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Upload llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8

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  1. llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8/bench.slurm +111 -0
  2. llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8/config.yaml +90 -0
  3. llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8/log.out +325 -0
  4. llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8/status.txt +1 -0
llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8/bench.slurm ADDED
@@ -0,0 +1,111 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ #!/bin/bash
2
+
3
+ #SBATCH --job-name=bench_cluster
4
+ #SBATCH --time=02:00:00
5
+ #SBATCH --partition=hopper-prod
6
+ #SBATCH --nodes=1
7
+ #SBATCH --gres=gpu:8
8
+ #SBATCH --qos=normal
9
+ #SBATCH --ntasks-per-node=1
10
+ #SBATCH --cpus-per-task=96
11
+ #SBATCH --exclusive
12
+ #SBATCH --output=/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8/log.out
13
+ #SBATCH --error=/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8/log.out
14
+
15
+ # Function to update status based on squeue output
16
+ update_status() {
17
+ job_id=$1
18
+ status_file=$2
19
+ # For unknown reasons, it doenst update status for pending. It only works for running
20
+ while true; do
21
+ job_status=$(squeue --job $job_id --noheader --format=%T)
22
+ echo "Job status: $job_status"
23
+ if [ -z "$job_status" ]; then
24
+ # Job has finished or is not found
25
+ break
26
+ elif [ "$job_status" = "RUNNING" ]; then
27
+ printf "running" > $status_file
28
+ break
29
+ fi
30
+ sleep 10
31
+ done
32
+ }
33
+
34
+ # Misc initializations.
35
+ echo "========================"
36
+ echo "START TIME: $(date)"
37
+ source /fsx/ferdinandmom/miniforge3/etc/profile.d/conda.sh
38
+ conda activate /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster
39
+ echo python3 version = $(python3 --version)
40
+ echo "========================"
41
+
42
+ # Slurm stuff
43
+ export HOSTNAMES=$(scontrol show hostnames "$SLURM_JOB_NODELIST")
44
+ export MASTER_ADDR=$(scontrol show hostnames "$SLURM_JOB_NODELIST" | head -n 1)
45
+ export MASTER_PORT=$((1024 + RANDOM % 64511))
46
+
47
+ export TMPDIR=/scratch
48
+ export HF_DATASETS_CACHE="/admin/home/ferdinand_mom/.cache"
49
+ export CUBLAS_WORKSPACE_CONFIG=":4096:8"
50
+ export CUDA_DEVICE_MAX_CONNECTIONS="1"
51
+
52
+ huggingface-cli login --token $HUGGINGFACE_TOKEN
53
+
54
+
55
+ NANOTRON_REPO="/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron"
56
+ CMD="$NANOTRON_REPO/run_train.py --config-file /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8/config.yaml"
57
+
58
+ LAUNCHER="torchrun \
59
+ --nproc_per_node 8 \
60
+ --nnodes 1 \
61
+ --rdzv_endpoint ${MASTER_ADDR}:${MASTER_PORT} \
62
+ --rdzv_backend c10d \
63
+ --max_restarts 0 \
64
+ --tee 3 \
65
+ --node_rank ${SLURM_PROCID}"
66
+
67
+ # Checkout the bench_cluster branch
68
+ cd $NANOTRON_REPO
69
+ git checkout bench_cluster
70
+ cd ..
71
+ # Get the current job ID
72
+ job_id=${SLURM_JOB_ID}
73
+
74
+ # Update status to "pending" or "running" in the background
75
+ update_status $job_id /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8/status.txt &
76
+
77
+ # Run the main command
78
+ srun -u $LAUNCHER $CMD
79
+ exit_status=$?
