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egs/librispeech/ASR/conformer_ctc/run-multi-node-multi-gpu.sh
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113
egs/librispeech/ASR/conformer_ctc/run-multi-node-multi-gpu.sh
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#!/usr/bin/env bash
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#
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# This script is the entry point to start model training
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# with multi-node multi-GPU.
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#
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# Read the usage instructions for how to run this script.
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set -e
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cur_dir=$(cd $(dirname $BASH_SOURCE) && pwd)
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# DDP related parameters
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master_addr=
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node_rank=
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num_nodes=
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master_port=1234
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# Training script parameters
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# You can add more if you like
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#
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# Use ./conformer_ctc/train.py --help to see more
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#
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max_duration=200
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bucketing_sampler=1
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full_libri=1
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start_epoch=0
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num_epochs=2
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exp_dir=conformer_ctc/exp3
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lang_dir=data/lang_bpe_500
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. $cur_dir/../shared/parse_options.sh
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function usage() {
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echo "Usage: "
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echo ""
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echo " $0 \\"
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echo " --master-addr <IP of master> \\"
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echo " --master-port <Port of master> \\"
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echo " --node-rank <rank of this node> \\"
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echo " --num-nodes <Number of node>"
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echo ""
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echo " --master-addr The ip address of the master node."
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echo " --master-port The port of the master node."
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echo " --node-rank Rank of this node."
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echo " --num-nodes Number of nodes in DDP training."
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echo ""
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echo "Usage example:"
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echo "Suppose you want to use DDP with two machines:"
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echo " (1) Machine 1 has 4 GPUs. You want to use"
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echo " GPU 0, 1, and 3 for training"
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echo " IP of machine 1 is: 10.177.41.71"
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echo " (2) Machine 2 has 4 GPUs. You want to use"
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echo " GPU 0, 2, and 3 for training"
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echo " IP of machine 2 is: 10.177.41.72"
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echo "You want to select machine 1 as the master node and"
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echo "assume that the port 1234 is free on machine 1."
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echo ""
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echo "On machine 1, you run:"
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echo ""
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echo " export CUDA_VISIBLE_DEVICES=\"0,1,3\""
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echo " ./conformer_ctc/run-multi-node-multi-gpu.sh --master-addr 10.177.41.71 --master-port 1234 --node-rank 0 --num-nodes 2"
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echo ""
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echo "On machine 2, you run:"
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echo ""
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echo " export CUDA_VISIBLE_DEVICES=\"0,2,3\""
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echo " ./conformer_ctc/run-multi-node-multi-gpu.sh --master-addr 10.177.41.71 --master-port 1234 --node-rank 1 --num-nodes 3"
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exit 1
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}
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default='\033[0m'
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bold='\033[1m'
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red='\033[31m'
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function error() {
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printf "${bold}${red}[ERROR]${default} $1\n"
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}
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[ ! -z $CUDA_VISIBLE_DEVICES ] || ( echo; error "Please set CUDA_VISIBLE_DEVICES"; echo; usage )
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[ ! -z $master_addr ] || ( echo; error "Please set --master-addr"; echo; usage )
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[ ! -z $master_port ] || ( echo; error "Please set --master-port"; echo; usage )
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[ ! -z $node_rank ] || ( echo; error "Please set --node-rank"; echo; usage )
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[ ! -z $num_nodes ] || ( echo; error "Please set --num-nodes"; echo; usage )
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# Number of GPUs this node has
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num_gpus=$(python3 -c "s=\"$CUDA_VISIBLE_DEVICES\"; print(len(s.split(',')))")
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echo "CUDA_VISIBLE_DEVICES: $CUDA_VISIBLE_DEVICES"
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echo "num_gpus: $num_gpus"
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echo "master_addr: $master_addr"
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export MASTER_ADDR=$master_addr
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export MASTER_PORT=$master_port
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set -x
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python -m torch.distributed.launch \
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--use_env \
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--nproc_per_node $num_gpus \
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--nnodes $num_nodes \
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--node_rank $node_rank \
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--master_addr $master_addr \
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--master_port $master_port \
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\
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$cur_dir/train.py \
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--use-multi-node true \
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--master-port $master_port \
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--max-duration $max_duration \
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--bucketing-sampler $bucketing_sampler \
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--full-libri $full_libri \
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--start-epoch $start_epoch \
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--num-epochs $num_epochs \
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--exp-dir $exp_dir \
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--lang-dir $lang_dir
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