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Upload llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-4

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.gitattributes CHANGED
@@ -116,3 +116,4 @@ llama-1B/8_GPUS/dp-2_tp-1_pp-4_mbz-1/profiler/ip-26-0-174-36_243244.172004896077
116
  llama-1B/8_GPUS/dp-1_tp-2_pp-4_mbz-4/profiler/ip-26-0-164-187_27331.1720048318217251415.pt.trace.json filter=lfs diff=lfs merge=lfs -text
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  llama-1B/8_GPUS/dp-2_tp-4_pp-1_mbz-4/profiler/ip-26-0-163-220_412762.1720048514231027509.pt.trace.json filter=lfs diff=lfs merge=lfs -text
118
  llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-32/profiler/ip-26-0-171-88_1097996.1720048094691939359.pt.trace.json filter=lfs diff=lfs merge=lfs -text
 
 
116
  llama-1B/8_GPUS/dp-1_tp-2_pp-4_mbz-4/profiler/ip-26-0-164-187_27331.1720048318217251415.pt.trace.json filter=lfs diff=lfs merge=lfs -text
117
  llama-1B/8_GPUS/dp-2_tp-4_pp-1_mbz-4/profiler/ip-26-0-163-220_412762.1720048514231027509.pt.trace.json filter=lfs diff=lfs merge=lfs -text
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  llama-1B/8_GPUS/dp-1_tp-8_pp-1_mbz-32/profiler/ip-26-0-171-88_1097996.1720048094691939359.pt.trace.json filter=lfs diff=lfs merge=lfs -text
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+ llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-4/profiler/ip-26-0-169-86_2274198.1720050009949646955.pt.trace.json.tmp filter=lfs diff=lfs merge=lfs -text
llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-4/bench.slurm ADDED
@@ -0,0 +1,111 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ #!/bin/bash
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+
3
+ #SBATCH --job-name=bench_cluster
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+ #SBATCH --time=02:00:00
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+ #SBATCH --partition=hopper-prod
6
+ #SBATCH --nodes=1
7
+ #SBATCH --gres=gpu:8
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+ #SBATCH --qos=normal
9
+ #SBATCH --ntasks-per-node=1
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+ #SBATCH --cpus-per-task=96
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+ #SBATCH --exclusive
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+ #SBATCH --output=/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-4/log.out
13
+ #SBATCH --error=/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-4/log.out
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+
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
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+ 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 $HUGGINGFACE_TOKEN
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+
54
+
55
+ NANOTRON_REPO="/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron"
56
+ CMD="$NANOTRON_REPO/run_train.py --config-file /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-4/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-1_tp-4_pp-2_mbz-4/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-1_tp-4_pp-2_mbz-4/status.txt
84
+ else
85
+ if grep -q "OutOfMemoryError" /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-4/log.out; then
86
+ printf "oom" > /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-4/status.txt
87
+ elif grep -q " CUDA error: an illegal memory access" /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-4/log.out; then
88
+ printf "oom" > /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-4/status.txt
89
+ elif grep -q "Timeout at NCCL" /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-4/log.out; then
90
+ printf "timeout" > /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-4/status.txt
91
+ else
92
+ printf "fail" > /fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-4/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-1_tp-4_pp-2_mbz-4 --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-1_tp-4_pp-2_mbz-4 --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-1_tp-4_pp-2_mbz-4 llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-4 --commit-message "Upload llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-4"
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-1_tp-4_pp-2_mbz-4/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: 1
49
+ expert_parallel_size: 1
50
+ pp: 2
51
+ pp_engine: 1f1b
52
+ tp: 4
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-1_tp-4_pp-2_mbz-4
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: 256
79
+ limit_test_batches: 0
80
+ limit_val_batches: 0
81
+ micro_batch_size: 4
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-1_tp-4_pp-2_mbz-4/log.out ADDED
@@ -0,0 +1,595 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ========================
2
+ START TIME: Wed Jul 3 23:26:01 UTC 2024
3
+ python3 version = Python 3.10.14
4
+ ========================
5
+ The token has not been saved to the git credentials helper. Pass `add_to_git_credential=True` in this function directly or `--add-to-git-credential` if using via `huggingface-cli` if you want to set the git credential as well.
6
+ Token is valid (permission: write).
