b5f1e53a0f
* models.py -> loaders/ module refactor * refactor ModelLoader class * plugin manager changes * circular import fix * pytest * pytest * minor improvements * fix * minor changes * fix test * remove dead code * coderabbit comments * lint * fix * coderabbit suggestion I liked * more coderabbit * review comments, yak shaving * lint * updating in light of SP ctx manager changes * review comment * review comment 2
71 lines
2.0 KiB
Python
71 lines
2.0 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
|
|
|
|
# pylint: disable=duplicate-code
|
|
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()
|