Upload llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32

llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32/bench.slurm

@@ -0,0 +1,111 @@
+#!/bin/bash
+
+#SBATCH --job-name=bench_cluster
+#SBATCH --time=00:59:00
+#SBATCH --partition=hopper-prod
+#SBATCH --nodes=2
+#SBATCH --gres=gpu:8
+#SBATCH --qos=high
+#SBATCH --ntasks-per-node=1
+#SBATCH --cpus-per-task=96
+#SBATCH --exclusive
+#SBATCH --output=/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32/log.out
+#SBATCH --error=/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32/log.out
+
+# Function to update status based on squeue output
+update_status() {
+    job_id=$1
+    status_file=$2
+    # For unknown reasons, it doenst update status for pending. It only works for running 
+    while true; do
+        job_status=$(squeue --job $job_id --noheader --format=%T)
+        echo "Job status: $job_status"
+        if [ -z "$job_status" ]; then
+            # Job has finished or is not found
+            break
+        elif [ "$job_status" = "RUNNING" ]; then
+            printf "running" > $status_file
+            break
+        fi
+        sleep 10
+    done
+}
+
+# Misc initializations.
+echo "========================"
+echo "START TIME: $(date)"
+source /fsx/ferdinandmom/miniforge3/etc/profile.d/conda.sh
+conda activate /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster
+echo python3 version = $(python3 --version)
+echo "========================"
+
+# Slurm stuff
+export HOSTNAMES=$(scontrol show hostnames "$SLURM_JOB_NODELIST")
+export MASTER_ADDR=$(scontrol show hostnames "$SLURM_JOB_NODELIST" | head -n 1)
+export MASTER_PORT=$((1024 + RANDOM % 64511))
+
+export TMPDIR=/scratch
+export HF_DATASETS_CACHE="/admin/home/ferdinand_mom/.cache"
+export CUBLAS_WORKSPACE_CONFIG=":4096:8"
+export CUDA_DEVICE_MAX_CONNECTIONS="1"
+
+huggingface-cli login --token $HUGGINGFACE_TOKEN
+
+
+NANOTRON_REPO="/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron"
+CMD="$NANOTRON_REPO/run_train.py --config-file /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32/config.yaml"
+
+LAUNCHER="torchrun \
+   --nproc_per_node 8 \
+   --nnodes 2 \
+   --rdzv_endpoint ${MASTER_ADDR}:${MASTER_PORT} \
+   --rdzv_backend c10d \
+   --max_restarts 0 \
+   --tee 3 \
+   --node_rank ${SLURM_PROCID}"
+
+# Checkout the bench_cluster branch
+cd $NANOTRON_REPO
+git checkout bench_cluster
+cd ..
+# Get the current job ID
+job_id=${SLURM_JOB_ID}
+
+# Update status to "pending" or "running" in the background
+update_status $job_id /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32/status.txt &
+
+# Run the main command
+srun -u $LAUNCHER $CMD
+exit_status=$?
+
+# Update status based on the exit status of `srun`
+if [ $exit_status -eq 0 ]; then
+    printf "completed" > /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32/status.txt
+else
+    if grep -q "OutOfMemoryError" /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32/log.out; then
+        printf "oom" > /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32/status.txt
+    elif grep -q " CUDA error: an illegal memory access" /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32/log.out; then
+        printf "oom" > /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32/status.txt
+    elif grep -q "Timeout at NCCL" /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32/log.out; then
+        printf "timeout" > /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32/status.txt
+    else
+        printf "fail" > /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32/status.txt
+    fi 
+fi
+
+# Run the report script if the job completed successfully
+if [ $exit_status -eq 0 ]; then
+    python /fsx/ferdinandmom/ferdinand-hf/bench_cluster/main.py report --inp_dir /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32 --is_logs
+    python /fsx/ferdinandmom/ferdinand-hf/bench_cluster/main.py report --inp_dir /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32 --is_profiler
+fi
+
+
+# Push to hub the folder using huggingface_cli
+huggingface-cli upload nanotron/bench_cluster /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32 llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32 --commit-message "Upload llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32"
+
+# Verify the upload
+if [ $? -eq 0 ]; then
+    echo "Uploading to Huggingface Hub successful"
+else
+    echo "Failed to upload to Huggingface Hub"
+fi

llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32/config.yaml

@@ -0,0 +1,90 @@
+general:
+  project: bench_cluster
+  seed: 42
+model:
+  ddp_bucket_cap_mb: 25
+  dtype: bfloat16
+  init_method:
+    std: 0.025
+  make_vocab_size_divisible_by: 1
+  model_config:
+    bos_token_id: 1
+    eos_token_id: 2
+    hidden_act: silu
+    hidden_size: 2048
+    initializer_range: 0.02
+    intermediate_size: 4096
+    is_llama_config: true
+    max_position_embeddings: 4096
+    num_attention_heads: 32
+    num_hidden_layers: 24
+    num_key_value_heads: 32
+    pad_token_id: null
+    pretraining_tp: 1
+    rms_norm_eps: 1.0e-05
+    rope_scaling: null
+    rope_theta: 10000.0
+    tie_word_embeddings: true
+    use_cache: true
+    vocab_size: 50257
+optimizer:
+  accumulate_grad_in_fp32: true
+  clip_grad: 1.0
+  learning_rate_scheduler:
+    learning_rate: 0.0001
+    lr_decay_style: linear
+    lr_warmup_style: linear
+    lr_warmup_steps: 1
+    min_decay_lr: 1.0e-05
+  optimizer_factory:
+    adam_beta1: 0.9
+    adam_beta2: 0.95
+    adam_eps: 1.0e-08
+    name: adamW
+    torch_adam_is_fused: true
+  weight_decay: 0.01
+  zero_stage: 1
+parallelism:
+  dp: 1
+  expert_parallel_size: 1
+  pp: 1
+  pp_engine: 1f1b
+  tp: 16
+  tp_linear_async_communication: false
+  tp_mode: REDUCE_SCATTER
+profiler:
+  profiler_export_path: /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32
+tokenizer:
+  tokenizer_max_length: null
+  tokenizer_name_or_path: openai-community/gpt2
+  tokenizer_revision: null
+data_stages:
+- name: Training Stage
+  start_training_step: 1
+  data:
+    dataset:
+      dataset_overwrite_cache: false
+      dataset_processing_num_proc_per_process: 64
+      hf_dataset_config_name: null
+      hf_dataset_or_datasets: roneneldan/TinyStories
+      hf_dataset_splits: train
+      text_column_name: text
+    num_loading_workers: 32
+    seed: 42
+lighteval: null
+tokens:
+  train_steps: 20
+  val_check_interval: -1
+  batch_accumulation_per_replica: 32
+  limit_test_batches: 0
+  limit_val_batches: 0
+  micro_batch_size: 32
+  sequence_length: 4096
+logging:
+  iteration_step_info_interval: 1
+  log_level: info
+  log_level_replica: info
+checkpoints:
+  checkpoint_interval: 100000
+  checkpoints_path: /dev/null
+  resume_checkpoint_path: null

llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32/log.out

@@ -0,0 +1,550 @@
+========================
+START TIME: Tue Jul  2 16:31:55 UTC 2024
+python3 version = Python 3.10.14
+========================
+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.
+Token is valid (permission: write).
+Your token has been saved to /admin/home/ferdinand_mom/.cache/huggingface/token
+Login successful
+Already on 'bench_cluster'
+M	examples/config_tiny_llama.py
+M	examples/config_tiny_llama.yaml
+M	examples/train_tiny_llama.sh
+M	src/nanotron/models/llama.py
+M	src/nanotron/trainer.py
+Your branch is up to date with 'origin/bench_cluster'.
+Job status: RUNNING
+W0702 16:31:57.484000 139796830594880 torch/distributed/run.py:757] 
+W0702 16:31:57.484000 139796830594880 torch/distributed/run.py:757] *****************************************
