Initial commit: DCNv4 custom op mirror setup
- Add enhanced README with project structure and quick start guide - Initialize repository with DCNv4 CUDA extension (PyTorch module) - Include classification, detection, and segmentation subdirectories - Reference upstream OpenGVLab DCNv4 implementation Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
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25
detection/slurm_train.sh
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25
detection/slurm_train.sh
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#!/usr/bin/env bash
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set -x
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PARTITION=$1
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JOB_NAME=$2
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CONFIG=$3
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WORK_DIR=$4
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GPUS=${GPUS:-8}
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GPUS_PER_NODE=${GPUS_PER_NODE:-8}
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CPUS_PER_TASK=${CPUS_PER_TASK:-10}
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SRUN_ARGS=${SRUN_ARGS:-""}
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PY_ARGS=${@:5}
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PYTHONPATH="$(dirname $0)/..":$PYTHONPATH \
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srun -p ${PARTITION} \
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--job-name=${JOB_NAME} \
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--gres=gpu:${GPUS_PER_NODE} \
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--ntasks=${GPUS} \
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--ntasks-per-node=${GPUS_PER_NODE} \
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--cpus-per-task=${CPUS_PER_TASK} \
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--kill-on-bad-exit=1 \
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--quotatype=reserved \
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${SRUN_ARGS} \
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python -u train.py ${CONFIG} --work-dir=${WORK_DIR} --launcher="slurm" ${PY_ARGS}
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