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#!/bin/bash
#SBATCH --comment clap
#SBATCH --partition=gpu
#SBATCH --job-name=mclap
#SBATCH --nodes 1
#SBATCH --ntasks-per-node 1
#SBATCH --cpus-per-gpu=6
#SBATCH --gres=gpu:1
#SBATCH --output=%x_%j.out
#SBATCH --exclude gpu-st-p4d-24xlarge-[23,30,31,108,115,134,135,183,185,186,187,188,275,277,290,374]
module load intelmpi
source /opt/intel/mpi/latest/env/vars.sh
export LD_LIBRARY_PATH=/opt/aws-ofi-nccl/lib:/opt/amazon/efa/lib64:/usr/local/cuda-11.0/efa/lib:/usr/local/cuda-11.0/lib:/usr/local/cuda-11.0/lib64:/usr/local/cuda-11.0:/opt/nccl/build/lib:/opt/aws-ofi-nccl-install/lib:/opt/aws-ofi-nccl/lib:$LD_LIBRARY_PATH
export NCCL_PROTO=simple
export PATH=/opt/amazon/efa/bin:$PATH
export LD_PRELOAD="/opt/nccl/build/lib/libnccl.so"
export FI_EFA_FORK_SAFE=1
export FI_LOG_LEVEL=1
export FI_EFA_USE_DEVICE_RDMA=1 # use for p4dn
#export NCCL_ALGO=ring
export NCCL_DEBUG=info
#export NCCL_DEBUG_SUBSYS=INIT,ENV,GRAPH,COLL
export PYTHONFAULTHANDLER=1
export CUDA_LAUNCH_BLOCKING=0
export OMPI_MCA_mtl_base_verbose=1
export FI_EFA_ENABLE_SHM_TRANSFER=0
export FI_PROVIDER=efa
export FI_EFA_TX_MIN_CREDITS=64
export NCCL_TREE_THRESHOLD=0
#export NCCL_P2P_DISABLE=1
#export NCCL_IBEXT_DISABLE=1
#export NCCL_SOCKET_IFNAME="eth0,en,eth,em,bond"
# sent to sub script
export HOSTNAMES=`scontrol show hostnames "$SLURM_JOB_NODELIST"`
export MASTER_ADDR=$(scontrol show hostnames "$SLURM_JOB_NODELIST" | head -n 1)
export MASTER_PORT=12802
export COUNT_NODE=`scontrol show hostnames "$SLURM_JOB_NODELIST" | wc -l`
echo go $COUNT_NODE
echo $HOSTNAMES
source /fsx/yusong/clap/bin/activate
cd /fsx/yusong/CLAP/src
export TRANSFORMERS_CACHE=/fsx/yusong/transformers_cache
srun --comment clap --cpu_bind=v --accel-bind=gn python -m evaluate.eval_retrieval_main \
--save-frequency 5 \
--save-top-performance 3 \
--save-most-recent \
--dataset-type="webdataset" \
--precision="fp32" \
--warmup 0 \
--batch-size=512 \
--wd=0.0 \
--epochs=50 \
--workers=6 \
--use-bn-sync \
--freeze-text \
--amodel HTSAT-tiny \
--tmodel roberta \
--report-to "wandb" \
--wandb-notes "10.17-zeroshot-esc50-dataset-4#" \
--datasetnames "esc50" \
--datasetinfos "train" \
--seed 3407 \
--remotedata \
--logs /fsx/clap_logs \
--gather-with-grad \
--openai-model-cache-dir /fsx/yusong/transformers_cache \
--data-filling "repeatpad" \
--data-truncating "rand_trunc" \
--class-label-path="../class_labels/ESC50_class_labels_indices_space.json" \
--pretrained="/fsx/clap_logs/2022_10_17-02_08_21-model_HTSAT-tiny-lr_0.0001-b_96-j_6-p_fp32/checkpoints" |