+W0702 16:31:57.484000 139796830594880 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. 
+W0702 16:31:57.484000 139796830594880 torch/distributed/run.py:757] *****************************************
+W0702 16:31:57.490000 140386122716992 torch/distributed/run.py:757] 
+W0702 16:31:57.490000 140386122716992 torch/distributed/run.py:757] *****************************************
+W0702 16:31:57.490000 140386122716992 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. 
+W0702 16:31:57.490000 140386122716992 torch/distributed/run.py:757] *****************************************
+[default0]:07/02/2024 16:32:15 [WARNING|DP=0|PP=0|TP=0|ip-26-0-169-239]: [Vocab Size Padding] Padded vocab (size: 50257) with 15 dummy tokens (new size: 50272)
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: Config:
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: Config(general=GeneralArgs(project='bench_cluster',
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                            run='%date_%jobid',
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                            seed=42,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                            step=None,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                            consumed_train_samples=None,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                            benchmark_csv_path=None,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                            ignore_sanity_checks=True),
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:        parallelism=ParallelismArgs(dp=1,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                    pp=1,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                    tp=16,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                    pp_engine=<nanotron.parallel.pipeline_parallel.engine.OneForwardOneBackwardPipelineEngine object at 0x7f55d6098790>,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                    tp_mode=<TensorParallelLinearMode.REDUCE_SCATTER: 2>,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                    tp_linear_async_communication=False,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                    expert_parallel_size=1),
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:        model=ModelArgs(model_config=LlamaConfig(bos_token_id=1,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                 eos_token_id=2,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                 hidden_act='silu',
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                 hidden_size=2048,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                 initializer_range=0.02,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                 intermediate_size=4096,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                 is_llama_config=True,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                 max_position_embeddings=4096,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                 num_attention_heads=32,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                 num_hidden_layers=24,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                 num_key_value_heads=32,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                 pad_token_id=None,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                 pretraining_tp=1,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                 rms_norm_eps=1e-05,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                 rope_scaling=None,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                 rope_theta=10000.0,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                 tie_word_embeddings=True,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                 use_cache=True,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                 vocab_size=50272),
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                        init_method=RandomInit(std=0.025),
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                        dtype=torch.bfloat16,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                        make_vocab_size_divisible_by=1,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                        ddp_bucket_cap_mb=25),
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:        tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2',
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                tokenizer_revision=None,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                tokenizer_max_length=None),
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:        checkpoints=CheckpointsArgs(checkpoints_path=Path('/dev/null'),
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                    checkpoint_interval=100000,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                    save_initial_state=False,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                    resume_checkpoint_path=None,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                    checkpoints_path_is_shared_file_system=False),
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:        logging=LoggingArgs(log_level='info',
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                            log_level_replica='info',
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                            iteration_step_info_interval=1),
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:        tokens=TokensArgs(sequence_length=4096,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                          train_steps=20,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                          micro_batch_size=32,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                          batch_accumulation_per_replica=32,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                          val_check_interval=-1,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                          limit_val_batches=0,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                          limit_test_batches=0),
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:        optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                                     adam_beta1=0.9,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                                     adam_beta2=0.95,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                                     torch_adam_is_fused=True,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                                     name='adamW'),
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                zero_stage=1,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                weight_decay=0.01,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                clip_grad=1.0,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                accumulate_grad_in_fp32=True,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                                        lr_warmup_steps=1,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                                        lr_warmup_style='linear',
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                                        lr_decay_style='linear',
