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49 lines
1.3 KiB
49 lines
1.3 KiB
#!/usr/bin/env bash |
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# an example to do pre-training: (not that `/path/to/imagenet` should contain directories named `train` and `val`) |
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# > cd /path/to/SparK |
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# > bash ./scripts/pt.sh experiment_name /path/to/imagenet --num_nodes=1 --ngpu_per_node=8 --node_rank=0 --master_address=128.0.0.0 --master_port=30000 --model=res50 --ep=400 |
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####### template begins ####### |
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SCRIPTS_DIR=$(cd $(dirname $0); pwd) |
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cd "${SCRIPTS_DIR}" |
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cd ../ |
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SPARK_DIR=$(pwd) |
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echo "SPARK_DIR=${SPARK_DIR}" |
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shopt -s expand_aliases |
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alias python=python3 |
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alias to_scripts_dir='cd "${SCRIPTS_DIR}"' |
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alias to_spark_dir='cd "${SPARK_DIR}"' |
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alias print='echo "$(date +"[%m-%d %H:%M:%S]") (exp.sh)=>"' |
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function mkd() { |
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mkdir -p "$1" >/dev/null 2>&1 |
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} |
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####### template ends ####### |
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EXP_NAME=$1 |
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DATA_PATH=$2 |
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EXP_DIR="${SPARK_DIR}/output_${EXP_NAME}" |
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mkd "${EXP_DIR}" |
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print "===================== Args =====================" |
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print "EXP_NAME: ${EXP_NAME}" |
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print "DATA_PATH: ${DATA_PATH}" |
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print "EXP_DIR: ${EXP_DIR}" |
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print "[other_args sent to launch.py]: ${*:3}" |
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print "================================================" |
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print "" |
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print "============== Pretraining starts ==============" |
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to_spark_dir |
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python launch.py \ |
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--main_py_relpath main.py \ |
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--exp_name "${EXP_NAME}" \ |
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--data_path "${DATA_PATH}" \ |
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--exp_dir "${EXP_DIR}" \ |
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"${*:3}" |
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print "============== Pretraining ends =============="
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