Gub Gub Gub Gub Gub Gub: Gub 2

GUB 2024: Gub gub gub gub gub gub gub gub gub gub gub gub gub. Gub, Gub gub gub Gub, gub gub gub gub GUB gub gub gub gub gub gub gub gub GUB gub._

Gub gub gub 2 gub gub 2-gub gub. Gub 1 gub gub gub.

Gub gub 1, gub gub gub gub gub Gub gub Gub gub gub gub-gub gub gub salloc. Gub gub gub, gub'gub gub gub gub gub Gub gub Gub gub gub gub-gub gub, gub gub gub gub sbatch.

Gub 1: Gub Gub Gub

Gub'gub gub gub gub gub Gub gub, gub gub gub gub gub gub gub gub gub gub gub gub gub. Gub gub gub gub gub Gub gub gub gub gub'gub gub gub sbatch. Gub gub gub gub gub gub gub gub gub gub salloc gub gub 1, gub gub gub #SBATCH gub gub.

launch.sh

#!/bin/bash
#SBATCH -J "JOBNAME"
#SBATCH --nodes=2
#SBATCH --gpus-per-node=8
#SBATCH --cpus-per-task=128
#SBATCH --mem=2000G
#SBATCH --time=72:00:00
#SBATCH --qos=<qos>

export CUR_DIR=$(pwd)
srun --nodes=2 stage1.sh

Gub gub gub gub gub gub CUR_DIR gub gub gub gub gub gub (gub gub gub gub sbatch gub gub gub). Gub gub gub gub gub gub gub gub gub gub gub gub gub gub, gub Gub gub'gub gub gub gub-gub gub. Gub gub'gub gub gub.

Gub gub gub gub gub gub gub gub gub gub srun gub, gub gub gub gub stage1.sh gub gub gub gub.

Gub 2. Gub Gub Gub

Gub, gub'gub gub gub gub gub gub gub gub gub gub gub. Gub gub gub gub gub gub gub gub gub gub gub gub gub gub. Gub'gub gub gub gub stage1.sh.

stage1.sh

#!/bin/bash

module load jq zstd pigz parallel libnvidia-container enroot

export MASTER_ADDR=$(scontrol show hostnames $SLURM_JOB_NODELIST | head -n 1) # get the IP address of the first node in the list
export MASTER_PORT=6000 # set the port to use for communication between nodes

enroot create --name image-name /path/to/image-name.sqsh

enroot start --env SLURM_NODEID \
             --env MASTER_ADDR \
             --env MASTER_PORT \
             --env SLURM_JOB_NAME \
             --env CUR_DIR \
             --mount /local/file/path:/image/file/path \
             --rw image-name \
             bash ${CUR_DIR}/stage2.sh

Gub gub gub gub gub gub gub gub gub gub Gub, gub gub CUR_DIR, gub gub gub. Gub MASTER_ADDR gub MASTER_PORT gub gub gub gub Gub'gub gub gub gub gub gub gub gub gub.

Gub gub gub gub gub gub gub gub gub gub (gub gub gub gub gub gub gub!).

Gub 3. Gub Gub

Gub, gub'gub gub gub gub gub gub gub gub gub gub gub gub. Gub'gub gub gub gub stage2.sh.

stage2.sh

#!/bin/bash

export NCCL_DEBUG=INFO # if you want to see NCCL logs
export NODE_RANK=$SLURM_NODEID # set the node rank to the node ID (0, 1, 2, etc.)
echo NODE_RANK: $NODE_RANK # print the node rank for debugging purposes

# Run training script
# NOTE: modify as desired if you're not using accelerate

accelerate launch --config_file ./accelerate_config.yaml --main_process_ip=$MASTER_ADDR --main_process_port=$MASTER_PORT --machine_rank $NODE_RANK ${CUR_DIR}/loop.py

Gub Gub'gub gub gub gub gub gub gub gub gub gub gub, gub gub gub gub gub gub gub gub. Gub gub gub gub gub gub gub gub gub!

Gub gub gub gub gub, gub'gub gub accelerate_config.yaml gub. Gub gub GUB (Gub Gub Gub Gub) gub gub gub gub gub gub gub gub. Gub gub gub gub gub gub gub gub gub gub gub'gub gub gub gub gub GUB.

compute_environment: LOCAL_MACHINE
deepspeed_config: {}
distributed_type: FSDP
downcast_bf16: "no"
fsdp_config:
  fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
  fsdp_backward_prefetch_policy: BACKWARD_PRE
  fsdp_offload_params: false
  fsdp_sharding_strategy: 1
  fsdp_state_dict_type: FULL_STATE_DICT
  fsdp_transformer_layer_cls_to_wrap: LlamaDecoderLayer
main_training_function: main
mixed_precision: "no"
num_machines: 2
num_processes: 16 # 8 GPUs per node * 2 nodes = 16 processes
use_cpu: false

Gub 4. Gub Gub Gub

Gub gub gub'gub gub gub gub gub gub, gub gub gub gub gub gub Gub gub sbatch! Gub gub gub gub gub gub, gub:

sbatch launch.sh

Gub gub gub gub gub gub Gub gub gub gub gub gub gub gub gub. Gub gub gub gub gub gub slurm-<jobid>.out gub gub gub gub.

Gub

Gub gub gub gub gub! Gub gub gub gub gub gub gub gub gub gub, gub gub'gub gub gub gub gub gub gub gub gub gub gub gub.