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                                        lr_decay_steps=19,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                                        lr_decay_starting_step=None,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                                        min_decay_lr=1e-05)),
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:        data_stages=[DatasetStageArgs(name='Training Stage',
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                      start_training_step=1,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                      data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories',
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                                                 hf_dataset_splits='train',
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                                                 hf_dataset_config_name=None,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                                                 dataset_processing_num_proc_per_process=64,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                                                 dataset_overwrite_cache=False,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                                                 text_column_name='text'),
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                    seed=42,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:                                                    num_loading_workers=32))],
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:        profiler=ProfilerArgs(profiler_export_path=Path('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-1_tp-16_pp-1_mbz-32')),
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:        lighteval=None)
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: Model Config:
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: LlamaConfig(bos_token_id=1,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:             eos_token_id=2,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:             hidden_act='silu',
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:             hidden_size=2048,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:             initializer_range=0.02,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:             intermediate_size=4096,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:             is_llama_config=True,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:             max_position_embeddings=4096,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:             num_attention_heads=32,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:             num_hidden_layers=24,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:             num_key_value_heads=32,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:             pad_token_id=None,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:             pretraining_tp=1,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:             rms_norm_eps=1e-05,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:             rope_scaling=None,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:             rope_theta=10000.0,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:             tie_word_embeddings=True,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:             use_cache=True,
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:             vocab_size=50272)
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: Building model..
+[default0]:07/02/2024 16:32:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: Setting PP block ranks...
+[default3]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=3|ip-26-0-169-239]: Local number of parameters: 69.4M (132.46MiB)
+[default3]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=3|ip-26-0-169-239]: [After model building] Memory usage: 159.71MiB. Peak allocated: 174.02MiB Peak reserved: 178.00MiB
+[default4]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=4|ip-26-0-169-239]: Local number of parameters: 69.4M (132.46MiB)
+[default4]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=4|ip-26-0-169-239]: [After model building] Memory usage: 159.71MiB. Peak allocated: 174.02MiB Peak reserved: 178.00MiB
+[default1]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=1|ip-26-0-169-239]: Local number of parameters: 69.4M (132.46MiB)
+[default4]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=4|ip-26-0-169-239]: No checkpoint path provided.
+[default3]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=3|ip-26-0-169-239]: No checkpoint path provided.
+[default1]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=1|ip-26-0-169-239]: [After model building] Memory usage: 159.71MiB. Peak allocated: 174.02MiB Peak reserved: 178.00MiB
+[default1]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=1|ip-26-0-169-239]: No checkpoint path provided.
+[default5]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=5|ip-26-0-169-239]: Local number of parameters: 69.4M (132.46MiB)
+[default5]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=5|ip-26-0-169-239]: [After model building] Memory usage: 159.71MiB. Peak allocated: 174.02MiB Peak reserved: 178.00MiB
+[default5]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=5|ip-26-0-169-239]: No checkpoint path provided.
+[default7]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=7|ip-26-0-169-239]: Local number of parameters: 69.4M (132.46MiB)
+[default7]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=7|ip-26-0-169-239]: [After model building] Memory usage: 159.71MiB. Peak allocated: 174.02MiB Peak reserved: 178.00MiB
+[default7]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=7|ip-26-0-169-239]: No checkpoint path provided.
+[default2]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=2|ip-26-0-169-239]: Local number of parameters: 69.4M (132.46MiB)
+[default2]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=2|ip-26-0-169-239]: [After model building] Memory usage: 159.71MiB. Peak allocated: 174.02MiB Peak reserved: 178.00MiB
+[default2]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=2|ip-26-0-169-239]: No checkpoint path provided.
+[default0]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: Total number of parameters: 1.11G (2119.44MiB)
+[default0]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: Local number of parameters: 69.4M (132.46MiB)
+[default0]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: [After model building] Memory usage: 159.71MiB. Peak allocated: 174.02MiB Peak reserved: 178.00MiB
+[default0]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: No checkpoint path provided.
+[default0]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: Parametrizing model parameters using StandardParametrizator
+[default0]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: [Optimizer Building] Using LearningRateForSP as learning rate
+[default0]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: [ZeRO sharding] Size of optimizer params per rank:
+[default0]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: [ZeRO sharding] DP Rank 0 has 69.4M out of 69.4M (100.00%) params' optimizer states
+[default6]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=6|ip-26-0-169-239]: Local number of parameters: 69.4M (132.46MiB)
+[default6]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=6|ip-26-0-169-239]: [After model building] Memory usage: 159.71MiB. Peak allocated: 174.02MiB Peak reserved: 178.00MiB
+[default6]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=6|ip-26-0-169-239]: No checkpoint path provided.
