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# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# 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 argparse
import importlib
import os
from loguru import logger as logging
from megatron.core.tensor_parallel.random import model_parallel_cuda_manual_seed
from omegaconf import OmegaConf
from cosmos_predict1.utils import misc
from cosmos_predict1.utils.config_helper import get_config_module, override
from cosmos_predict1.utils.lazy_config import instantiate
from cosmos_predict1.utils.lazy_config.lazy import LazyConfig
@misc.timer("instantiate LLM")
def instantiate_model(config, trainer) -> None:
model_parallel_cuda_manual_seed(config.trainer.seed)
model = instantiate(config.model)
if not config.model["model_config"].set_parallel_mode:
misc.set_random_seed(seed=config.trainer.seed, by_rank=True)
return model
@logging.catch(reraise=True)
def launch(config, args: argparse.Namespace) -> None:
# Check that the config is valid
config.validate()
# Freeze the config so developers don't change it during training.
config.freeze() # type: ignore
trainer = config.trainer.type(config)
# Create the model
model = instantiate_model(config, trainer)
model.on_model_init_end()
dataloader_train = instantiate(config.dataloader_train)
dataloader_val = instantiate(config.dataloader_val)
trainer.train(
model,
dataloader_train,
dataloader_val,
)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Training")
parser.add_argument(
"--config", default="projects.cosmos.ar.v1.configs.train_openhermes", help="Path to the config file"
)
parser.add_argument("--cluster", default=None, help="Cluster name")
parser.add_argument(
"opts",
help="""Modify config options at the end of the command. For Yacs configs, use
space-separated "PATH.KEY VALUE" pairs.
For python-based LazyConfig, use "path.key=value".
""".strip(),
default=None,
nargs=argparse.REMAINDER,
)
parser.add_argument(
"--dryrun",
action="store_true",
help="Do a dry run without training. Useful for debugging the config.",
)
args = parser.parse_args()
config = importlib.import_module(get_config_module(args.config)).make_config()
config = override(config, args.opts)
if args.dryrun:
os.makedirs(config.job.path_local, exist_ok=True)
LazyConfig.save_yaml(config, f"{config.job.path_local}/config.yaml")
print(OmegaConf.to_yaml(OmegaConf.load(f"{config.job.path_local}/config.yaml")))
else:
# Launch the training job.
launch(config, args)
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