80
+
81
+ # Update status based on the exit status of `srun`
82
+ if [ $exit_status -eq 0 ]; then
83
+ printf "completed" > /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8/status.txt
84
+ else
85
+ if grep -q "OutOfMemoryError" /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8/log.out; then
86
+ printf "oom" > /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8/status.txt
87
+ elif grep -q " CUDA error: an illegal memory access" /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8/log.out; then
88
+ printf "oom" > /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8/status.txt
89
+ elif grep -q "Timeout at NCCL" /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8/log.out; then
90
+ printf "timeout" > /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8/status.txt
91
+ else
92
+ printf "fail" > /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8/status.txt
93
+ fi
94
+ fi
95
+
96
+ # Run the report script if the job completed successfully
97
+ if [ $exit_status -eq 0 ]; then
98
+ python /fsx/ferdinandmom/ferdinand-hf/bench_cluster/main.py report --inp_dir /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8 --is_logs
99
+ python /fsx/ferdinandmom/ferdinand-hf/bench_cluster/main.py report --inp_dir /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8 --is_profiler
100
+ fi
101
+
102
+
103
+ # Push to hub the folder using huggingface_cli
104
+ huggingface-cli upload nanotron/bench_cluster /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8 llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8 --commit-message "Upload llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8"
105
+
106
+ # Verify the upload
107
+ if [ $? -eq 0 ]; then
108
+ echo "Uploading to Huggingface Hub successful"
109
+ else
110
+ echo "Failed to upload to Huggingface Hub"
111
+ fi
llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8/config.yaml ADDED
@@ -0,0 +1,90 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ general:
2
+ project: bench_cluster
3
+ seed: 42
4
+ model:
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
+ 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: 8
49
+ expert_parallel_size: 1
50
+ pp: 1
51
+ pp_engine: 1f1b
52
+ tp: 1
53
+ tp_linear_async_communication: false
54
+ tp_mode: REDUCE_SCATTER
55
+ profiler:
56
+ profiler_export_path: /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8
57
+ tokenizer:
58
+ tokenizer_max_length: null
59
+ tokenizer_name_or_path: openai-community/gpt2
60
+ tokenizer_revision: null
61
+ data_stages:
62
+ - name: Training Stage
63
+ start_training_step: 1
64
+ 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: 8
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
llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8/log.out ADDED
@@ -0,0 +1,325 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ========================
2
+ START TIME: Thu Jul 4 00:00:38 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
+ W0704 00:00:41.637000 140486515681088 torch/distributed/run.py:757]
18
+ W0704 00:00:41.637000 140486515681088 torch/distributed/run.py:757] *****************************************
19
+ W0704 00:00:41.637000 140486515681088 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
+ W0704 00:00:41.637000 140486515681088 torch/distributed/run.py:757] *****************************************
21
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: Config:
22
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: Config(general=GeneralArgs(project='bench_cluster',
23
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: run='%date_%jobid',
24
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: seed=42,
25
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: step=None,
26
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: consumed_train_samples=None,
27
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: benchmark_csv_path=None,
28
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: ignore_sanity_checks=True),
29
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: parallelism=ParallelismArgs(dp=8,
30
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: pp=1,
31
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: tp=1,
32
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: pp_engine=<nanotron.parallel.pipeline_parallel.engine.OneForwardOneBackwardPipelineEngine object at 0x7fd4453b0820>,
33
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: tp_mode=<TensorParallelLinearMode.REDUCE_SCATTER: 2>,
34
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: tp_linear_async_communication=False,
35
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: expert_parallel_size=1),
36
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: model=ModelArgs(model_config=LlamaConfig(bos_token_id=1,
37
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: eos_token_id=2,
38
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: hidden_act='silu',
39
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: hidden_size=2048,
40
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: initializer_range=0.02,
41
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: intermediate_size=4096,
42
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: is_llama_config=True,
43
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: max_position_embeddings=4096,
44
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: num_attention_heads=32,
45
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: num_hidden_layers=24,
46
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: num_key_value_heads=32,
47
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: pad_token_id=None,
48
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: pretraining_tp=1,
49
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: rms_norm_eps=1e-05,
50
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: rope_scaling=None,
51
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: rope_theta=10000.0,
52
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: tie_word_embeddings=True,
53
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: use_cache=True,
54
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: vocab_size=50257),
55
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: init_method=RandomInit(std=0.025),
56
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: dtype=torch.bfloat16,
57
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: make_vocab_size_divisible_by=1,
58
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: ddp_bucket_cap_mb=25),
59
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2',
60
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: tokenizer_revision=None,
61
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: tokenizer_max_length=None),
62
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: checkpoints=CheckpointsArgs(checkpoints_path=Path('/dev/null'),
