208fb7b8e7
* debug * debug * debug * revert unneeded change * add accelerator config to base trainer builder * add back accumulated_cache_size_limit setting * lint * accelerator constructor patch for single-GPU torch fp8 * lint * re-using existing fp8 code * lint * remove accelerate patch now fix in latest release * fix * docs * add fp8 + fsdp2 example * remove unused config * update config * smoke tests * add validator * add 2.7.0 guard for fsdp2 * fix * add config descriptions * add FSDP doc link * nit * set force_recompute_fp8_weight_in_bwd with enable_fsdp_float8_all_gather * better cfg for smoke tests * add test for accelerate patching * update fp8 validator
63 lines
2.1 KiB
Python
63 lines
2.1 KiB
Python
"""
|
|
Simple end-to-end smoke tests for FP8 mixed precision training
|
|
"""
|
|
|
|
from axolotl.common.datasets import load_datasets
|
|
from axolotl.train import train
|
|
from axolotl.utils.config import normalize_config, validate_config
|
|
from axolotl.utils.dict import DictDefault
|
|
|
|
from tests.e2e.utils import check_model_output_exists, require_torch_2_7_0
|
|
|
|
|
|
class FP8IntegrationTestCase:
|
|
"""
|
|
e2e smoke tests for FP8 mixed precision training with Axolotl
|
|
"""
|
|
|
|
@require_torch_2_7_0
|
|
def test_fp8_single_gpu_smoke(self, temp_dir):
|
|
"""Smoke test for single GPU FP8 + torch.compile training"""
|
|
# pylint: disable=duplicate-code
|
|
cfg = DictDefault(
|
|
{
|
|
"base_model": "HuggingFaceTB/SmolLM2-135M",
|
|
"tokenizer_type": "AutoTokenizer",
|
|
"trust_remote_code": True,
|
|
"sequence_len": 512,
|
|
"val_set_size": 0.05,
|
|
"special_tokens": {
|
|
"pad_token": "<|endoftext|>",
|
|
},
|
|
"datasets": [
|
|
{
|
|
"path": "mhenrichsen/alpaca_2k_test",
|
|
"type": "alpaca",
|
|
},
|
|
],
|
|
"num_epochs": 1,
|
|
"max_steps": 3, # Very short smoke test
|
|
"micro_batch_size": 1,
|
|
"gradient_accumulation_steps": 2,
|
|
"output_dir": temp_dir,
|
|
"learning_rate": 0.00001,
|
|
"optimizer": "adamw_torch_fused",
|
|
"lr_scheduler": "cosine",
|
|
"sdp_attention": True,
|
|
"pad_to_seq_len": True,
|
|
"sample_packing": True,
|
|
"fp8": True,
|
|
"torch_compile": True,
|
|
"save_safetensors": True,
|
|
"save_first_step": False,
|
|
}
|
|
)
|
|
|
|
# pylint: disable=duplicate-code
|
|
cfg = validate_config(cfg)
|
|
normalize_config(cfg)
|
|
dataset_meta = load_datasets(cfg=cfg)
|
|
|
|
train(cfg=cfg, dataset_meta=dataset_meta)
|
|
check_model_output_exists(temp_dir, cfg)
|