+[default3]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=11|ip-26-0-169-247]: Local number of parameters: 69.4M (132.46MiB)
+[default3]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=11|ip-26-0-169-247]: [After model building] Memory usage: 159.71MiB. Peak allocated: 174.02MiB Peak reserved: 178.00MiB
+[default3]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=11|ip-26-0-169-247]: No checkpoint path provided.
+[default1]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=9|ip-26-0-169-247]: Local number of parameters: 69.4M (132.46MiB)
+[default1]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=9|ip-26-0-169-247]: [After model building] Memory usage: 159.71MiB. Peak allocated: 174.02MiB Peak reserved: 178.00MiB
+[default1]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=9|ip-26-0-169-247]: No checkpoint path provided.
+[default5]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=13|ip-26-0-169-247]: Local number of parameters: 69.4M (132.46MiB)
+[default5]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=13|ip-26-0-169-247]: [After model building] Memory usage: 159.71MiB. Peak allocated: 174.02MiB Peak reserved: 178.00MiB
+[default2]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=10|ip-26-0-169-247]: Local number of parameters: 69.4M (132.46MiB)
+[default6]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=14|ip-26-0-169-247]: Local number of parameters: 69.4M (132.46MiB)
+[default6]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=14|ip-26-0-169-247]: [After model building] Memory usage: 159.71MiB. Peak allocated: 174.02MiB Peak reserved: 178.00MiB
+[default5]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=13|ip-26-0-169-247]: No checkpoint path provided.
+[default4]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=12|ip-26-0-169-247]: Local number of parameters: 69.4M (132.46MiB)
+[default4]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=12|ip-26-0-169-247]: [After model building] Memory usage: 159.71MiB. Peak allocated: 174.02MiB Peak reserved: 178.00MiB
+[default2]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=10|ip-26-0-169-247]: [After model building] Memory usage: 159.71MiB. Peak allocated: 174.02MiB Peak reserved: 178.00MiB
+[default2]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=10|ip-26-0-169-247]: No checkpoint path provided.
+[default6]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=14|ip-26-0-169-247]: No checkpoint path provided.
+[default4]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=12|ip-26-0-169-247]: No checkpoint path provided.
+[default0]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=8|ip-26-0-169-247]: Local number of parameters: 69.4M (132.46MiB)
+[default0]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=8|ip-26-0-169-247]: [After model building] Memory usage: 159.71MiB. Peak allocated: 174.02MiB Peak reserved: 178.00MiB
+[default0]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=8|ip-26-0-169-247]: No checkpoint path provided.
+[default7]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=15|ip-26-0-169-247]: Local number of parameters: 69.4M (132.46MiB)
+[default7]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=15|ip-26-0-169-247]: [After model building] Memory usage: 159.71MiB. Peak allocated: 174.02MiB Peak reserved: 178.00MiB
+[default7]:07/02/2024 16:32:32 [INFO|DP=0|PP=0|TP=15|ip-26-0-169-247]: No checkpoint path provided.
+[default0]:07/02/2024 16:32:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples
+[default0]:07/02/2024 16:32:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: Using `datasets` library
+[default0]:07/02/2024 16:32:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: Loading tokenizer from openai-community/gpt2 and transformers/hf_hub versions ('4.41.2', '0.23.4')
+[default0]:07/02/2024 16:32:33 [WARNING|DP=0|PP=0|TP=0|ip-26-0-169-239]: Repo card metadata block was not found. Setting CardData to empty.
+[default0]:Repo card metadata block was not found. Setting CardData to empty.
+[default0]:07/02/2024 16:32:34 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: [Training Plan] There are 1 training stages 
+[default0]:07/02/2024 16:32:34 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: [Stage Training Stage] start from step 1 
+[default0]:07/02/2024 16:32:34 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: 
+[default0]:07/02/2024 16:32:34 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: [Start training] datetime: 2024-07-02 16:32:34.409740 | mbs: 32 | grad_accum: 32 | global_batch_size: 1024 | sequence_length: 4096 | train_steps: 20 | start_iteration_step: 0 | consumed_train_samples: 0
+[default0]:07/02/2024 16:32:34 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps
+[default0]:07/02/2024 16:32:34 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-239]:  Memory usage: 689.57MiB. Peak allocated 689.57MiB. Peak reserved: 710.00MiB
+[default4]:07/02/2024 16:32:34 [WARNING|DP=0|PP=0|TP=4|ip-26-0-169-239]: Repo card metadata block was not found. Setting CardData to empty.
+[default2]:07/02/2024 16:32:34 [WARNING|DP=0|PP=0|TP=2|ip-26-0-169-239]: Repo card metadata block was not found. Setting CardData to empty.
+[default2]:Repo card metadata block was not found. Setting CardData to empty.
+[default0]:Repo card metadata block was not found. Setting CardData to empty.
+[default5]:07/02/2024 16:32:34 [WARNING|DP=0|PP=0|TP=13|ip-26-0-169-247]: Repo card metadata block was not found. Setting CardData to empty.
