wehub-resource-sync
48 lines
1.3 KiB
Bash
Executable File
48 lines
1.3 KiB
Bash
Executable File
#!/bin/sh
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set -x
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DIR="$( cd "$(dirname "$(readlink -f "$0")")" || exit ; pwd -P )"
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sudo mkdir -p /mle/ /kaggle/
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CURRENT_USER=$(id -un)
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sudo chown -R $CURRENT_USER:$CURRENT_USER /workspace/ /mle/ /kaggle/
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ls -lat /
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cd $DIR/../RD-Agent
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mkdir -p log/
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git fetch
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git checkout ${RD_COMMIT:-ee8d97c52062607cac778b8aeb10769b075a8d11}
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make dev
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pip install 'litellm[proxy]'
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pip install git+https://github.com/you-n-g/litellm@add_mi_cred_pr
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cd $DIR/../litellm-srv/
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export AZURE_CLIENT_ID
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export AZURE_SCOPE=api://trapi/.default
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export AZURE_CREDENTIAL=ManagedIdentityCredential
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sed -i '/proxy_handler_instance/d' litellm.trapi.yaml # remove useless handler in production
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nohup litellm --config litellm.trapi.yaml &
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sleep 10 # wait for litellm to start
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cd $DIR/../RD-Agent
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script -c "timeout ${RD_TIMEOUT:-24h} python rdagent/app/data_science/loop.py --competition $DS_COMPETITION" log/stdout.${DS_COMPETITION}.log
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unset LOG_TRACE_PATH # avoid make the original log dirty.
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python rdagent/log/mle_summary.py grade_summary --log_folder=./log/
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tar cf log.tar log
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# NOTE: when we have $AMLT_OUTPUT_DIR, maybe we don't have to copy file actively to azure blob now.
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# RD_OUTPUT_DIR=${RD_OUTPUT_DIR:-/data/rdagent}/
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# mkdir -p $RD_OUTPUT_DIR
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# cp -r log.tar $RD_OUTPUT_DIR/${RD_RES_NAME:-log.tar}
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cp -r log.tar $AMLT_OUTPUT_DIR/${RD_RES_NAME:-log.tar}
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set > $AMLT_OUTPUT_DIR/env
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