7
+ Your token has been saved to /admin/home/ferdinand_mom/.cache/huggingface/token
8
+ Login successful
9
+ Already on 'bench_cluster'
10
+ M examples/config_tiny_llama.py
11
+ M examples/config_tiny_llama.yaml
12
+ M examples/train_tiny_llama.sh
13
+ M src/nanotron/models/llama.py
14
+ M src/nanotron/trainer.py
15
+ Your branch is up to date with 'origin/bench_cluster'.
16
+ Job status: RUNNING
17
+ W0703 23:26:10.004000 139973789022016 torch/distributed/run.py:757]
18
+ W0703 23:26:10.004000 139973789022016 torch/distributed/run.py:757] *****************************************
19
+ W0703 23:26:10.004000 139973789022016 torch/distributed/run.py:757] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed.
20
+ W0703 23:26:10.004000 139973789022016 torch/distributed/run.py:757] *****************************************
21
+ [default0]:07/03/2024 23:26:32 [WARNING|DP=0|PP=0|TP=0|ip-26-0-169-86]: [Vocab Size Padding] Padded vocab (size: 50257) with 3 dummy tokens (new size: 50260)
22
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Config:
23
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Config(general=GeneralArgs(project='bench_cluster',
24
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: run='%date_%jobid',
25
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: seed=42,
26
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: step=None,
27
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: consumed_train_samples=None,
28
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: benchmark_csv_path=None,
29
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: ignore_sanity_checks=True),
30
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: parallelism=ParallelismArgs(dp=1,
31
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: pp=2,
32
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: tp=4,
33
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: pp_engine=<nanotron.parallel.pipeline_parallel.engine.OneForwardOneBackwardPipelineEngine object at 0x7f94edff88e0>,
34
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: tp_mode=<TensorParallelLinearMode.REDUCE_SCATTER: 2>,
35
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: tp_linear_async_communication=False,
36
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: expert_parallel_size=1),
37
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: model=ModelArgs(model_config=LlamaConfig(bos_token_id=1,
38
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: eos_token_id=2,
39
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: hidden_act='silu',
40
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: hidden_size=2048,
41
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: initializer_range=0.02,
42
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: intermediate_size=4096,
43
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: is_llama_config=True,
44
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: max_position_embeddings=4096,
45
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: num_attention_heads=32,
46
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: num_hidden_layers=24,
47
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: num_key_value_heads=32,
48
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: pad_token_id=None,
49
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: pretraining_tp=1,
50
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: rms_norm_eps=1e-05,
51
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: rope_scaling=None,
52
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: rope_theta=10000.0,
53
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: tie_word_embeddings=True,
54
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: use_cache=True,
55
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: vocab_size=50260),
56
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: init_method=RandomInit(std=0.025),
57
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: dtype=torch.bfloat16,
58
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: make_vocab_size_divisible_by=1,
59
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: ddp_bucket_cap_mb=25),
60
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2',
61
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: tokenizer_revision=None,
62
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: tokenizer_max_length=None),
63
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: checkpoints=CheckpointsArgs(checkpoints_path=Path('/dev/null'),
64
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: checkpoint_interval=100000,
65
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: save_initial_state=False,
66
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: resume_checkpoint_path=None,
67
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: checkpoints_path_is_shared_file_system=False),
68
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: logging=LoggingArgs(log_level='info',
69
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: log_level_replica='info',
70
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: iteration_step_info_interval=1),
71
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: tokens=TokensArgs(sequence_length=4096,
72
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: train_steps=20,
73
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: micro_batch_size=4,
74
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: batch_accumulation_per_replica=256,
75
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: val_check_interval=-1,
76
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: limit_val_batches=0,
77
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: limit_test_batches=0),
78
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08,
79
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: adam_beta1=0.9,
80
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: adam_beta2=0.95,
81
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: torch_adam_is_fused=True,
82
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: name='adamW'),
83
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: zero_stage=1,
84
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: weight_decay=0.01,
85
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: clip_grad=1.0,
86
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: accumulate_grad_in_fp32=True,
87
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001,
88
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: lr_warmup_steps=1,
89
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: lr_warmup_style='linear',
90
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: lr_decay_style='linear',
91
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: lr_decay_steps=19,
92
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: lr_decay_starting_step=None,
93
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: min_decay_lr=1e-05)),
94
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: data_stages=[DatasetStageArgs(name='Training Stage',
95
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: start_training_step=1,
96
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories',
97
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: hf_dataset_splits='train',
98
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: hf_dataset_config_name=None,
99
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: dataset_processing_num_proc_per_process=64,
100
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: dataset_overwrite_cache=False,
101
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: text_column_name='text'),
102
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: seed=42,
103
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: num_loading_workers=0))],
104
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: profiler=ProfilerArgs(profiler_export_path=Path('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-4')),
105
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: lighteval=None)
106
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Model Config:
107
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: LlamaConfig(bos_token_id=1,
108
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: eos_token_id=2,
109
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: hidden_act='silu',
110
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: hidden_size=2048,
111
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: initializer_range=0.02,
112
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: intermediate_size=4096,
113
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: is_llama_config=True,
114
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: max_position_embeddings=4096,
115
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: num_attention_heads=32,
116
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: num_hidden_layers=24,
117
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: num_key_value_heads=32,
118
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: pad_token_id=None,
119
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: pretraining_tp=1,
120
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: rms_norm_eps=1e-05,
121
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: rope_scaling=None,
122
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: rope_theta=10000.0,
123
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: tie_word_embeddings=True,
124
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: use_cache=True,
125
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: vocab_size=50260)
126
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Building model..