+[default2]:07/02/2024 16:32:34 [WARNING|DP=0|PP=0|TP=10|ip-26-0-169-247]: Repo card metadata block was not found. Setting CardData to empty.
+[default1]:07/02/2024 16:32:34 [WARNING|DP=0|PP=0|TP=9|ip-26-0-169-247]: Repo card metadata block was not found. Setting CardData to empty.
+[default4]:Repo card metadata block was not found. Setting CardData to empty.
+[default0]:07/02/2024 16:32:34 [WARNING|DP=0|PP=0|TP=8|ip-26-0-169-247]: Repo card metadata block was not found. Setting CardData to empty.
+[default3]:Repo card metadata block was not found. Setting CardData to empty.
+[default1]:Repo card metadata block was not found. Setting CardData to empty.
+[default5]:Repo card metadata block was not found. Setting CardData to empty.
+[default2]:Repo card metadata block was not found. Setting CardData to empty.
+[default3]:07/02/2024 16:32:34 [WARNING|DP=0|PP=0|TP=3|ip-26-0-169-239]: Repo card metadata block was not found. Setting CardData to empty.
+[default1]:07/02/2024 16:32:34 [WARNING|DP=0|PP=0|TP=1|ip-26-0-169-239]: Repo card metadata block was not found. Setting CardData to empty.
+[default5]:07/02/2024 16:32:34 [WARNING|DP=0|PP=0|TP=5|ip-26-0-169-239]: Repo card metadata block was not found. Setting CardData to empty.
+[default7]:07/02/2024 16:32:34 [WARNING|DP=0|PP=0|TP=7|ip-26-0-169-239]: Repo card metadata block was not found. Setting CardData to empty.
+[default3]:Repo card metadata block was not found. Setting CardData to empty.
+[default1]:Repo card metadata block was not found. Setting CardData to empty.
+[default6]:07/02/2024 16:32:34 [WARNING|DP=0|PP=0|TP=6|ip-26-0-169-239]: Repo card metadata block was not found. Setting CardData to empty.
+[default6]:Repo card metadata block was not found. Setting CardData to empty.
+[default3]:07/02/2024 16:32:34 [WARNING|DP=0|PP=0|TP=11|ip-26-0-169-247]: Repo card metadata block was not found. Setting CardData to empty.
+[default6]:07/02/2024 16:32:34 [WARNING|DP=0|PP=0|TP=14|ip-26-0-169-247]: Repo card metadata block was not found. Setting CardData to empty.
+[default4]:07/02/2024 16:32:34 [WARNING|DP=0|PP=0|TP=12|ip-26-0-169-247]: Repo card metadata block was not found. Setting CardData to empty.
+[default5]:Repo card metadata block was not found. Setting CardData to empty.
+[default7]:Repo card metadata block was not found. Setting CardData to empty.
+[default4]:Repo card metadata block was not found. Setting CardData to empty.
+[default7]:07/02/2024 16:32:34 [WARNING|DP=0|PP=0|TP=15|ip-26-0-169-247]: Repo card metadata block was not found. Setting CardData to empty.
+[default6]:Repo card metadata block was not found. Setting CardData to empty.
+[default7]:Repo card metadata block was not found. Setting CardData to empty.
+[default7]:[rank7]: OSError: [Errno 122] Disk quota exceeded
+[default7]:
+[default7]:[rank7]: During handling of the above exception, another exception occurred:
+[default7]:
+[default7]:[rank7]: Traceback (most recent call last):
+[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
+[default7]:[rank7]:     trainer.train(dataloader)
+[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
+[default7]:[rank7]:     outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
+[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
+[default7]:[rank7]:     outputs = self.pipeline_engine.train_batch_iter(
+[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
+[default7]:[rank7]:     output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
+[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
+[default7]:[rank7]:     output = model(**micro_batch)
+[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
+[default7]:[rank7]:     return self._call_impl(*args, **kwargs)
+[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
+[default7]:[rank7]:     return forward_call(*args, **kwargs)
+[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
+[default7]:[rank7]:     sharded_logits = self.model(
+[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
+[default7]:[rank7]:     return self._call_impl(*args, **kwargs)
+[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
+[default7]:[rank7]:     return forward_call(*args, **kwargs)
+[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
+[default7]:[rank7]:     return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
+[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
+[default7]:[rank7]:     hidden_encoder_states = encoder_block(**hidden_encoder_states)
+[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
+[default7]:[rank7]:     return self._call_impl(*args, **kwargs)
+[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
+[default7]:[rank7]:     return forward_call(*args, **kwargs)
+[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
+[default7]:[rank7]:     output = self.pp_block(**new_kwargs)
+[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
+[default7]:[rank7]:     return self._call_impl(*args, **kwargs)
+[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
+[default7]:[rank7]:     return forward_call(*args, **kwargs)
+[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 629, in forward
+[default7]:[rank7]:     hidden_states = self.input_layernorm(hidden_states)
+[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
+[default7]:[rank7]:     return self._call_impl(*args, **kwargs)
+[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
+[default7]:[rank7]:     return forward_call(*args, **kwargs)
+[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/nn/layer_norm.py", line 42, in forward
+[default7]:[rank7]:     return layer_norm_fn(
+[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/flash_attn/ops/triton/layer_norm.py", line 875, in layer_norm_fn
+[default7]:[rank7]:     return LayerNormFn.apply(
+[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/function.py", line 598, in apply
+[default7]:[rank7]:     return super().apply(*args, **kwargs)  # type: ignore[misc]
+[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/flash_attn/ops/triton/layer_norm.py", line 748, in forward
+[default7]:[rank7]:     y, y1, mean, rstd, residual_out, seeds, dropout_mask, dropout_mask1 = _layer_norm_fwd(
+[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/flash_attn/ops/triton/layer_norm.py", line 335, in _layer_norm_fwd
