Upload llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64
Browse files
llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64/bench.slurm
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| 1 |
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#!/bin/bash
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| 2 |
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| 3 |
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#SBATCH --job-name=bench_cluster
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| 4 |
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#SBATCH --time=02:00:00
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| 5 |
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#SBATCH --partition=hopper-prod
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| 6 |
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#SBATCH --nodes=1
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| 7 |
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#SBATCH --gres=gpu:8
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#SBATCH --qos=normal
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| 9 |
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#SBATCH --ntasks-per-node=1
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| 10 |
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#SBATCH --cpus-per-task=96
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| 11 |
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#SBATCH --exclusive
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#SBATCH --output=/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64/log.out
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#SBATCH --error=/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64/log.out
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# Function to update status based on squeue output
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update_status() {
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job_id=$1
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status_file=$2
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| 19 |
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# For unknown reasons, it doenst update status for pending. It only works for running
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| 20 |
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while true; do
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| 21 |
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job_status=$(squeue --job $job_id --noheader --format=%T)
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| 22 |
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echo "Job status: $job_status"
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| 23 |
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if [ -z "$job_status" ]; then
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| 24 |
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# Job has finished or is not found
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break
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elif [ "$job_status" = "RUNNING" ]; then
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printf "running" > $status_file
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| 28 |
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break
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fi
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sleep 10
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done
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}
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# Misc initializations.
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echo "========================"
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| 36 |
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echo "START TIME: $(date)"
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source /fsx/ferdinandmom/miniforge3/etc/profile.d/conda.sh
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| 38 |
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conda activate /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster
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| 39 |
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echo python3 version = $(python3 --version)
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| 40 |
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echo "========================"
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| 41 |
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| 42 |
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# Slurm stuff
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export HOSTNAMES=$(scontrol show hostnames "$SLURM_JOB_NODELIST")
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| 44 |
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export MASTER_ADDR=$(scontrol show hostnames "$SLURM_JOB_NODELIST" | head -n 1)
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| 45 |
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export MASTER_PORT=$((1024 + RANDOM % 64511))
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| 46 |
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| 47 |
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export TMPDIR=/scratch
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| 48 |
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export HF_DATASETS_CACHE="/admin/home/ferdinand_mom/.cache"
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| 49 |
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export CUBLAS_WORKSPACE_CONFIG=":4096:8"
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| 50 |
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export CUDA_DEVICE_MAX_CONNECTIONS="1"
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| 51 |
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| 52 |
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huggingface-cli login --token $HUGGINGFACE_TOKEN
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| 53 |
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| 54 |
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| 55 |
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NANOTRON_REPO="/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron"
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| 56 |
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CMD="$NANOTRON_REPO/run_train.py --config-file /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64/config.yaml"
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| 57 |
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| 58 |
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LAUNCHER="torchrun \
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| 59 |
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--nproc_per_node 8 \
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| 60 |
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--nnodes 1 \
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| 61 |
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--rdzv_endpoint ${MASTER_ADDR}:${MASTER_PORT} \
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| 62 |
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--rdzv_backend c10d \
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| 63 |
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--max_restarts 0 \
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| 64 |
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--tee 3 \
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| 65 |
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--node_rank ${SLURM_PROCID}"
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| 66 |
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| 67 |
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# Checkout the bench_cluster branch
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| 68 |
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cd $NANOTRON_REPO
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| 69 |
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git checkout bench_cluster
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| 70 |
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cd ..
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| 71 |
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# Get the current job ID
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| 72 |
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job_id=${SLURM_JOB_ID}
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| 73 |
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| 74 |
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# Update status to "pending" or "running" in the background
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| 75 |
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update_status $job_id /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64/status.txt &
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| 76 |
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| 77 |
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# Run the main command
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| 78 |
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srun -u $LAUNCHER $CMD
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| 79 |
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exit_status=$?
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| 80 |
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| 81 |
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# Update status based on the exit status of `srun`
