_tokenizer(cfg)
ModelLoader(cfg, tokenizer).load()