+[default7]:[rank7]:     _layer_norm_fwd_1pass_kernel[(M,)](
+[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/jit.py", line 167, in <lambda>
+[default7]:[rank7]:     return lambda *args, **kwargs: self.run(grid=grid, warmup=False, *args, **kwargs)
+[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 143, in run
+[default7]:[rank7]:     timings = {config: self._bench(*args, config=config, **kwargs) for config in pruned_configs}
+[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 143, in <dictcomp>
+[default7]:[rank7]:     timings = {config: self._bench(*args, config=config, **kwargs) for config in pruned_configs}
+[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 122, in _bench
+[default7]:[rank7]:     return do_bench(kernel_call, warmup=self.warmup, rep=self.rep, quantiles=(0.5, 0.2, 0.8))
+[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/testing.py", line 102, in do_bench
+[default7]:[rank7]:     fn()
+[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 110, in kernel_call
+[default7]:[rank7]:     self.fn.run(
+[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 305, in run
+[default7]:[rank7]:     return self.fn.run(*args, **kwargs)
+[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 305, in run
+[default7]:[rank7]:     return self.fn.run(*args, **kwargs)
+[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 305, in run
+[default7]:[rank7]:     return self.fn.run(*args, **kwargs)
+[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/jit.py", line 416, in run
+[default7]:[rank7]:     self.cache[device][key] = compile(
+[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/compiler/compiler.py", line 194, in compile
+[default7]:[rank7]:     metadata_group[f"{src.name}.{ext}"] = fn_cache_manager.put(next_module, f"{src.name}.{ext}")
+[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/cache.py", line 123, in put
+[default7]:[rank7]:     with open(temp_path, mode) as f:
+[default7]:[rank7]: OSError: [Errno 122] Disk quota exceeded
+[default4]:[rank4]: OSError: [Errno 122] Disk quota exceeded
+[default4]:
+[default4]:[rank4]: During handling of the above exception, another exception occurred:
+[default4]:
+[default4]:[rank4]: Traceback (most recent call last):
+[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
+[default4]:[rank4]:     trainer.train(dataloader)
+[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
+[default4]:[rank4]:     outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
+[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
+[default4]:[rank4]:     outputs = self.pipeline_engine.train_batch_iter(
+[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
+[default4]:[rank4]:     output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
+[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
+[default4]:[rank4]:     output = model(**micro_batch)
+[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
+[default4]:[rank4]:     return self._call_impl(*args, **kwargs)
+[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
+[default4]:[rank4]:     return forward_call(*args, **kwargs)
+[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
+[default4]:[rank4]:     sharded_logits = self.model(
+[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
+[default4]:[rank4]:     return self._call_impl(*args, **kwargs)
+[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
+[default4]:[rank4]:     return forward_call(*args, **kwargs)
+[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
+[default4]:[rank4]:     return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
+[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
+[default4]:[rank4]:     hidden_encoder_states = encoder_block(**hidden_encoder_states)
+[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
+[default4]:[rank4]:     return self._call_impl(*args, **kwargs)
+[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
+[default4]:[rank4]:     return forward_call(*args, **kwargs)
+[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
+[default4]:[rank4]:     output = self.pp_block(**new_kwargs)
+[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
+[default4]:[rank4]:     return self._call_impl(*args, **kwargs)
+[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
+[default4]:[rank4]:     return forward_call(*args, **kwargs)
+[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 629, in forward
+[default4]:[rank4]:     hidden_states = self.input_layernorm(hidden_states)
+[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
+[default4]:[rank4]:     return self._call_impl(*args, **kwargs)
+[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
+[default4]:[rank4]:     return forward_call(*args, **kwargs)
+[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/nn/layer_norm.py", line 42, in forward
+[default4]:[rank4]:     return layer_norm_fn(
+[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/flash_attn/ops/triton/layer_norm.py", line 875, in layer_norm_fn
+[default4]:[rank4]:     return LayerNormFn.apply(
+[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/function.py", line 598, in apply
+[default4]:[rank4]:     return super().apply(*args, **kwargs)  # type: ignore[misc]
+[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/flash_attn/ops/triton/layer_norm.py", line 748, in forward
+[default4]:[rank4]:     y, y1, mean, rstd, residual_out, seeds, dropout_mask, dropout_mask1 = _layer_norm_fwd(
+[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/flash_attn/ops/triton/layer_norm.py", line 335, in _layer_norm_fwd
+[default4]:[rank4]:     _layer_norm_fwd_1pass_kernel[(M,)](
+[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/jit.py", line 167, in <lambda>
+[default4]:[rank4]:     return lambda *args, **kwargs: self.run(grid=grid, warmup=False, *args, **kwargs)
+[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 143, in run
+[default4]:[rank4]:     timings = {config: self._bench(*args, config=config, **kwargs) for config in pruned_configs}
+[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 143, in <dictcomp>
+[default4]:[rank4]:     timings = {config: self._bench(*args, config=config, **kwargs) for config in pruned_configs}
+[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 122, in _bench
