NeMo_Canary / examples /nlp /language_modeling /megatron_bert_pretraining.py
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# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import torch.multiprocessing as mp
from omegaconf.omegaconf import OmegaConf, open_dict
from nemo.collections.nlp.models.language_modeling.megatron_bert_model import MegatronBertModel
from nemo.collections.nlp.parts.megatron_trainer_builder import MegatronBertTrainerBuilder
from nemo.core.config import hydra_runner
from nemo.utils import logging
from nemo.utils.exp_manager import exp_manager
@hydra_runner(config_path="conf", config_name="megatron_bert_config")
def main(cfg) -> None:
if cfg.model.data.dataloader_type != "LDDL":
mp.set_start_method("spawn", force=True)
logging.info("\n\n************** Experiment configuration ***********")
logging.info(f'\n{OmegaConf.to_yaml(cfg)}')
trainer = MegatronBertTrainerBuilder(cfg).create_trainer()
exp_manager(trainer, cfg.exp_manager)
model = MegatronBertModel(cfg.model, trainer)
trainer.fit(model)
if __name__ == '__main__':
main()