| | """ |
| | E2E tests for lora llama |
| | """ |
| |
|
| | import logging |
| | import os |
| | import unittest |
| | from pathlib import Path |
| |
|
| | import pytest |
| |
|
| | 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 .utils import with_temp_dir |
| |
|
| | LOG = logging.getLogger("axolotl.tests.e2e") |
| | os.environ["WANDB_DISABLED"] = "true" |
| |
|
| |
|
| | @pytest.mark.skip(reason="doesn't seem to work on modal") |
| | class TestPhi(unittest.TestCase): |
| | """ |
| | Test case for Phi2 models |
| | """ |
| |
|
| | @with_temp_dir |
| | def test_phi_ft(self, temp_dir): |
| | |
| | cfg = DictDefault( |
| | { |
| | "base_model": "microsoft/phi-1_5", |
| | "model_type": "AutoModelForCausalLM", |
| | "tokenizer_type": "AutoTokenizer", |
| | "sequence_len": 2048, |
| | "sample_packing": False, |
| | "load_in_8bit": False, |
| | "adapter": None, |
| | "val_set_size": 0.1, |
| | "special_tokens": { |
| | "pad_token": "<|endoftext|>", |
| | }, |
| | "datasets": [ |
| | { |
| | "path": "mhenrichsen/alpaca_2k_test", |
| | "type": "alpaca", |
| | }, |
| | ], |
| | "dataset_shard_num": 10, |
| | "dataset_shard_idx": 0, |
| | "num_epochs": 1, |
| | "micro_batch_size": 1, |
| | "gradient_accumulation_steps": 1, |
| | "output_dir": temp_dir, |
| | "learning_rate": 0.00001, |
| | "optimizer": "paged_adamw_8bit", |
| | "lr_scheduler": "cosine", |
| | "flash_attention": True, |
| | "max_steps": 10, |
| | "save_steps": 10, |
| | "eval_steps": 10, |
| | "bf16": "auto", |
| | } |
| | ) |
| | normalize_config(cfg) |
| | cli_args = TrainerCliArgs() |
| | dataset_meta = load_datasets(cfg=cfg, cli_args=cli_args) |
| |
|
| | train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta) |
| | assert (Path(temp_dir) / "pytorch_model.bin").exists() |
| |
|
| | @with_temp_dir |
| | def test_phi_qlora(self, temp_dir): |
| | |
| | cfg = DictDefault( |
| | { |
| | "base_model": "microsoft/phi-1_5", |
| | "model_type": "AutoModelForCausalLM", |
| | "tokenizer_type": "AutoTokenizer", |
| | "sequence_len": 2048, |
| | "sample_packing": False, |
| | "load_in_8bit": False, |
| | "adapter": "qlora", |
| | "lora_r": 64, |
| | "lora_alpha": 32, |
| | "lora_dropout": 0.05, |
| | "lora_target_linear": True, |
| | "val_set_size": 0.1, |
| | "special_tokens": { |
| | "pad_token": "<|endoftext|>", |
| | }, |
| | "datasets": [ |
| | { |
| | "path": "mhenrichsen/alpaca_2k_test", |
| | "type": "alpaca", |
| | }, |
| | ], |
| | "dataset_shard_num": 10, |
| | "dataset_shard_idx": 0, |
| | "num_epochs": 1, |
| | "micro_batch_size": 1, |
| | "gradient_accumulation_steps": 1, |
| | "output_dir": temp_dir, |
| | "learning_rate": 0.00001, |
| | "optimizer": "paged_adamw_8bit", |
| | "lr_scheduler": "cosine", |
| | "flash_attention": True, |
| | "max_steps": 10, |
| | "save_steps": 10, |
| | "eval_steps": 10, |
| | "bf16": "auto", |
| | } |
| | ) |
| | normalize_config(cfg) |
| | cli_args = TrainerCliArgs() |
| | dataset_meta = load_datasets(cfg=cfg, cli_args=cli_args) |
| |
|
| | train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta) |
| | assert (Path(temp_dir) / "adapter_model.bin").exists() |
| |
|