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| 82 |
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if [ $exit_status -eq 0 ]; then
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| 83 |
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printf "completed" > /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64/status.txt
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| 84 |
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else
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| 85 |
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if grep -q "OutOfMemoryError" /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64/log.out; then
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| 86 |
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printf "oom" > /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64/status.txt
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| 87 |
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elif grep -q " CUDA error: an illegal memory access" /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64/log.out; then
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| 88 |
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printf "oom" > /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64/status.txt
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| 89 |
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elif grep -q "Timeout at NCCL" /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64/log.out; then
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| 90 |
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printf "timeout" > /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64/status.txt
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| 91 |
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else
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| 92 |
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printf "fail" > /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64/status.txt
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| 93 |
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fi
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| 94 |
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fi
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| 95 |
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| 96 |
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# Run the report script if the job completed successfully
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| 97 |
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if [ $exit_status -eq 0 ]; then
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| 98 |
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python /fsx/ferdinandmom/ferdinand-hf/bench_cluster/main.py report --inp_dir /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64 --is_logs
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| 99 |
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python /fsx/ferdinandmom/ferdinand-hf/bench_cluster/main.py report --inp_dir /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64 --is_profiler
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| 100 |
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fi
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| 101 |
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| 102 |
+
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| 103 |
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# Push to hub the folder using huggingface_cli
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| 104 |
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huggingface-cli upload nanotron/bench_cluster /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64 llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64 --commit-message "Upload llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64"
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| 105 |
+
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| 106 |
+
# Verify the upload
|
| 107 |
+
if [ $? -eq 0 ]; then
|
| 108 |
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echo "Uploading to Huggingface Hub successful"
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| 109 |
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else
|
| 110 |
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echo "Failed to upload to Huggingface Hub"
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| 111 |
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fi
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llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64/config.yaml
ADDED
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@@ -0,0 +1,90 @@
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| 1 |
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general:
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| 2 |
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project: bench_cluster
|
| 3 |
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seed: 42
|
| 4 |
+
model:
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| 5 |
+
ddp_bucket_cap_mb: 25
|
| 6 |
+
dtype: bfloat16
|
| 7 |
+
init_method:
|
| 8 |
+
std: 0.025
|
| 9 |
+
make_vocab_size_divisible_by: 1
|
| 10 |
+
model_config:
|
| 11 |
+
bos_token_id: 1
|
| 12 |
+
eos_token_id: 2
|
| 13 |
+
hidden_act: silu
|
| 14 |
+
hidden_size: 2048
|
| 15 |
+
initializer_range: 0.02
|
| 16 |
+
intermediate_size: 4096
|
| 17 |
+
is_llama_config: true
|
| 18 |
+
max_position_embeddings: 4096
|
| 19 |
+
num_attention_heads: 32
|
| 20 |
+
num_hidden_layers: 24
|
| 21 |
+
num_key_value_heads: 32
|
| 22 |
+
pad_token_id: null
|
| 23 |
+
pretraining_tp: 1
|
| 24 |
+
rms_norm_eps: 1.0e-05
|
| 25 |
+
rope_scaling: null
|
| 26 |
+
rope_theta: 10000.0
|
| 27 |
+
tie_word_embeddings: true
|
| 28 |
+
use_cache: true
|
| 29 |
+
vocab_size: 50257
|
| 30 |
+
optimizer:
|
| 31 |
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accumulate_grad_in_fp32: true
|
| 32 |
+
clip_grad: 1.0
|
| 33 |
+
learning_rate_scheduler:
|
| 34 |
+
learning_rate: 0.0001
|
| 35 |
+
lr_decay_style: linear
|
| 36 |
+
lr_warmup_style: linear
|
| 37 |
+
lr_warmup_steps: 1
|
| 38 |
+
min_decay_lr: 1.0e-05
|
| 39 |
+
optimizer_factory:
|
| 40 |
+
adam_beta1: 0.9
|
| 41 |
+
adam_beta2: 0.95
|
| 42 |
+
adam_eps: 1.0e-08
|
| 43 |
+
name: adamW
|
| 44 |
+
torch_adam_is_fused: true
|
| 45 |
+
weight_decay: 0.01
|
| 46 |
+
zero_stage: 1
|
| 47 |
+
parallelism:
|
| 48 |
+
dp: 1
|
| 49 |
+
expert_parallel_size: 1
|
| 50 |
+
pp: 1
|
| 51 |
+
pp_engine: 1f1b
|
| 52 |
+
tp: 8
|
| 53 |
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tp_linear_async_communication: false
|
| 54 |
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tp_mode: REDUCE_SCATTER
|
| 55 |
+
profiler:
|
| 56 |
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profiler_export_path: /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64
|
| 57 |
+
tokenizer:
|
| 58 |
+
tokenizer_max_length: null
|
| 59 |
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tokenizer_name_or_path: openai-community/gpt2
|
| 60 |
+
tokenizer_revision: null
|
| 61 |
+
data_stages:
|
| 62 |
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- name: Training Stage
|
| 63 |
+
start_training_step: 1
|
| 64 |
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data:
|
| 65 |
+
dataset:
|
| 66 |
+
dataset_overwrite_cache: false
|
| 67 |
+
dataset_processing_num_proc_per_process: 64
|
| 68 |
+
hf_dataset_config_name: null
|
| 69 |
+
hf_dataset_or_datasets: roneneldan/TinyStories
|
| 70 |
+
hf_dataset_splits: train
|
| 71 |
+
text_column_name: text
|
| 72 |
+
num_loading_workers: 0
|
| 73 |
+
seed: 42
|
| 74 |
+
lighteval: null
|
| 75 |
+
tokens:
|
| 76 |
+
train_steps: 20
|
| 77 |
+
val_check_interval: -1
|
| 78 |
+
batch_accumulation_per_replica: 16
|
| 79 |
+
limit_test_batches: 0
|
| 80 |
+
limit_val_batches: 0
|
| 81 |
+
micro_batch_size: 64
|
| 82 |
+
sequence_length: 4096
|
| 83 |
+
logging:
|
| 84 |
+
iteration_step_info_interval: 1
|
| 85 |
+
log_level: info
|
| 86 |
+
log_level_replica: info
|
| 87 |
+
checkpoints:
|
| 88 |
+
checkpoint_interval: 100000
|
| 89 |
+
checkpoints_path: /dev/null
|
| 90 |
+
resume_checkpoint_path: null
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llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64/log.out
ADDED
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|
| 1 |
+
========================
|
| 2 |
+
START TIME: Wed Jul 3 22:44:22 UTC 2024
|
| 3 |
+
python3 version = Python 3.10.14
|
| 4 |
+
========================
|
| 5 |
+
The token has not been saved to the git credentials helper. Pass `add_to_git_credential=True` in this function directly or `--add-to-git-credential` if using via `huggingface-cli` if you want to set the git credential as well.
|
| 6 |
+
Token is valid (permission: write).
|
| 7 |
+
Your token has been saved to /admin/home/ferdinand_mom/.cache/huggingface/token
|
| 8 |
+
Login successful
|
| 9 |
+
Already on 'bench_cluster'
|
| 10 |
+
M examples/config_tiny_llama.py
|
| 11 |
+
M examples/config_tiny_llama.yaml
|
| 12 |
+
M examples/train_tiny_llama.sh
|
| 13 |
+
M src/nanotron/models/llama.py
|
| 14 |
+
M src/nanotron/trainer.py
|
| 15 |
+
Your branch is up to date with 'origin/bench_cluster'.
|
| 16 |
+
Job status: RUNNING
|
| 17 |
+
W0703 22:44:25.641000 139726242240320 torch/distributed/run.py:757]
|
| 18 |
+
W0703 22:44:25.641000 139726242240320 torch/distributed/run.py:757] *****************************************
|
| 19 |
+
W0703 22:44:25.641000 139726242240320 torch/distributed/run.py:757] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed.