+[default4]:[rank4]:     return do_bench(kernel_call, warmup=self.warmup, rep=self.rep, quantiles=(0.5, 0.2, 0.8))
+[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/testing.py", line 102, in do_bench
+[default4]:[rank4]:     fn()
+[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 110, in kernel_call
+[default4]:[rank4]:     self.fn.run(
+[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 305, in run
+[default4]:[rank4]:     return self.fn.run(*args, **kwargs)
+[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 305, in run
+[default4]:[rank4]:     return self.fn.run(*args, **kwargs)
+[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 305, in run
+[default4]:[rank4]:     return self.fn.run(*args, **kwargs)
+[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/jit.py", line 416, in run
+[default4]:[rank4]:     self.cache[device][key] = compile(
+[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/compiler/compiler.py", line 194, in compile
+[default4]:[rank4]:     metadata_group[f"{src.name}.{ext}"] = fn_cache_manager.put(next_module, f"{src.name}.{ext}")
+[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/cache.py", line 123, in put
+[default4]:[rank4]:     with open(temp_path, mode) as f:
+[default4]:[rank4]: OSError: [Errno 122] Disk quota exceeded
+[default4]:[rank12]: OSError: [Errno 122] Disk quota exceeded
+[default4]:
+[default4]:[rank12]: During handling of the above exception, another exception occurred:
+[default4]:
+[default4]:[rank12]: Traceback (most recent call last):
+[default4]:[rank12]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
+[default4]:[rank12]:     trainer.train(dataloader)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
+[default4]:[rank12]:     outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
+[default4]:[rank12]:     outputs = self.pipeline_engine.train_batch_iter(
+[default4]:[rank12]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
+[default4]:[rank12]:     output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
+[default4]:[rank12]:     output = model(**micro_batch)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
+[default4]:[rank12]:     return self._call_impl(*args, **kwargs)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
+[default4]:[rank12]:     return forward_call(*args, **kwargs)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
+[default4]:[rank12]:     sharded_logits = self.model(
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
+[default4]:[rank12]:     return self._call_impl(*args, **kwargs)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
+[default4]:[rank12]:     return forward_call(*args, **kwargs)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
+[default4]:[rank12]:     return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
+[default4]:[rank12]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
+[default4]:[rank12]:     hidden_encoder_states = encoder_block(**hidden_encoder_states)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
+[default4]:[rank12]:     return self._call_impl(*args, **kwargs)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
+[default4]:[rank12]:     return forward_call(*args, **kwargs)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
+[default4]:[rank12]:     output = self.pp_block(**new_kwargs)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
+[default4]:[rank12]:     return self._call_impl(*args, **kwargs)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
+[default4]:[rank12]:     return forward_call(*args, **kwargs)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 629, in forward
+[default4]:[rank12]:     hidden_states = self.input_layernorm(hidden_states)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
+[default4]:[rank12]:     return self._call_impl(*args, **kwargs)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
+[default4]:[rank12]:     return forward_call(*args, **kwargs)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/nn/layer_norm.py", line 42, in forward
+[default4]:[rank12]:     return layer_norm_fn(
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/flash_attn/ops/triton/layer_norm.py", line 875, in layer_norm_fn
+[default4]:[rank12]:     return LayerNormFn.apply(
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/function.py", line 598, in apply
+[default4]:[rank12]:     return super().apply(*args, **kwargs)  # type: ignore[misc]
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/flash_attn/ops/triton/layer_norm.py", line 748, in forward
+[default4]:[rank12]:     y, y1, mean, rstd, residual_out, seeds, dropout_mask, dropout_mask1 = _layer_norm_fwd(
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/flash_attn/ops/triton/layer_norm.py", line 335, in _layer_norm_fwd
+[default4]:[rank12]:     _layer_norm_fwd_1pass_kernel[(M,)](
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/jit.py", line 167, in <lambda>
+[default4]:[rank12]:     return lambda *args, **kwargs: self.run(grid=grid, warmup=False, *args, **kwargs)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 143, in run
+[default4]:[rank12]:     timings = {config: self._bench(*args, config=config, **kwargs) for config in pruned_configs}
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 143, in <dictcomp>
+[default4]:[rank12]:     timings = {config: self._bench(*args, config=config, **kwargs) for config in pruned_configs}
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 122, in _bench
+[default4]:[rank12]:     return do_bench(kernel_call, warmup=self.warmup, rep=self.rep, quantiles=(0.5, 0.2, 0.8))
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/testing.py", line 102, in do_bench
+[default4]:[rank12]:     fn()
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 110, in kernel_call
+[default4]:[rank12]:     self.fn.run(
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 305, in run
+[default4]:[rank12]:     return self.fn.run(*args, **kwargs)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 305, in run
+[default4]:[rank12]:     return self.fn.run(*args, **kwargs)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/autotuner.py", line 305, in run
+[default4]:[rank12]:     return self.fn.run(*args, **kwargs)
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/jit.py", line 416, in run
+[default4]:[rank12]:     self.cache[device][key] = compile(
