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| """ | |
| Copyright (c) 2022, salesforce.com, inc. | |
| All rights reserved. | |
| SPDX-License-Identifier: BSD-3-Clause | |
| For full license text, see the LICENSE_Lavis file in the repo root or https://opensource.org/licenses/BSD-3-Clause | |
| """ | |
| import argparse | |
| import os | |
| import random | |
| import numpy as np | |
| import torch | |
| import torch.backends.cudnn as cudnn | |
| import yaml | |
| # import esm | |
| import minigpt4.tasks as tasks | |
| from minigpt4.esm.esm_config import Config | |
| from minigpt4.common.dist_utils import get_rank, init_distributed_mode | |
| from minigpt4.common.logger import setup_logger | |
| from minigpt4.common.optims import ( | |
| LinearWarmupCosineLRScheduler, | |
| LinearWarmupStepLRScheduler, | |
| ) | |
| from minigpt4.common.registry import registry | |
| from minigpt4.common.utils import now | |
| # imports modules for registration | |
| from minigpt4.datasets.builders import * | |
| from minigpt4.datasets.pdb_dataset import ESMDataset | |
| from minigpt4.datasets.qa_dataset import QADataset | |
| from minigpt4.models import * | |
| from minigpt4.processors import * | |
| from minigpt4.runners import * | |
| from minigpt4.tasks import * | |
| def parse_args(): | |
| parser = argparse.ArgumentParser(description="Training") | |
| parser.add_argument("--cfg-path", required=False, help="path to configuration file.", | |
| default='configs/train_modality_alignment.yaml') | |
| parser.add_argument( | |
| "--options", | |
| nargs="+", | |
| help="override some settings in the used config, the key-value pair " | |
| "in xxx=yyy format will be merged into config file (deprecate), " | |
| "change to --cfg-options instead.", | |
| ) | |
| args = parser.parse_args() | |
| # if 'LOCAL_RANK' not in os.environ: | |
| # os.environ['LOCAL_RANK'] = str(args.local_rank) | |
| return args | |
| def setup_seeds(config): | |
| seed = config.run_cfg.seed + get_rank() | |
| random.seed(seed) | |
| np.random.seed(seed) | |
| torch.manual_seed(seed) | |
| cudnn.benchmark = False | |
| cudnn.deterministic = True | |
| def get_runner_class(cfg): | |
| """ | |
| Get runner class from config. Default to epoch-based runner. | |
| """ | |
| runner_cls = registry.get_runner_class(cfg.run_cfg.get("runner", "runner_base")) | |
| return runner_cls | |
| def is_stage_1_training(cfg): | |
| return cfg.to_dict()["run"]["stage"] == 1 | |
| def main(): | |
| # allow auto-dl completes on main process without timeout when using NCCL backend. | |
| # os.environ["NCCL_BLOCKING_WAIT"] = "1" | |
| # set before init_distributed_mode() to ensure the same job_id shared across all ranks. | |
| job_id = now() | |
| cfg = Config(parse_args()) | |
| init_distributed_mode(cfg.run_cfg) | |
| setup_seeds(cfg) | |
| # set after init_distributed_mode() to only log on master. | |
| setup_logger() | |
| cfg.pretty_print() | |
| task = tasks.setup_task(cfg) | |
| datasets_raw = [] | |
| if (is_stage_1_training(cfg)): | |
| datasets_raw = ESMDataset(pdb_root="/home/ubuntu/pt/", | |
| seq_root="/home/ubuntu/seq/", | |
| ann_paths="/home/ubuntu/proteinchat/data/esm_subset/abstract.json", | |
| dataset_description="/home/ubuntu/dataset.json", | |
| chain="A") | |
| else: | |
| datasets_raw = QADataset(pdb_root="/home/ubuntu/pt/", | |
| seq_root="/home/ubuntu/seq/", | |
| # ann_paths="/home/ubuntu/proteinchat/data/esm_subset/qa_all.json", | |
| ann_paths="/home/ubuntu/proteinchat/data/esm_subset/GPT_merged_summary.json", | |
| # dataset_description="/home/ubuntu/dataset.json", | |
| chain="A") | |
| datasets = {'esm': {'train': datasets_raw}} | |
| model = task.build_model(cfg) | |
| runner = get_runner_class(cfg)( | |
| cfg=cfg, job_id=job_id, task=task, model=model, datasets=datasets | |
| ) | |
| runner.train() | |
| if __name__ == "__main__": | |
| main() | |