|
| 20 |
+
W0703 22:44:25.641000 139726242240320 torch/distributed/run.py:757] *****************************************
|
| 21 |
+
[default0]:07/03/2024 22:44:42 [WARNING|DP=0|PP=0|TP=0|ip-26-0-161-178]: [Vocab Size Padding] Padded vocab (size: 50257) with 7 dummy tokens (new size: 50264)
|
| 22 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Config:
|
| 23 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Config(general=GeneralArgs(project='bench_cluster',
|
| 24 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: run='%date_%jobid',
|
| 25 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: seed=42,
|
| 26 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: step=None,
|
| 27 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: consumed_train_samples=None,
|
| 28 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: benchmark_csv_path=None,
|
| 29 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: ignore_sanity_checks=True),
|
| 30 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: parallelism=ParallelismArgs(dp=1,
|
| 31 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: pp=1,
|
| 32 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: tp=8,
|
| 33 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: pp_engine=<nanotron.parallel.pipeline_parallel.engine.OneForwardOneBackwardPipelineEngine object at 0x7feccf030940>,
|
| 34 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: tp_mode=<TensorParallelLinearMode.REDUCE_SCATTER: 2>,
|
| 35 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: tp_linear_async_communication=False,
|
| 36 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: expert_parallel_size=1),
|
| 37 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: model=ModelArgs(model_config=LlamaConfig(bos_token_id=1,
|
| 38 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: eos_token_id=2,
|
| 39 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: hidden_act='silu',
|
| 40 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: hidden_size=2048,
|
| 41 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: initializer_range=0.02,
|
| 42 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: intermediate_size=4096,
|
| 43 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: is_llama_config=True,
|
| 44 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: max_position_embeddings=4096,
|
| 45 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: num_attention_heads=32,
|
| 46 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: num_hidden_layers=24,
|
| 47 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: num_key_value_heads=32,
|
| 48 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: pad_token_id=None,
|
| 49 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: pretraining_tp=1,
|
| 50 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: rms_norm_eps=1e-05,
|
| 51 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: rope_scaling=None,
|
| 52 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: rope_theta=10000.0,
|
| 53 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: tie_word_embeddings=True,
|
| 54 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: use_cache=True,
|
| 55 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: vocab_size=50264),
|
| 56 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: init_method=RandomInit(std=0.025),
|
| 57 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: dtype=torch.bfloat16,
|
| 58 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: make_vocab_size_divisible_by=1,
|
| 59 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: ddp_bucket_cap_mb=25),
|
| 60 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2',
|
| 61 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: tokenizer_revision=None,
|
| 62 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: tokenizer_max_length=None),
|
| 63 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: checkpoints=CheckpointsArgs(checkpoints_path=Path('/dev/null'),
|
| 64 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: checkpoint_interval=100000,
|
| 65 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: save_initial_state=False,
|
| 66 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: resume_checkpoint_path=None,
|
| 67 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: checkpoints_path_is_shared_file_system=False),
|
| 68 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: logging=LoggingArgs(log_level='info',
|
| 69 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: log_level_replica='info',
|
| 70 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: iteration_step_info_interval=1),
|
| 71 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: tokens=TokensArgs(sequence_length=4096,
|
| 72 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: train_steps=20,
|
| 73 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: micro_batch_size=64,
|
| 74 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: batch_accumulation_per_replica=16,
|
| 75 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: val_check_interval=-1,
|
| 76 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: limit_val_batches=0,
|
| 77 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: limit_test_batches=0),
|
| 78 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08,
|
| 79 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: adam_beta1=0.9,
|
| 80 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: adam_beta2=0.95,
|
| 81 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: torch_adam_is_fused=True,
|
| 82 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: name='adamW'),
|
| 83 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: zero_stage=1,
|
| 84 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: weight_decay=0.01,
|
| 85 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: clip_grad=1.0,
|
| 86 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: accumulate_grad_in_fp32=True,
|
| 87 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001,
|
| 88 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: lr_warmup_steps=1,
|
| 89 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: lr_warmup_style='linear',
|
| 90 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: lr_decay_style='linear',
|
| 91 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: lr_decay_steps=19,
|
| 92 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: lr_decay_starting_step=None,
|
| 93 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: min_decay_lr=1e-05)),
|
| 94 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: data_stages=[DatasetStageArgs(name='Training Stage',
|
| 95 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: start_training_step=1,
|
| 96 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories',
|
| 97 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: hf_dataset_splits='train',
|
| 98 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: hf_dataset_config_name=None,
|
| 99 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: dataset_processing_num_proc_per_process=64,
|
| 100 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: dataset_overwrite_cache=False,
|
| 101 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: text_column_name='text'),
|
| 102 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: seed=42,
|
| 103 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: num_loading_workers=0))],
|
| 104 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: profiler=ProfilerArgs(profiler_export_path=Path('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64')),
|
| 105 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: lighteval=None)
|
| 106 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Model Config:
|
| 107 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: LlamaConfig(bos_token_id=1,
|
| 108 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: eos_token_id=2,
|
| 109 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: hidden_act='silu',
|
| 110 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: hidden_size=2048,
|
| 111 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: initializer_range=0.02,
|
| 112 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: intermediate_size=4096,
|
| 113 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: is_llama_config=True,
|
| 114 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: max_position_embeddings=4096,
|
| 115 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: num_attention_heads=32,
|
| 116 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: num_hidden_layers=24,
|
| 117 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: num_key_value_heads=32,
|
| 118 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: pad_token_id=None,
|
| 119 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: pretraining_tp=1,
|
| 120 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: rms_norm_eps=1e-05,
|
| 121 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: rope_scaling=None,
|
| 122 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: rope_theta=10000.0,
|
| 123 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: tie_word_embeddings=True,
|
| 124 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: use_cache=True,
|
| 125 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: vocab_size=50264)
|
| 126 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Building model..
|
| 127 |
+
[default0]:07/03/2024 22:44:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Setting PP block ranks...
|
| 128 |
+
[default3]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=3|ip-26-0-161-178]: Local number of parameters: 139M (264.73MiB)
|
| 129 |
+
[default3]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=3|ip-26-0-161-178]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB
|
| 130 |
+
[default3]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=3|ip-26-0-161-178]: No checkpoint path provided.
|
| 131 |
+
[default7]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=7|ip-26-0-161-178]: Local number of parameters: 139M (264.73MiB)
|
| 132 |
+
[default7]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=7|ip-26-0-161-178]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB
|
| 133 |
+
[default7]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=7|ip-26-0-161-178]: No checkpoint path provided.
|
| 134 |
+
[default0]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Total number of parameters: 1.11G (2117.88MiB)
|
| 135 |
+
[default0]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Local number of parameters: 139M (264.73MiB)
|
| 136 |
+
[default0]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB
|
| 137 |
+
[default0]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: No checkpoint path provided.
|
| 138 |
+
[default0]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Parametrizing model parameters using StandardParametrizator
|
| 139 |
+
[default0]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: [Optimizer Building] Using LearningRateForSP as learning rate
|
| 140 |
+
[default0]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: [ZeRO sharding] Size of optimizer params per rank:
|
| 141 |
+
[default0]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: [ZeRO sharding] DP Rank 0 has 139M out of 139M (100.00%) params' optimizer states
|
| 142 |
+
[default1]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=1|ip-26-0-161-178]: Local number of parameters: 139M (264.73MiB)
|
| 143 |
+
[default1]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=1|ip-26-0-161-178]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB
|
| 144 |
+
[default1]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=1|ip-26-0-161-178]: No checkpoint path provided.
|
| 145 |
+
[default4]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=4|ip-26-0-161-178]: Local number of parameters: 139M (264.73MiB)
|
| 146 |
+
[default4]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=4|ip-26-0-161-178]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB
|
| 147 |
+
[default4]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=4|ip-26-0-161-178]: No checkpoint path provided.
|
| 148 |
+
[default2]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=2|ip-26-0-161-178]: Local number of parameters: 139M (264.73MiB)
|
| 149 |
+
[default2]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=2|ip-26-0-161-178]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB
|
| 150 |
+
[default2]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=2|ip-26-0-161-178]: No checkpoint path provided.