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/compiler/compiler.py", line 194, in compile
+[default4]:[rank12]:     metadata_group[f"{src.name}.{ext}"] = fn_cache_manager.put(next_module, f"{src.name}.{ext}")
+[default4]:[rank12]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/triton/runtime/cache.py", line 123, in put
+[default4]:[rank12]:     with open(temp_path, mode) as f:
+[default4]:[rank12]: OSError: [Errno 122] Disk quota exceeded
+W0702 16:32:48.847000 140386122716992 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2427255 closing signal SIGTERM
+W0702 16:32:48.852000 140386122716992 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2427256 closing signal SIGTERM
+W0702 16:32:48.854000 140386122716992 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2427257 closing signal SIGTERM
+W0702 16:32:48.862000 139796830594880 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 99623 closing signal SIGTERM
+W0702 16:32:48.863000 140386122716992 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2427258 closing signal SIGTERM
+W0702 16:32:48.866000 139796830594880 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 99624 closing signal SIGTERM
+W0702 16:32:48.871000 139796830594880 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 99625 closing signal SIGTERM
+W0702 16:32:48.875000 139796830594880 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 99626 closing signal SIGTERM
+W0702 16:32:48.878000 139796830594880 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 99628 closing signal SIGTERM
+W0702 16:32:48.880000 139796830594880 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 99629 closing signal SIGTERM
+W0702 16:32:48.882000 139796830594880 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 99630 closing signal SIGTERM
+W0702 16:32:48.891000 140386122716992 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2427260 closing signal SIGTERM
+W0702 16:32:48.894000 140386122716992 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2427261 closing signal SIGTERM
+E0702 16:32:51.295000 140386122716992 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: 1) local_rank: 4 (pid: 2427259) of binary: /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10
+Traceback (most recent call last):
+  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in <module>
+    sys.exit(main())
+  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper
+    return f(*args, **kwargs)
+  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 879, in main
+    run(args)
+  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 870, in run
+    elastic_launch(
+  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 132, in __call__
+    return launch_agent(self._config, self._entrypoint, list(args))
+  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 263, in launch_agent
+    raise ChildFailedError(
+torch.distributed.elastic.multiprocessing.errors.ChildFailedError: 
+============================================================
+/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py FAILED
+------------------------------------------------------------
+Failures:
+[1]:
+  time      : 2024-07-02_16:32:48
+  host      : ip-26-0-169-239.ec2.internal
+  rank      : 7 (local_rank: 7)
+  exitcode  : 1 (pid: 2427262)
+  error_file: <N/A>
+  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
+------------------------------------------------------------
+Root Cause (first observed failure):
+[0]:
+  time      : 2024-07-02_16:32:48
+  host      : ip-26-0-169-239.ec2.internal
+  rank      : 4 (local_rank: 4)
+  exitcode  : 1 (pid: 2427259)
+  error_file: <N/A>
+  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
+============================================================
+E0702 16:32:51.480000 139796830594880 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: 1) local_rank: 4 (pid: 99627) of binary: /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10
+W0702 16:32:51.487000 139796830594880 torch/distributed/elastic/rendezvous/dynamic_rendezvous.py:1203] The node 'ip-26-0-169-247.ec2.internal_99554_0' has failed to shutdown the rendezvous 'none' due to an error of type RendezvousConnectionError.
+W0702 16:32:51.515000 139796830594880 torch/distributed/elastic/rendezvous/dynamic_rendezvous.py:1203] The node 'ip-26-0-169-247.ec2.internal_99554_0' has failed to shutdown the rendezvous 'none' due to an error of type RendezvousConnectionError.
+W0702 16:32:51.525000 139796830594880 torch/distributed/elastic/rendezvous/dynamic_rendezvous.py:1203] The node 'ip-26-0-169-247.ec2.internal_99554_0' has failed to shutdown the rendezvous 'none' due to an error of type RendezvousConnectionError.
+Traceback (most recent call last):
+  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in <module>
+    sys.exit(main())
+  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper
+    return f(*args, **kwargs)
+  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 879, in main
+    run(args)
+  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 870, in run
+    elastic_launch(
+  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 132, in __call__
+    return launch_agent(self._config, self._entrypoint, list(args))
+  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 263, in launch_agent
+    raise ChildFailedError(
+torch.distributed.elastic.multiprocessing.errors.ChildFailedError: 
+============================================================
+/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py FAILED
+------------------------------------------------------------
+Failures:
+  <NO_OTHER_FAILURES>
+------------------------------------------------------------
+Root Cause (first observed failure):
+[0]:
+  time      : 2024-07-02_16:32:48
+  host      : ip-26-0-169-247.ec2.internal
+  rank      : 12 (local_rank: 4)
+  exitcode  : 1 (pid: 99627)
+  error_file: <N/A>
+  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
+============================================================
+srun: error: ip-26-0-169-239: task 0: Exited with exit code 1
+srun: error: ip-26-0-169-247: task 1: Exited with exit code 1
+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/16_GPUS/dp-1_tp-16_pp-1_mbz-32/status.txt

@@ -0,0 +1 @@
+fail