63
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: checkpoint_interval=100000,
64
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: save_initial_state=False,
65
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: resume_checkpoint_path=None,
66
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: checkpoints_path_is_shared_file_system=False),
67
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: logging=LoggingArgs(log_level='info',
68
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: log_level_replica='info',
69
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: iteration_step_info_interval=1),
70
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: tokens=TokensArgs(sequence_length=4096,
71
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: train_steps=20,
72
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: micro_batch_size=8,
73
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: batch_accumulation_per_replica=16,
74
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: val_check_interval=-1,
75
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: limit_val_batches=0,
76
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: limit_test_batches=0),
77
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08,
78
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: adam_beta1=0.9,
79
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: adam_beta2=0.95,
80
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: torch_adam_is_fused=True,
81
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: name='adamW'),
82
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: zero_stage=1,
83
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: weight_decay=0.01,
84
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: clip_grad=1.0,
85
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: accumulate_grad_in_fp32=True,
86
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001,
87
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: lr_warmup_steps=1,
88
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: lr_warmup_style='linear',
89
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: lr_decay_style='linear',
90
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: lr_decay_steps=19,
91
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: lr_decay_starting_step=None,
92
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: min_decay_lr=1e-05)),
93
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: data_stages=[DatasetStageArgs(name='Training Stage',
94
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: start_training_step=1,
95
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories',
96
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: hf_dataset_splits='train',
97
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: hf_dataset_config_name=None,
98
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: dataset_processing_num_proc_per_process=64,
99
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: dataset_overwrite_cache=False,
100
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: text_column_name='text'),
101
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: seed=42,
102
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: num_loading_workers=0))],
103
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: profiler=ProfilerArgs(profiler_export_path=Path('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-8_tp-1_pp-1_mbz-8')),
104
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: lighteval=None)
105
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: Model Config:
106
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: LlamaConfig(bos_token_id=1,
107
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: eos_token_id=2,
108
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: hidden_act='silu',
109
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: hidden_size=2048,
110
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: initializer_range=0.02,
111
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: intermediate_size=4096,
112
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: is_llama_config=True,
113
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: max_position_embeddings=4096,
114
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: num_attention_heads=32,
115
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: num_hidden_layers=24,
116
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: num_key_value_heads=32,
117
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: pad_token_id=None,
118
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: pretraining_tp=1,
119
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: rms_norm_eps=1e-05,
120
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: rope_scaling=None,
121
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: rope_theta=10000.0,
122
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: tie_word_embeddings=True,
123
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: use_cache=True,
124
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: vocab_size=50257)
125
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: Building model..
126
+ [default0]:07/04/2024 00:01:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: Setting PP block ranks...
127
+ [default6]:07/04/2024 00:01:10 [INFO|DP=6|PP=0|TP=0|ip-26-0-169-139]: No checkpoint path provided.
128
+ [default0]:07/04/2024 00:01:10 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: Total number of parameters: 1.11G (2116.51MiB)
129
+ [default0]:07/04/2024 00:01:10 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: Local number of parameters: 1.11G (2116.51MiB)
130
+ [default0]:07/04/2024 00:01:10 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: [After model building] Memory usage: 2140.53MiB. Peak allocated: 2338.88MiB Peak reserved: 2392.00MiB
131
+ [default0]:07/04/2024 00:01:10 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: No checkpoint path provided.
132
+ [default0]:07/04/2024 00:01:10 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: Parametrizing model parameters using StandardParametrizator
133
+ [default4]:07/04/2024 00:01:10 [INFO|DP=4|PP=0|TP=0|ip-26-0-169-139]: No checkpoint path provided.
134
+ [default3]:07/04/2024 00:01:10 [INFO|DP=3|PP=0|TP=0|ip-26-0-169-139]: No checkpoint path provided.
135
+ [default5]:07/04/2024 00:01:10 [INFO|DP=5|PP=0|TP=0|ip-26-0-169-139]: No checkpoint path provided.
136
+ [default2]:07/04/2024 00:01:10 [INFO|DP=2|PP=0|TP=0|ip-26-0-169-139]: No checkpoint path provided.
137
+ [default7]:07/04/2024 00:01:10 [INFO|DP=7|PP=0|TP=0|ip-26-0-169-139]: No checkpoint path provided.
138
+ [default1]:07/04/2024 00:01:10 [INFO|DP=1|PP=0|TP=0|ip-26-0-169-139]: No checkpoint path provided.