127
+ [default0]:07/03/2024 23:26:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Setting PP block ranks...
128
+ [default5]:07/03/2024 23:26:47 [INFO|DP=0|PP=1|TP=1|ip-26-0-169-86]: Local number of parameters: 131M (249.16MiB)
129
+ [default5]:07/03/2024 23:26:47 [INFO|DP=0|PP=1|TP=1|ip-26-0-169-86]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB
130
+ [default5]:07/03/2024 23:26:47 [INFO|DP=0|PP=1|TP=1|ip-26-0-169-86]: No checkpoint path provided.
131
+ [default1]:07/03/2024 23:26:47 [INFO|DP=0|PP=0|TP=1|ip-26-0-169-86]: Local number of parameters: 173M (329.19MiB)
132
+ [default1]:07/03/2024 23:26:47 [INFO|DP=0|PP=0|TP=1|ip-26-0-169-86]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB
133
+ [default1]:07/03/2024 23:26:47 [INFO|DP=0|PP=0|TP=1|ip-26-0-169-86]: No checkpoint path provided.
134
+ [default0]:07/03/2024 23:26:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Total number of parameters: 1.21G (2313.42MiB)
135
+ [default0]:07/03/2024 23:26:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Local number of parameters: 173M (329.19MiB)
136
+ [default0]:07/03/2024 23:26:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB
137
+ [default0]:07/03/2024 23:26:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: No checkpoint path provided.
138
+ [default0]:07/03/2024 23:26:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Parametrizing model parameters using StandardParametrizator
139
+ [default7]:07/03/2024 23:26:47 [INFO|DP=0|PP=1|TP=3|ip-26-0-169-86]: Local number of parameters: 131M (249.16MiB)
140
+ [default7]:07/03/2024 23:26:47 [INFO|DP=0|PP=1|TP=3|ip-26-0-169-86]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB
141
+ [default7]:07/03/2024 23:26:47 [INFO|DP=0|PP=1|TP=3|ip-26-0-169-86]: No checkpoint path provided.
142
+ [default2]:07/03/2024 23:26:47 [INFO|DP=0|PP=0|TP=2|ip-26-0-169-86]: Local number of parameters: 173M (329.19MiB)
143
+ [default2]:07/03/2024 23:26:47 [INFO|DP=0|PP=0|TP=2|ip-26-0-169-86]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB
144
+ [default2]:07/03/2024 23:26:47 [INFO|DP=0|PP=0|TP=2|ip-26-0-169-86]: No checkpoint path provided.
145
+ [default4]:07/03/2024 23:26:47 [INFO|DP=0|PP=1|TP=0|ip-26-0-169-86]: Local number of parameters: 131M (249.16MiB)
146
+ [default4]:07/03/2024 23:26:47 [INFO|DP=0|PP=1|TP=0|ip-26-0-169-86]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB
147
+ [default4]:07/03/2024 23:26:47 [INFO|DP=0|PP=1|TP=0|ip-26-0-169-86]: No checkpoint path provided.
148
+ [default6]:07/03/2024 23:26:47 [INFO|DP=0|PP=1|TP=2|ip-26-0-169-86]: Local number of parameters: 131M (249.16MiB)
149
+ [default6]:07/03/2024 23:26:47 [INFO|DP=0|PP=1|TP=2|ip-26-0-169-86]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB
150
+ [default6]:07/03/2024 23:26:47 [INFO|DP=0|PP=1|TP=2|ip-26-0-169-86]: No checkpoint path provided.
