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# Copyright 2020-2025 The HuggingFace Team. 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 os
import sys
import warnings
from accelerate.commands.launch import launch_command, launch_command_parser
from .scripts.chat import main as chat_main
from .scripts.chat import make_parser as make_chat_parser
from .scripts.dpo import make_parser as make_dpo_parser
from .scripts.env import print_env
from .scripts.grpo import make_parser as make_grpo_parser
from .scripts.kto import make_parser as make_kto_parser
from .scripts.sft import make_parser as make_sft_parser
from .scripts.utils import TrlParser
from .scripts.vllm_serve import main as vllm_serve_main
from .scripts.vllm_serve import make_parser as make_vllm_serve_parser
def main():
parser = TrlParser(prog="TRL CLI", usage="trl", allow_abbrev=False)
# Add the subparsers
subparsers = parser.add_subparsers(help="available commands", dest="command", parser_class=TrlParser)
# Add the subparsers for every script
make_chat_parser(subparsers)
make_dpo_parser(subparsers)
subparsers.add_parser("env", help="Print the environment information")
make_grpo_parser(subparsers)
make_kto_parser(subparsers)
make_sft_parser(subparsers)
make_vllm_serve_parser(subparsers)
# Parse the arguments
args = parser.parse_args()
if args.command == "chat":
(chat_args,) = parser.parse_args_and_config()
chat_main(chat_args)
if args.command == "dpo":
# Get the default args for the launch command
dpo_training_script = os.path.join(os.path.dirname(os.path.abspath(__file__)), "scripts", "dpo.py")
args = launch_command_parser().parse_args([dpo_training_script])
# Feed the args to the launch command
args.training_script_args = sys.argv[2:] # remove "trl" and "dpo"
launch_command(args) # launch training
elif args.command == "env":
print_env()
elif args.command == "grpo":
# Get the default args for the launch command
grpo_training_script = os.path.join(os.path.dirname(os.path.abspath(__file__)), "scripts", "grpo.py")
args = launch_command_parser().parse_args([grpo_training_script])
# Feed the args to the launch command
args.training_script_args = sys.argv[2:] # remove "trl" and "grpo"
launch_command(args) # launch training
elif args.command == "kto":
# Get the default args for the launch command
kto_training_script = os.path.join(os.path.dirname(os.path.abspath(__file__)), "scripts", "kto.py")
args = launch_command_parser().parse_args([kto_training_script])
# Feed the args to the launch command
args.training_script_args = sys.argv[2:] # remove "trl" and "kto"
launch_command(args) # launch training
elif args.command == "sft":
# Get the default args for the launch command
sft_training_script = os.path.join(os.path.dirname(os.path.abspath(__file__)), "scripts", "sft.py")
args = launch_command_parser().parse_args([sft_training_script])
# Feed the args to the launch command
args.training_script_args = sys.argv[2:] # remove "trl" and "sft"
launch_command(args) # launch training
elif args.command == "vllm-serve":
(script_args,) = parser.parse_args_and_config()
# Known issue: Using DeepSpeed with tensor_parallel_size=1 and data_parallel_size>1 may cause a crash when
# launched via the CLI. Suggest running the module directly.
# More information: https://github.com/vllm-project/vllm/issues/17079
if script_args.tensor_parallel_size == 1 and script_args.data_parallel_size > 1:
warnings.warn(
"Detected configuration: tensor_parallel_size=1 and data_parallel_size>1. This setup is known to "
"cause a crash when using the `trl vllm-serve` CLI entry point. As a workaround, please run the "
"server using the module path instead: `python -m trl.scripts.vllm_serve`",
RuntimeWarning,
)
vllm_serve_main(script_args)
if __name__ == "__main__":
main()
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