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嘉渊 2023-04-24 18:58:37 +08:00
parent b7e34131d2
commit 189b51d42b
3 changed files with 8 additions and 2 deletions
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1
egs/aishell/paraformer/run.sh
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@ -180,7 +180,6 @@ if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
--input_size $feats_dim \ --input_size $feats_dim \
--ngpu $gpu_num \ --ngpu $gpu_num \
--num_worker_count $count \ --num_worker_count $count \
--multiprocessing_distributed true \
--dist_init_method $init_method \ --dist_init_method $init_method \
--dist_world_size $world_size \ --dist_world_size $world_size \
--dist_rank $rank \ --dist_rank $rank \

7
funasr/bin/train.py
View File

@ -77,6 +77,12 @@ def get_parser():
help="Whether to use the find_unused_parameters in " help="Whether to use the find_unused_parameters in "
"torch.nn.parallel.DistributedDataParallel ", "torch.nn.parallel.DistributedDataParallel ",
) )
parser.add_argument(
"--gpu_id",
type=int,
default=0,
help="local gpu id.",
)
# cudnn related # cudnn related
parser.add_argument( parser.add_argument(
@ -399,6 +405,7 @@ if __name__ == '__main__':
torch.backends.cudnn.deterministic = args.cudnn_deterministic torch.backends.cudnn.deterministic = args.cudnn_deterministic
# ddp init # ddp init
os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpu_id)
args.distributed = args.dist_world_size > 1 args.distributed = args.dist_world_size > 1
distributed_option = build_distributed(args) distributed_option = build_distributed(args)

2
funasr/datasets/small_datasets/sequence_iter_factory.py
View File

@ -62,7 +62,7 @@ class SequenceIterFactory(AbsIterFactory):
# sampler # sampler
dataset_conf = args.dataset_conf dataset_conf = args.dataset_conf
batch_sampler = LengthBatchSampler( batch_sampler = LengthBatchSampler(
batch_bins=dataset_conf["batch_size"], batch_bins=dataset_conf["batch_size"] * args.ngpu,
shape_files=shape_files, shape_files=shape_files,
sort_in_batch=dataset_conf["sort_in_batch"] if hasattr(dataset_conf, "sort_in_batch") else "descending", sort_in_batch=dataset_conf["sort_in_batch"] if hasattr(dataset_conf, "sort_in_batch") else "descending",
sort_batch=dataset_conf["sort_batch"] if hasattr(dataset_conf, "sort_batch") else "ascending", sort_batch=dataset_conf["sort_batch"] if hasattr(dataset_conf, "sort_batch") else "ascending",