151
+ [default3]:07/03/2024 23:26:47 [INFO|DP=0|PP=0|TP=3|ip-26-0-169-86]: Local number of parameters: 173M (329.19MiB)
152
+ [default3]:07/03/2024 23:26:47 [INFO|DP=0|PP=0|TP=3|ip-26-0-169-86]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB
153
+ [default3]:07/03/2024 23:26:47 [INFO|DP=0|PP=0|TP=3|ip-26-0-169-86]: No checkpoint path provided.
154
+ [default0]:07/03/2024 23:26:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: [Optimizer Building] Using LearningRateForSP as learning rate
155
+ [default0]:07/03/2024 23:26:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: [ZeRO sharding] Size of optimizer params per rank:
156
+ [default0]:07/03/2024 23:26:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: [ZeRO sharding] DP Rank 0 has 173M out of 173M (100.00%) params' optimizer states
157
+ [default0]:07/03/2024 23:26:49 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples
158
+ [default0]:07/03/2024 23:26:49 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Using `datasets` library
159
+ [default0]:07/03/2024 23:26:49 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Loading tokenizer from openai-community/gpt2 and transformers/hf_hub versions ('4.41.2', '0.23.4')
160
+ [default0]:07/03/2024 23:26:49 [WARNING|DP=0|PP=0|TP=0|ip-26-0-169-86]: Repo card metadata block was not found. Setting CardData to empty.
161
+ [default0]:Repo card metadata block was not found. Setting CardData to empty.
162
+ [default0]:07/03/2024 23:26:52 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: [Training Plan] There are 1 training stages
163
+ [default0]:07/03/2024 23:26:52 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: [Stage Training Stage] start from step 1
164
+ [default0]:07/03/2024 23:26:52 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]:
165
+ [default0]:07/03/2024 23:26:52 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: [Start training] datetime: 2024-07-03 23:26:52.108515 | mbs: 4 | grad_accum: 256 | global_batch_size: 1024 | sequence_length: 4096 | train_steps: 20 | start_iteration_step: 0 | consumed_train_samples: 0
166
+ [default0]:07/03/2024 23:26:52 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps
167
+ [default0]:07/03/2024 23:26:52 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Memory usage: 1660.89MiB. Peak allocated 1660.89MiB. Peak reserved: 1668.00MiB
168
+ [default1]:07/03/2024 23:26:52 [WARNING|DP=0|PP=0|TP=1|ip-26-0-169-86]: Repo card metadata block was not found. Setting CardData to empty.
169
+ [default4]:Repo card metadata block was not found. Setting CardData to empty.
170
+ [default7]:07/03/2024 23:26:52 [WARNING|DP=0|PP=1|TP=3|ip-26-0-169-86]: Repo card metadata block was not found. Setting CardData to empty.
171
+ [default2]:07/03/2024 23:26:52 [WARNING|DP=0|PP=0|TP=2|ip-26-0-169-86]: Repo card metadata block was not found. Setting CardData to empty.
172
+ [default6]:07/03/2024 23:26:52 [WARNING|DP=0|PP=1|TP=2|ip-26-0-169-86]: Repo card metadata block was not found. Setting CardData to empty.
173
+ [default4]:07/03/2024 23:26:52 [WARNING|DP=0|PP=1|TP=0|ip-26-0-169-86]: Repo card metadata block was not found. Setting CardData to empty.
174
+ [default3]:07/03/2024 23:26:52 [WARNING|DP=0|PP=0|TP=3|ip-26-0-169-86]: Repo card metadata block was not found. Setting CardData to empty.
175
+ [default7]:Repo card metadata block was not found. Setting CardData to empty.
176
+ [default2]:Repo card metadata block was not found. Setting CardData to empty.
177
+ [default3]:Repo card metadata block was not found. Setting CardData to empty.
178
+ [default6]:Repo card metadata block was not found. Setting CardData to empty.
179
+ [default1]:Repo card metadata block was not found. Setting CardData to empty.
180
+ [default5]:07/03/2024 23:26:57 [WARNING|DP=0|PP=1|TP=1|ip-26-0-169-86]: Repo card metadata block was not found. Setting CardData to empty.