139
+ [default0]:07/04/2024 00:01:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: [Optimizer Building] Using LearningRateForSP as learning rate
140
+ [default0]:07/04/2024 00:01:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: [ZeRO sharding] Size of optimizer params per rank:
141
+ [default0]:07/04/2024 00:01:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: [ZeRO sharding] DP Rank 0 has 139M out of 1.11G (12.50%) params' optimizer states
142
+ [default0]:07/04/2024 00:01:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: [ZeRO sharding] DP Rank 1 has 139M out of 1.11G (12.50%) params' optimizer states
143
+ [default0]:07/04/2024 00:01:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: [ZeRO sharding] DP Rank 2 has 139M out of 1.11G (12.50%) params' optimizer states
144
+ [default0]:07/04/2024 00:01:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: [ZeRO sharding] DP Rank 3 has 139M out of 1.11G (12.50%) params' optimizer states
145
+ [default0]:07/04/2024 00:01:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: [ZeRO sharding] DP Rank 4 has 139M out of 1.11G (12.50%) params' optimizer states
146
+ [default0]:07/04/2024 00:01:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: [ZeRO sharding] DP Rank 5 has 139M out of 1.11G (12.50%) params' optimizer states
147
+ [default0]:07/04/2024 00:01:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: [ZeRO sharding] DP Rank 6 has 139M out of 1.11G (12.50%) params' optimizer states
148
+ [default0]:07/04/2024 00:01:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: [ZeRO sharding] DP Rank 7 has 139M out of 1.11G (12.50%) params' optimizer states
149
+ [default0]:07/04/2024 00:01:19 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples
150
+ [default0]:07/04/2024 00:01:19 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: Using `datasets` library
151
+ [default0]:07/04/2024 00:01:19 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: Loading tokenizer from openai-community/gpt2 and transformers/hf_hub versions ('4.41.2', '0.23.4')
152
+ [default0]:07/04/2024 00:01:19 [WARNING|DP=0|PP=0|TP=0|ip-26-0-169-139]: Repo card metadata block was not found. Setting CardData to empty.
153
+ [default0]:Repo card metadata block was not found. Setting CardData to empty.
154
+ [default0]:07/04/2024 00:01:20 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: [Training Plan] There are 1 training stages
155
+ [default0]:07/04/2024 00:01:20 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: [Stage Training Stage] start from step 1
156
+ [default0]:07/04/2024 00:01:20 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]:
157
+ [default0]:07/04/2024 00:01:20 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: [Start training] datetime: 2024-07-04 00:01:20.559063 | mbs: 8 | grad_accum: 16 | global_batch_size: 1024 | sequence_length: 4096 | train_steps: 20 | start_iteration_step: 0 | consumed_train_samples: 0
158
+ [default0]:07/04/2024 00:01:20 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps
159
+ [default0]:07/04/2024 00:01:20 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-139]: Memory usage: 6904.53MiB. Peak allocated 6904.53MiB. Peak reserved: 7156.00MiB
160
+ [default6]:07/04/2024 00:01:20 [WARNING|DP=6|PP=0|TP=0|ip-26-0-169-139]: Repo card metadata block was not found. Setting CardData to empty.
161
+ [default3]:Repo card metadata block was not found. Setting CardData to empty.
162
+ [default3]:07/04/2024 00:01:20 [WARNING|DP=3|PP=0|TP=0|ip-26-0-169-139]: Repo card metadata block was not found. Setting CardData to empty.
163
+ [default7]:07/04/2024 00:01:20 [WARNING|DP=7|PP=0|TP=0|ip-26-0-169-139]: Repo card metadata block was not found. Setting CardData to empty.
164
+ [default5]:07/04/2024 00:01:20 [WARNING|DP=5|PP=0|TP=0|ip-26-0-169-139]: Repo card metadata block was not found. Setting CardData to empty.
165
+ [default2]:07/04/2024 00:01:20 [WARNING|DP=2|PP=0|TP=0|ip-26-0-169-139]: Repo card metadata block was not found. Setting CardData to empty.
166
+ [default2]:Repo card metadata block was not found. Setting CardData to empty.
167
+ [default5]:Repo card metadata block was not found. Setting CardData to empty.
