# -*- encoding: utf-8 -*-
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#!/usr/bin/env python3
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# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
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# MIT License (https://opensource.org/licenses/MIT)
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import os
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from funasr.tasks.lm import LMTask
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# for LM Training
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def parse_args():
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parser = LMTask.get_parser()
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parser.add_argument(
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"--gpu_id",
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type=int,
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default=0,
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help="local gpu id.",
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)
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args = parser.parse_args()
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return args
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def main(args=None, cmd=None):
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# for LM Training
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LMTask.main(args=args, cmd=cmd)
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if __name__ == '__main__':
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args = parse_args()
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# setup local gpu_id
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os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpu_id)
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# DDP settings
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if args.ngpu > 1:
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args.distributed = True
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else:
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args.distributed = False
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assert args.num_worker_count == 1
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# re-compute batch size: when dataset type is small
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if args.dataset_type == "small" and args.ngpu != 0:
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if args.batch_size is not None:
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args.batch_size = args.batch_size * args.ngpu
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if args.batch_bins is not None:
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args.batch_bins = args.batch_bins * args.ngpu
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main(args=args)
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