|
| 151 |
+
[default6]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=6|ip-26-0-161-178]: Local number of parameters: 139M (264.73MiB)
|
| 152 |
+
[default6]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=6|ip-26-0-161-178]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB
|
| 153 |
+
[default5]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=5|ip-26-0-161-178]: Local number of parameters: 139M (264.73MiB)
|
| 154 |
+
[default5]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=5|ip-26-0-161-178]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB
|
| 155 |
+
[default5]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=5|ip-26-0-161-178]: No checkpoint path provided.
|
| 156 |
+
[default6]:07/03/2024 22:44:57 [INFO|DP=0|PP=0|TP=6|ip-26-0-161-178]: No checkpoint path provided.
|
| 157 |
+
[default0]:07/03/2024 22:44:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples
|
| 158 |
+
[default0]:07/03/2024 22:44:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Using `datasets` library
|
| 159 |
+
[default0]:07/03/2024 22:44:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Loading tokenizer from openai-community/gpt2 and transformers/hf_hub versions ('4.41.2', '0.23.4')
|
| 160 |
+
[default0]:07/03/2024 22:44:58 [WARNING|DP=0|PP=0|TP=0|ip-26-0-161-178]: Repo card metadata block was not found. Setting CardData to empty.
|
| 161 |
+
[default0]:Repo card metadata block was not found. Setting CardData to empty.
|
| 162 |
+
[default0]:07/03/2024 22:44:59 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: [Training Plan] There are 1 training stages
|
| 163 |
+
[default0]:07/03/2024 22:44:59 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: [Stage Training Stage] start from step 1
|
| 164 |
+
[default0]:07/03/2024 22:44:59 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]:
|
| 165 |
+
[default0]:07/03/2024 22:44:59 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: [Start training] datetime: 2024-07-03 22:44:59.542192 | mbs: 64 | grad_accum: 16 | global_batch_size: 1024 | sequence_length: 4096 | train_steps: 20 | start_iteration_step: 0 | consumed_train_samples: 0
|
| 166 |
+
[default0]:07/03/2024 22:44:59 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps
|
| 167 |
+
[default0]:07/03/2024 22:44:59 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Memory usage: 1350.75MiB. Peak allocated 1350.76MiB. Peak reserved: 1384.00MiB
|
| 168 |
+
[default4]:Repo card metadata block was not found. Setting CardData to empty.
|
| 169 |
+
[default4]:07/03/2024 22:44:59 [WARNING|DP=0|PP=0|TP=4|ip-26-0-161-178]: Repo card metadata block was not found. Setting CardData to empty.
|
| 170 |
+
[default6]:Repo card metadata block was not found. Setting CardData to empty.
|
| 171 |
+
[default6]:07/03/2024 22:44:59 [WARNING|DP=0|PP=0|TP=6|ip-26-0-161-178]: Repo card metadata block was not found. Setting CardData to empty.
|
| 172 |
+
[default3]:07/03/2024 22:44:59 [WARNING|DP=0|PP=0|TP=3|ip-26-0-161-178]: Repo card metadata block was not found. Setting CardData to empty.
|
| 173 |
+
[default7]:07/03/2024 22:44:59 [WARNING|DP=0|PP=0|TP=7|ip-26-0-161-178]: Repo card metadata block was not found. Setting CardData to empty.
|
| 174 |
+
[default1]:07/03/2024 22:44:59 [WARNING|DP=0|PP=0|TP=1|ip-26-0-161-178]: Repo card metadata block was not found. Setting CardData to empty.
|
| 175 |
+
[default2]:Repo card metadata block was not found. Setting CardData to empty.
|
| 176 |
+
[default1]:Repo card metadata block was not found. Setting CardData to empty.
|
| 177 |
+
[default7]:Repo card metadata block was not found. Setting CardData to empty.
|
| 178 |
+
[default2]:07/03/2024 22:44:59 [WARNING|DP=0|PP=0|TP=2|ip-26-0-161-178]: Repo card metadata block was not found. Setting CardData to empty.
|
| 179 |
+
[default5]:07/03/2024 22:44:59 [WARNING|DP=0|PP=0|TP=5|ip-26-0-161-178]: Repo card metadata block was not found. Setting CardData to empty.
|
| 180 |
+
[default3]:Repo card metadata block was not found. Setting CardData to empty.
|
| 181 |
+
[default5]:Repo card metadata block was not found. Setting CardData to empty.
|
| 182 |
+
[default1]:07/03/2024 22:45:10 [WARNING|DP=0|PP=0|TP=1|ip-26-0-161-178]: Using the latest cached version of the dataset since roneneldan/TinyStories couldn't be found on the Hugging Face Hub
|
| 183 |
+
[default1]:07/03/2024 22:45:10 [WARNING|DP=0|PP=0|TP=1|ip-26-0-161-178]: Found the latest cached dataset configuration 'default' at /admin/home/ferdinand_mom/.cache/roneneldan___tiny_stories/default/0.0.0/691b0d9bd48ade766778c940011ca1c549f6359b (last modified on Mon Jun 24 07:59:52 2024).
|
| 184 |
+
[default1]:Using the latest cached version of the dataset since roneneldan/TinyStories couldn't be found on the Hugging Face Hub
|
| 185 |
+
[default1]:Found the latest cached dataset configuration 'default' at /admin/home/ferdinand_mom/.cache/roneneldan___tiny_stories/default/0.0.0/691b0d9bd48ade766778c940011ca1c549f6359b (last modified on Mon Jun 24 07:59:52 2024).