168
+ [default1]:07/04/2024 00:01:20 [WARNING|DP=1|PP=0|TP=0|ip-26-0-169-139]: Repo card metadata block was not found. Setting CardData to empty.
169
+ [default1]:Repo card metadata block was not found. Setting CardData to empty.
170
+ [default7]:Repo card metadata block was not found. Setting CardData to empty.
171
+ [default6]:Repo card metadata block was not found. Setting CardData to empty.
172
+ [default4]:07/04/2024 00:01:20 [WARNING|DP=4|PP=0|TP=0|ip-26-0-169-139]: Repo card metadata block was not found. Setting CardData to empty.
173
+ [default4]:Repo card metadata block was not found. Setting CardData to empty.
174
+ [default0]:[rank0]: Traceback (most recent call last):
175
+ [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
176
+ [default0]:[rank0]: trainer.train(dataloader)
177
+ [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
178
+ [default0]:[rank0]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
179
+ [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
180
+ [default0]:[rank0]: outputs = self.pipeline_engine.train_batch_iter(
181
+ [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
182
+ [default0]:[rank0]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
183
+ [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
184
+ [default0]:[rank0]: output = model(**micro_batch)
185
+ [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
186
+ [default0]:[rank0]: return self._call_impl(*args, **kwargs)
187
+ [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
188
+ [default0]:[rank0]: return forward_call(*args, **kwargs)
189
+ [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
190
+ [default0]:[rank0]: sharded_logits = self.model(
191
+ [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
192
+ [default0]:[rank0]: return self._call_impl(*args, **kwargs)
193
+ [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
194
+ [default0]:[rank0]: return forward_call(*args, **kwargs)
195
+ [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
196
+ [default0]:[rank0]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
197
+ [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 786, in forward_with_hidden_states
198
+ [default0]:[rank0]: fp32_sharded_logits = self.cast_to_fp32(x=sharded_logits)["output"]
199
+ [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
200
+ [default0]:[rank0]: return self._call_impl(*args, **kwargs)
201
+ [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
202
+ [default0]:[rank0]: return forward_call(*args, **kwargs)
203
+ [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
204
+ [default0]:[rank0]: output = self.pp_block(**new_kwargs)
205
+ [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 753, in <lambda>
206
+ [default0]:[rank0]: module_builder=lambda: lambda x: x.float(),
207
+ [default0]:[rank0]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 6.14 GiB. GPU
208
+ [default2]:[rank2]: Traceback (most recent call last):
209
+ [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
210
+ [default2]:[rank2]: trainer.train(dataloader)
211
+ [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
212
+ [default2]:[rank2]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
213
+ [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
214
+ [default2]:[rank2]: outputs = self.pipeline_engine.train_batch_iter(
215
+ [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
216
+ [default2]:[rank2]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
217
+ [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
218
+ [default2]:[rank2]: output = model(**micro_batch)
219
+ [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
220
+ [default2]:[rank2]: return self._call_impl(*args, **kwargs)
221
+ [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
222
+ [default2]:[rank2]: return forward_call(*args, **kwargs)
223
+ [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
224
+ [default2]:[rank2]: sharded_logits = self.model(
225
+ [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
226
+ [default2]:[rank2]: return self._call_impl(*args, **kwargs)
227
+ [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
228
+ [default2]:[rank2]: return forward_call(*args, **kwargs)
229
+ [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
230
+ [default2]:[rank2]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
231
+ [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 786, in forward_with_hidden_states
232
+ [default2]:[rank2]: fp32_sharded_logits = self.cast_to_fp32(x=sharded_logits)["output"]
233
+ [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
234
+ [default2]:[rank2]: return self._call_impl(*args, **kwargs)
235
+ [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
236
+ [default2]:[rank2]: return forward_call(*args, **kwargs)
237
+ [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
238
+ [default2]:[rank2]: output = self.pp_block(**new_kwargs)
239
+ [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 753, in <lambda>
240
+ [default2]:[rank2]: module_builder=lambda: lambda x: x.float(),
241
+ [default2]:[rank2]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 6.14 GiB. GPU  has a total capacity of 79.33 GiB of which 215.94 MiB is free. Including non-PyTorch memory, this process has 79.11 GiB memory in use. Of the allocated memory 67.20 GiB is allocated by PyTorch, and 168.75 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)