|
| 186 |
+
[default2]:[rank2]: Traceback (most recent call last):
|
| 187 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
|
| 188 |
+
[default2]:[rank2]: trainer.train(dataloader)
|
| 189 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
|
| 190 |
+
[default2]:[rank2]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
|
| 191 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
|
| 192 |
+
[default2]:[rank2]: outputs = self.pipeline_engine.train_batch_iter(
|
| 193 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
|
| 194 |
+
[default2]:[rank2]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
|
| 195 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
|
| 196 |
+
[default2]:[rank2]: output = model(**micro_batch)
|
| 197 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 198 |
+
[default2]:[rank2]: return self._call_impl(*args, **kwargs)
|
| 199 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 200 |
+
[default2]:[rank2]: return forward_call(*args, **kwargs)
|
| 201 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
|
| 202 |
+
[default2]:[rank2]: sharded_logits = self.model(
|
| 203 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 204 |
+
[default2]:[rank2]: return self._call_impl(*args, **kwargs)
|
| 205 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 206 |
+
[default2]:[rank2]: return forward_call(*args, **kwargs)
|
| 207 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
|
| 208 |
+
[default2]:[rank2]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
|
| 209 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
|
| 210 |
+
[default2]:[rank2]: hidden_encoder_states = encoder_block(**hidden_encoder_states)
|
| 211 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 212 |
+
[default2]:[rank2]: return self._call_impl(*args, **kwargs)
|
| 213 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 214 |
+
[default2]:[rank2]: return forward_call(*args, **kwargs)
|
| 215 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
|
| 216 |
+
[default2]:[rank2]: output = self.pp_block(**new_kwargs)
|
| 217 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 218 |
+
[default2]:[rank2]: return self._call_impl(*args, **kwargs)
|
| 219 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 220 |
+
[default2]:[rank2]: return forward_call(*args, **kwargs)
|
| 221 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward
|
| 222 |
+
[default2]:[rank2]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
|
| 223 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 224 |
+
[default2]:[rank2]: return self._call_impl(*args, **kwargs)
|
| 225 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 226 |
+
[default2]:[rank2]: return forward_call(*args, **kwargs)
|
| 227 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward
|
| 228 |
+
[default2]:[rank2]: hidden_states = self.down_proj(self.split_silu_mul(merged_states))
|
| 229 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 230 |
+
[default2]:[rank2]: return self._call_impl(*args, **kwargs)
|
| 231 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 232 |
+
[default2]:[rank2]: return forward_call(*args, **kwargs)
|
| 233 |
+
[default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 128, in forward
|
| 234 |
+
[default2]:[rank2]: return self.act(gate_states) * up_states
|
| 235 |
+
[default2]:[rank2]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU has a total capacity of 79.33 GiB of which 101.94 MiB is free. Including non-PyTorch memory, this process has 79.22 GiB memory in use. Of the allocated memory 67.43 GiB is allocated by PyTorch, and 50.47 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
|
| 236 |
+
[default1]:[rank1]: Traceback (most recent call last):
|
| 237 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
|
| 238 |
+
[default1]:[rank1]: trainer.train(dataloader)
|
| 239 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
|
| 240 |
+
[default1]:[rank1]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
|
| 241 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
|
| 242 |
+
[default1]:[rank1]: outputs = self.pipeline_engine.train_batch_iter(
|
| 243 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
|
| 244 |
+
[default1]:[rank1]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
|
| 245 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
|
| 246 |
+
[default1]:[rank1]: output = model(**micro_batch)
|
| 247 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 248 |
+
[default1]:[rank1]: return self._call_impl(*args, **kwargs)
|
| 249 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 250 |
+
[default1]:[rank1]: return forward_call(*args, **kwargs)
|
| 251 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
|
| 252 |
+
[default1]:[rank1]: sharded_logits = self.model(
|
| 253 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 254 |
+
[default1]:[rank1]: return self._call_impl(*args, **kwargs)
|
| 255 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 256 |
+
[default1]:[rank1]: return forward_call(*args, **kwargs)
|
| 257 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
|
| 258 |
+
[default1]:[rank1]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
|
| 259 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
|
| 260 |
+
[default1]:[rank1]: hidden_encoder_states = encoder_block(**hidden_encoder_states)
|
| 261 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 262 |
+
[default1]:[rank1]: return self._call_impl(*args, **kwargs)
|
| 263 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 264 |
+
[default1]:[rank1]: return forward_call(*args, **kwargs)
|
| 265 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
|
| 266 |
+
[default1]:[rank1]: output = self.pp_block(**new_kwargs)
|
| 267 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 268 |
+
[default1]:[rank1]: return self._call_impl(*args, **kwargs)
|
| 269 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 270 |
+
[default1]:[rank1]: return forward_call(*args, **kwargs)
|
| 271 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward
|
| 272 |
+
[default1]:[rank1]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
|
| 273 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 274 |
+
[default1]:[rank1]: return self._call_impl(*args, **kwargs)
|
| 275 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 276 |
+
[default1]:[rank1]: return forward_call(*args, **kwargs)
|
| 277 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward
|
| 278 |
+
[default1]:[rank1]: hidden_states = self.down_proj(self.split_silu_mul(merged_states))
|
| 279 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 280 |
+
[default1]:[rank1]: return self._call_impl(*args, **kwargs)
|
| 281 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 282 |
+
[default1]:[rank1]: return forward_call(*args, **kwargs)
|
| 283 |
+
[default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 128, in forward
|
| 284 |
+
[default1]:[rank1]: return self.act(gate_states) * up_states
|
| 285 |
+
[default1]:[rank1]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU has a total capacity of 79.33 GiB of which 101.94 MiB is free. Including non-PyTorch memory, this process has 79.22 GiB memory in use. Of the allocated memory 67.43 GiB is allocated by PyTorch, and 50.47 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
|
| 286 |
+
[default4]:[rank4]: Traceback (most recent call last):
|
| 287 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
|
| 288 |
+
[default4]:[rank4]: trainer.train(dataloader)
|
| 289 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
|
| 290 |
+
[default4]:[rank4]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
|
| 291 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
|
| 292 |
+
[default4]:[rank4]: outputs = self.pipeline_engine.train_batch_iter(
|
| 293 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
|
| 294 |
+
[default4]:[rank4]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
|
| 295 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
|
| 296 |
+
[default4]:[rank4]: output = model(**micro_batch)
|
| 297 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 298 |
+
[default4]:[rank4]: return self._call_impl(*args, **kwargs)
|
| 299 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 300 |
+
[default4]:[rank4]: return forward_call(*args, **kwargs)
|
| 301 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
|
| 302 |
+
[default4]:[rank4]: sharded_logits = self.model(
|
| 303 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 304 |
+
[default4]:[rank4]: return self._call_impl(*args, **kwargs)
|
| 305 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 306 |
+
[default4]:[rank4]: return forward_call(*args, **kwargs)
|
| 307 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
|
| 308 |
+
[default4]:[rank4]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
|
| 309 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
|
| 310 |
+
[default4]:[rank4]: hidden_encoder_states = encoder_block(**hidden_encoder_states)
|
| 311 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 312 |
+
[default4]:[rank4]: return self._call_impl(*args, **kwargs)
|
| 313 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 314 |
+
[default4]:[rank4]: return forward_call(*args, **kwargs)
|
| 315 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
|
| 316 |
+
[default4]:[rank4]: output = self.pp_block(**new_kwargs)
|
| 317 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 318 |
+
[default4]:[rank4]: return self._call_impl(*args, **kwargs)
|
| 319 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 320 |
+
[default4]:[rank4]: return forward_call(*args, **kwargs)
|
| 321 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward
|
| 322 |
+
[default4]:[rank4]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
|
| 323 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 324 |
+
[default4]:[rank4]: return self._call_impl(*args, **kwargs)
|
| 325 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 326 |
+
[default4]:[rank4]: return forward_call(*args, **kwargs)
|
| 327 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward
|
| 328 |
+
[default4]:[rank4]: hidden_states = self.down_proj(self.split_silu_mul(merged_states))
|
| 329 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 330 |
+
[default4]:[rank4]: return self._call_impl(*args, **kwargs)
|
| 331 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 332 |
+
[default4]:[rank4]: return forward_call(*args, **kwargs)
|
| 333 |
+
[default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 128, in forward
|
| 334 |
+
[default4]:[rank4]: return self.act(gate_states) * up_states
|
| 335 |
+
[default4]:[rank4]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU has a total capacity of 79.33 GiB of which 101.94 MiB is free. Including non-PyTorch memory, this process has 79.22 GiB memory in use. Of the allocated memory 67.43 GiB is allocated by PyTorch, and 50.47 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
|
| 336 |
+
[default7]:[rank7]: Traceback (most recent call last):
|
| 337 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
|
| 338 |
+
[default7]:[rank7]: trainer.train(dataloader)
|
| 339 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
|
| 340 |
+
[default7]:[rank7]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
|
| 341 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
|
| 342 |
+
[default7]:[rank7]: outputs = self.pipeline_engine.train_batch_iter(
|
| 343 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
|
| 344 |
+
[default7]:[rank7]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
|
| 345 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
|
| 346 |
+
[default7]:[rank7]: output = model(**micro_batch)
|
| 347 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 348 |
+
[default7]:[rank7]: return self._call_impl(*args, **kwargs)
|
| 349 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 350 |
+
[default7]:[rank7]: return forward_call(*args, **kwargs)
|
| 351 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
|
| 352 |
+
[default7]:[rank7]: sharded_logits = self.model(
|
| 353 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 354 |
+
[default7]:[rank7]: return self._call_impl(*args, **kwargs)
|
| 355 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 356 |
+
[default7]:[rank7]: return forward_call(*args, **kwargs)
|
| 357 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
|
| 358 |
+
[default7]:[rank7]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
|
| 359 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
|
| 360 |
+
[default7]:[rank7]: hidden_encoder_states = encoder_block(**hidden_encoder_states)
|
| 361 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 362 |
+
[default7]:[rank7]: return self._call_impl(*args, **kwargs)
|
| 363 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 364 |
+
[default7]:[rank7]: return forward_call(*args, **kwargs)
|
| 365 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
|
| 366 |
+
[default7]:[rank7]: output = self.pp_block(**new_kwargs)
|
| 367 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 368 |
+
[default7]:[rank7]: return self._call_impl(*args, **kwargs)
|
| 369 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 370 |
+
[default7]:[rank7]: return forward_call(*args, **kwargs)
|
| 371 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward
|
| 372 |
+
[default7]:[rank7]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
|
| 373 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 374 |
+
[default7]:[rank7]: return self._call_impl(*args, **kwargs)
|
| 375 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 376 |
+
[default7]:[rank7]: return forward_call(*args, **kwargs)
|
| 377 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward
|
| 378 |
+
[default7]:[rank7]: hidden_states = self.down_proj(self.split_silu_mul(merged_states))
|
| 379 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 380 |
+
[default7]:[rank7]: return self._call_impl(*args, **kwargs)
|
| 381 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 382 |
+
[default7]:[rank7]: return forward_call(*args, **kwargs)
|
| 383 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward
|
| 384 |
+
[default7]:[rank7]: return row_linear(
|
| 385 |
+
[default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear
|
| 386 |
+
[default7]:[rank7]: out = F.linear(input, weight, bias)
|
| 387 |
+
[default7]:[rank7]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 1024.00 MiB. GPU has a total capacity of 79.33 GiB of which 565.94 MiB is free. Including non-PyTorch memory, this process has 78.77 GiB memory in use. Of the allocated memory 67.68 GiB is allocated by PyTorch, and 50.47 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
|
| 388 |
+
[default6]:[rank6]: Traceback (most recent call last):
|
| 389 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
|
| 390 |
+
[default6]:[rank6]: trainer.train(dataloader)
|
| 391 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
|
| 392 |
+
[default6]:[rank6]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
|
| 393 |
+
[default0]:[rank0]: Traceback (most recent call last):
|
| 394 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
|
| 395 |
+
[default0]:[rank0]: trainer.train(dataloader)
|
| 396 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
|
| 397 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
|
| 398 |
+
[default6]:[rank6]: outputs = self.pipeline_engine.train_batch_iter(
|
| 399 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
|
| 400 |
+
[default6]:[rank6]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
|
| 401 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
|
| 402 |
+
[default0]:[rank0]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
|
| 403 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
|
| 404 |
+
[default6]:[rank6]: output = model(**micro_batch)
|
| 405 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 406 |
+
[default0]:[rank0]: outputs = self.pipeline_engine.train_batch_iter(
|
| 407 |
+
[default6]:[rank6]: return self._call_impl(*args, **kwargs)
|
| 408 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 409 |
+
[default6]:[rank6]: return forward_call(*args, **kwargs)
|
| 410 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
|
| 411 |
+
[default6]:[rank6]: sharded_logits = self.model(
|
| 412 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
|
| 413 |
+
[default0]:[rank0]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
|
| 414 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 415 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
|