242
+ [default6]:[rank6]: Traceback (most recent call last):
243
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
244
+ [default6]:[rank6]: trainer.train(dataloader)
245
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
246
+ [default6]:[rank6]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
247
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
248
+ [default6]:[rank6]: outputs = self.pipeline_engine.train_batch_iter(
249
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
250
+ [default6]:[rank6]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
251
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
252
+ [default6]:[rank6]: output = model(**micro_batch)
253
+ [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
254
+ [default6]:[rank6]: return self._call_impl(*args, **kwargs)
255
+ [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
256
+ [default6]:[rank6]: return forward_call(*args, **kwargs)
257
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
258
+ [default6]:[rank6]: sharded_logits = self.model(
259
+ [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
260
+ [default6]:[rank6]: return self._call_impl(*args, **kwargs)
261
+ [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
262
+ [default6]:[rank6]: return forward_call(*args, **kwargs)
263
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
264
+ [default6]:[rank6]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
265
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 786, in forward_with_hidden_states
266
+ [default6]:[rank6]: fp32_sharded_logits = self.cast_to_fp32(x=sharded_logits)["output"]
267
+ [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
268
+ [default6]:[rank6]: return self._call_impl(*args, **kwargs)
269
+ [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
270
+ [default6]:[rank6]: return forward_call(*args, **kwargs)
271
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
272
+ [default6]:[rank6]: output = self.pp_block(**new_kwargs)
273
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 753, in <lambda>
274
+ [default6]:[rank6]: module_builder=lambda: lambda x: x.float(),
275
+ [default6]:[rank6]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 6.14 GiB. GPU  has a total capacity of 79.33 GiB of which 215.94 MiB is free. Including non-PyTorch memory, this process has 79.11 GiB memory in use. Of the allocated memory 67.20 GiB is allocated by PyTorch, and 168.75 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)
276
+ W0704 00:01:26.783000 140486515681088 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 676789 closing signal SIGTERM
277
+ W0704 00:01:26.784000 140486515681088 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 676791 closing signal SIGTERM
278
+ W0704 00:01:26.784000 140486515681088 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 676792 closing signal SIGTERM
279
+ W0704 00:01:26.785000 140486515681088 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 676793 closing signal SIGTERM
280
+ W0704 00:01:26.785000 140486515681088 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 676795 closing signal SIGTERM
281
+ E0704 00:01:28.099000 140486515681088 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: 1) local_rank: 0 (pid: 676788) of binary: /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10
282
+ Traceback (most recent call last):
283
+ File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in <module>
284
+ sys.exit(main())
285
+ File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper
286
+ return f(*args, **kwargs)
287
+ File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 879, in main
288
+ run(args)
289
+ File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 870, in run
290
+ elastic_launch(
291
+ File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 132, in __call__
292
+ return launch_agent(self._config, self._entrypoint, list(args))
293
+ File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 263, in launch_agent
294
+ raise ChildFailedError(
295
+ torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
296
+ ============================================================
297
+ /fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py FAILED
298
+ ------------------------------------------------------------
299
+ Failures:
300
+ [1]:
301
+ time : 2024-07-04_00:01:26
302
+ host : ip-26-0-169-139.ec2.internal
303
+ rank : 2 (local_rank: 2)
304
+ exitcode : 1 (pid: 676790)
305
+ error_file: <N/A>
306
+ traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
307
+ [2]:
308
+ time : 2024-07-04_00:01:26
309
+ host : ip-26-0-169-139.ec2.internal
310
+ rank : 6 (local_rank: 6)
311
+ exitcode : 1 (pid: 676794)
312
+ error_file: <N/A>
313
+ traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
314
+ ------------------------------------------------------------
315
+ Root Cause (first observed failure):
316
+ [0]:
317
+ time : 2024-07-04_00:01:26
318
+ host : ip-26-0-169-139.ec2.internal
319
+ rank : 0 (local_rank: 0)
320
+ exitcode : 1 (pid: 676788)
321
+ error_file: <N/A>
322
+ traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
323
+ ============================================================
324
+ srun: error: ip-26-0-169-139: task 0: Exited with exit code 1
325
+ 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-8_tp-1_pp-1_mbz-8/status.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ oom