| 416 |
+
[default0]:[rank0]: output = model(**micro_batch)
|
| 417 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 418 |
+
[default6]:[rank6]: return self._call_impl(*args, **kwargs)
|
| 419 |
+
[default0]:[rank0]: return self._call_impl(*args, **kwargs)
|
| 420 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 421 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 422 |
+
[default6]:[rank6]: return forward_call(*args, **kwargs)
|
| 423 |
+
[default0]:[rank0]: return forward_call(*args, **kwargs)
|
| 424 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
|
| 425 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
|
| 426 |
+
[default0]:[rank0]: sharded_logits = self.model(
|
| 427 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 428 |
+
[default0]:[rank0]: return self._call_impl(*args, **kwargs)
|
| 429 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 430 |
+
[default0]:[rank0]: return forward_call(*args, **kwargs)
|
| 431 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
|
| 432 |
+
[default6]:[rank6]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
|
| 433 |
+
[default0]:[rank0]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
|
| 434 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
|
| 435 |
+
[default6]:[rank6]: hidden_encoder_states = encoder_block(**hidden_encoder_states)
|
| 436 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
|
| 437 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 438 |
+
[default0]:[rank0]: hidden_encoder_states = encoder_block(**hidden_encoder_states)
|
| 439 |
+
[default6]:[rank6]: return self._call_impl(*args, **kwargs)
|
| 440 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 441 |
+
[default6]:[rank6]: return forward_call(*args, **kwargs)
|
| 442 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
|
| 443 |
+
[default6]:[rank6]: output = self.pp_block(**new_kwargs)
|
| 444 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 445 |
+
[default6]:[rank6]: return self._call_impl(*args, **kwargs)
|
| 446 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 447 |
+
[default6]:[rank6]: return forward_call(*args, **kwargs)
|
| 448 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward
|
| 449 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 450 |
+
[default0]:[rank0]: return self._call_impl(*args, **kwargs)
|
| 451 |
+
[default6]:[rank6]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
|
| 452 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 453 |
+
[default0]:[rank0]: return forward_call(*args, **kwargs)
|
| 454 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 455 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
|
| 456 |
+
[default6]:[rank6]: return self._call_impl(*args, **kwargs)
|
| 457 |
+
[default0]:[rank0]: output = self.pp_block(**new_kwargs)
|
| 458 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 459 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 460 |
+
[default0]:[rank0]: return self._call_impl(*args, **kwargs)
|
| 461 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 462 |
+
[default0]:[rank0]: return forward_call(*args, **kwargs)
|
| 463 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward
|
| 464 |
+
[default0]:[rank0]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
|
| 465 |
+
[default6]:[rank6]: return forward_call(*args, **kwargs)
|
| 466 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 467 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward
|
| 468 |
+
[default0]:[rank0]: return self._call_impl(*args, **kwargs)
|
| 469 |
+
[default6]:[rank6]: hidden_states = self.down_proj(self.split_silu_mul(merged_states))
|
| 470 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 471 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 472 |
+
[default0]:[rank0]: return forward_call(*args, **kwargs)
|
| 473 |
+
[default6]:[rank6]: return self._call_impl(*args, **kwargs)
|
| 474 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward
|
| 475 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 476 |
+
[default0]:[rank0]: hidden_states = self.down_proj(self.split_silu_mul(merged_states))
|
| 477 |
+
[default6]:[rank6]: return forward_call(*args, **kwargs)
|
| 478 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 479 |
+
[default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 128, in forward
|
| 480 |
+
[default0]:[rank0]: return self._call_impl(*args, **kwargs)
|
| 481 |
+
[default6]:[rank6]: return self.act(gate_states) * up_states
|
| 482 |
+
[default6]:[rank6]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU has a total capacity of 79.33 GiB of which 101.94 MiB is free. Including non-PyTorch memory, this process has 79.22 GiB memory in use. Of the allocated memory 67.43 GiB is allocated by PyTorch, and 50.47 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
|
| 483 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 484 |
+
[default0]:[rank0]: return forward_call(*args, **kwargs)
|
| 485 |
+
[default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 128, in forward
|
| 486 |
+
[default0]:[rank0]: return self.act(gate_states) * up_states
|
| 487 |
+
[default0]:[rank0]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU
|
| 488 |
+
[default3]:[rank3]: Traceback (most recent call last):
|
| 489 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
|
| 490 |
+
[default3]:[rank3]: trainer.train(dataloader)
|
| 491 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
|
| 492 |
+
[default3]:[rank3]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
|
| 493 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
|
| 494 |
+
[default3]:[rank3]: outputs = self.pipeline_engine.train_batch_iter(
|
| 495 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
|
| 496 |
+
[default5]:[rank5]: Traceback (most recent call last):
|
| 497 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
|
| 498 |
+
[default5]:[rank5]: trainer.train(dataloader)
|
| 499 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
|
| 500 |
+
[default5]:[rank5]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
|
| 501 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
|
| 502 |
+
[default3]:[rank3]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
|
| 503 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
|
| 504 |
+
[default3]:[rank3]: output = model(**micro_batch)
|
| 505 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 506 |
+
[default3]:[rank3]: return self._call_impl(*args, **kwargs)
|
| 507 |
+
[default5]:[rank5]: outputs = self.pipeline_engine.train_batch_iter(
|
| 508 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
|
| 509 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 510 |
+
[default3]:[rank3]: return forward_call(*args, **kwargs)
|
| 511 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
|
| 512 |
+
[default3]:[rank3]: sharded_logits = self.model(
|
| 513 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 514 |
+
[default5]:[rank5]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
|
| 515 |
+
[default3]:[rank3]: return self._call_impl(*args, **kwargs)
|
| 516 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
|
| 517 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 518 |
+
[default3]:[rank3]: return forward_call(*args, **kwargs)
|
| 519 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
|
| 520 |
+
[default3]:[rank3]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
|
| 521 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
|
| 522 |
+
[default3]:[rank3]: hidden_encoder_states = encoder_block(**hidden_encoder_states)
|
| 523 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 524 |
+
[default3]:[rank3]: return self._call_impl(*args, **kwargs)
|
| 525 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 526 |
+
[default3]:[rank3]: return forward_call(*args, **kwargs)
|
| 527 |
+
[default5]:[rank5]: output = model(**micro_batch)
|
| 528 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
|
| 529 |
+
[default3]:[rank3]: output = self.pp_block(**new_kwargs)
|
| 530 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 531 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 532 |
+
[default5]:[rank5]: return self._call_impl(*args, **kwargs)
|
| 533 |
+
[default3]:[rank3]: return self._call_impl(*args, **kwargs)
|
| 534 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 535 |
+
[default5]:[rank5]: return forward_call(*args, **kwargs)
|
| 536 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
|
| 537 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 538 |
+
[default5]:[rank5]: sharded_logits = self.model(
|
| 539 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 540 |
+
[default5]:[rank5]: return self._call_impl(*args, **kwargs)
|
| 541 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 542 |
+
[default5]:[rank5]: return forward_call(*args, **kwargs)
|
| 543 |
+
[default3]:[rank3]: return forward_call(*args, **kwargs)
|
| 544 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
|
| 545 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward
|
| 546 |
+
[default5]:[rank5]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
|
| 547 |
+
[default3]:[rank3]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
|
| 548 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 549 |
+
[default3]:[rank3]: return self._call_impl(*args, **kwargs)
|
| 550 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 551 |
+
[default3]:[rank3]: return forward_call(*args, **kwargs)
|
| 552 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
|
| 553 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward
|
| 554 |
+
[default5]:[rank5]: hidden_encoder_states = encoder_block(**hidden_encoder_states)
|
| 555 |
+
[default3]:[rank3]: hidden_states = self.down_proj(self.split_silu_mul(merged_states))
|
| 556 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 557 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 558 |
+
[default5]:[rank5]: return self._call_impl(*args, **kwargs)
|
| 559 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 560 |
+
[default3]:[rank3]: return self._call_impl(*args, **kwargs)
|
| 561 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 562 |
+
[default5]:[rank5]: return forward_call(*args, **kwargs)
|
| 563 |
+
[default3]:[rank3]: return forward_call(*args, **kwargs)
|
| 564 |
+
[default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 128, in forward
|
| 565 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
|
| 566 |
+
[default5]:[rank5]: output = self.pp_block(**new_kwargs)
|
| 567 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 568 |
+
[default5]:[rank5]: return self._call_impl(*args, **kwargs)
|
| 569 |
+
[default3]:[rank3]: return self.act(gate_states) * up_states
|
| 570 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 571 |
+
[default3]:[rank3]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU has a total capacity of 79.33 GiB of which 101.94 MiB is free. Including non-PyTorch memory, this process has 79.22 GiB memory in use. Of the allocated memory 67.43 GiB is allocated by PyTorch, and 50.47 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
|
| 572 |
+
[default5]:[rank5]: return forward_call(*args, **kwargs)
|
| 573 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward
|
| 574 |
+
[default5]:[rank5]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
|
| 575 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 576 |
+
[default5]:[rank5]: return self._call_impl(*args, **kwargs)
|
| 577 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 578 |
+
[default5]:[rank5]: return forward_call(*args, **kwargs)
|
| 579 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward
|
| 580 |
+
[default5]:[rank5]: hidden_states = self.down_proj(self.split_silu_mul(merged_states))
|
| 581 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
|
| 582 |
+
[default5]:[rank5]: return self._call_impl(*args, **kwargs)
|
| 583 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
|
| 584 |
+
[default5]:[rank5]: return forward_call(*args, **kwargs)
|
| 585 |
+
[default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 128, in forward
|
| 586 |
+
[default5]:[rank5]: return self.act(gate_states) * up_states
|
| 587 |
+
[default5]:[rank5]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU has a total capacity of 79.33 GiB of which 101.94 MiB is free. Including non-PyTorch memory, this process has 79.22 GiB memory in use. Of the allocated memory 67.43 GiB is allocated by PyTorch, and 50.47 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
|
| 588 |
+
E0703 22:45:21.130000 139726242240320 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: 1) local_rank: 0 (pid: 1029082) of binary: /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10
|
| 589 |
+
Traceback (most recent call last):
|
| 590 |
+
File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in <module>
|
| 591 |
+
sys.exit(main())
|
| 592 |
+
File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper
|
| 593 |
+
return f(*args, **kwargs)
|
| 594 |
+
File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 879, in main
|
| 595 |
+
run(args)
|
| 596 |
+
File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 870, in run
|
| 597 |
+
elastic_launch(
|
| 598 |
+
File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 132, in __call__
|
| 599 |
+
return launch_agent(self._config, self._entrypoint, list(args))
|
| 600 |
+
File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 263, in launch_agent
|
| 601 |
+
raise ChildFailedError(
|
| 602 |
+
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
|
| 603 |
+
============================================================
|
| 604 |
+
/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py FAILED
|
| 605 |
+
------------------------------------------------------------
|
| 606 |
+
Failures:
|
| 607 |
+
[1]:
|
| 608 |
+
time : 2024-07-03_22:45:21
|
| 609 |
+
host : ip-26-0-161-178.ec2.internal
|
| 610 |
+
rank : 1 (local_rank: 1)
|
| 611 |
+
exitcode : 1 (pid: 1029083)
|
| 612 |
+
error_file: <N/A>
|
| 613 |
+
traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
|
| 614 |
+
[2]:
|
| 615 |
+
time : 2024-07-03_22:45:21
|
| 616 |
+
host : ip-26-0-161-178.ec2.internal
|
| 617 |
+
rank : 2 (local_rank: 2)
|
| 618 |
+
exitcode : 1 (pid: 1029084)
|
| 619 |
+
error_file: <N/A>
|
| 620 |
+
traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
|
| 621 |
+
[3]:
|
| 622 |
+
time : 2024-07-03_22:45:21
|
| 623 |
+
host : ip-26-0-161-178.ec2.internal
|
| 624 |
+
rank : 3 (local_rank: 3)
|
| 625 |
+
exitcode : 1 (pid: 1029085)
|
| 626 |
+
error_file: <N/A>
|
| 627 |
+
traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
|
| 628 |
+
[4]:
|
| 629 |
+
time : 2024-07-03_22:45:21
|
| 630 |
+
host : ip-26-0-161-178.ec2.internal
|
| 631 |
+
rank : 4 (local_rank: 4)
|
| 632 |
+
exitcode : 1 (pid: 1029086)
|
| 633 |
+
error_file: <N/A>
|
| 634 |
+
traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
|
| 635 |
+
[5]:
|
| 636 |
+
time : 2024-07-03_22:45:21
|
| 637 |
+
host : ip-26-0-161-178.ec2.internal
|
| 638 |
+
rank : 5 (local_rank: 5)
|
| 639 |
+
exitcode : 1 (pid: 1029087)
|
| 640 |
+
error_file: <N/A>
|
| 641 |
+
traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
|
| 642 |
+
[6]:
|
| 643 |
+
time : 2024-07-03_22:45:21
|
| 644 |
+
host : ip-26-0-161-178.ec2.internal
|
| 645 |
+
rank : 6 (local_rank: 6)
|
| 646 |
+
exitcode : 1 (pid: 1029088)
|
| 647 |
+
error_file: <N/A>
|
| 648 |
+
traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
|
| 649 |
+
[7]:
|
| 650 |
+
time : 2024-07-03_22:45:21
|
| 651 |
+
host : ip-26-0-161-178.ec2.internal
|
| 652 |
+
rank : 7 (local_rank: 7)
|
| 653 |
+
exitcode : 1 (pid: 1029089)
|
| 654 |
+
error_file: <N/A>
|
| 655 |
+
traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
|
| 656 |
+
------------------------------------------------------------
|
| 657 |
+
Root Cause (first observed failure):
|
| 658 |
+
[0]:
|
| 659 |
+
time : 2024-07-03_22:45:21
|
| 660 |
+
host : ip-26-0-161-178.ec2.internal
|
| 661 |
+
rank : 0 (local_rank: 0)
|
| 662 |
+
exitcode : 1 (pid: 1029082)
|
| 663 |
+
error_file: <N/A>
|
| 664 |
+
traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
|
| 665 |
+
============================================================
|
| 666 |
+
srun: error: ip-26-0-161-178: task 0: Exited with exit code 1
|
| 667 |
+
Consider using `hf_transfer` for faster uploads. This solution comes with some limitations. See https://huggingface.co/docs/huggingface_hub/hf_transfer for more details.
|
llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-64/status.txt
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
oom
|