181
+ [default5]:Repo card metadata block was not found. Setting CardData to empty.
182
+ [default4]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
183
+ [default4]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
184
+ [default7]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
185
+ [default7]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
186
+ [default5]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
187
+ [default5]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
188
+ [default6]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
189
+ [default6]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
190
+ [default0]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
191
+ [default0]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
192
+ [default3]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
193
+ [default3]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
194
+ [default2]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
195
+ [default2]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
196
+ [default1]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
197
+ [default1]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
198
+ [default4]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
199
+ [default4]: warnings.warn(
200
+ [default2]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
201
+ [default2]: warnings.warn(
202
+ [default7]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
203
+ [default7]: warnings.warn(
204
+ [default5]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
205
+ [default5]: warnings.warn(
206
+ [default6]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
207
+ [default6]: warnings.warn(
208
+ [default1]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
209
+ [default1]: warnings.warn(
210
+ [default0]:07/03/2024 23:27:36 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Memory usage: 1732.03MiB. Peak allocated 13063.24MiB. Peak reserved: 13348.00MiB
211
+ [default0]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
212
+ [default0]: warnings.warn(
213
+ [default3]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
214
+ [default3]: warnings.warn(
215
+ [default0]:07/03/2024 23:27:44 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Memory usage: 3048.84MiB. Peak allocated 3048.84MiB. Peak reserved: 13348.00MiB
216
+ [default4]:07/03/2024 23:27:44 [INFO|DP=0|PP=1|TP=0|ip-26-0-169-86]: iteration: 1 / 20 | consumed_tokens: 4.19M | elapsed_time_per_iteration_ms: 45.1K | tokens_per_sec: 92.9K | tokens_per_sec_per_gpu: 11.6K | global_batch_size: 1.02K | lm_loss: 11.1 | lr: 0.0001 | model_tflops_per_gpu: 105 | hardware_tflops_per_gpu: 105 | grad_norm: 15 | cuda_memory_allocated: 2.44G | cuda_max_memory_reserved: 8.57G | hd_total_memory_tb: 312G | hd_used_memory_tb: 68.8G | hd_free_memory_tb: 243G
217
+ [default0]:07/03/2024 23:28:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Memory usage: 3048.84MiB. Peak allocated 14380.05MiB. Peak reserved: 14534.00MiB
218
+ [default0]:07/03/2024 23:28:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Memory usage: 3048.84MiB. Peak allocated 3048.88MiB. Peak reserved: 14534.00MiB
219
+ [default4]:07/03/2024 23:28:07 [INFO|DP=0|PP=1|TP=0|ip-26-0-169-86]: iteration: 2 / 20 | consumed_tokens: 8.39M | elapsed_time_per_iteration_ms: 23.1K | tokens_per_sec: 181K | tokens_per_sec_per_gpu: 22.7K | global_batch_size: 1.02K | lm_loss: 11.1 | lr: 9.53e-05 | model_tflops_per_gpu: 206 | hardware_tflops_per_gpu: 206 | grad_norm: 15.1 | cuda_memory_allocated: 2.44G | cuda_max_memory_reserved: 8.57G | hd_total_memory_tb: 312G | hd_used_memory_tb: 68.8G | hd_free_memory_tb: 243G
220
+ [default4]:07/03/2024 23:28:31 [INFO|DP=0|PP=1|TP=0|ip-26-0-169-86]: iteration: 3 / 20 | consumed_tokens: 12.6M | elapsed_time_per_iteration_ms: 24.8K | tokens_per_sec: 169K | tokens_per_sec_per_gpu: 21.1K | global_batch_size: 1.02K | lm_loss: 11.4 | lr: 9.05e-05 | model_tflops_per_gpu: 192 | hardware_tflops_per_gpu: 192 | grad_norm: 106 | cuda_memory_allocated: 2.44G | cuda_max_memory_reserved: 8.57G | hd_total_memory_tb: 312G | hd_used_memory_tb: 68.8G | hd_free_memory_tb: 243G
221
+ [default0]:07/03/2024 23:28:31 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Memory usage: 3048.84MiB. Peak allocated 14380.05MiB. Peak reserved: 14646.00MiB
222
+ [default0]:07/03/2024 23:28:31 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Memory usage: 3048.84MiB. Peak allocated 3048.88MiB. Peak reserved: 14646.00MiB
223
+ [default0]:STAGE:2024-07-03 23:28:31 2274198:2274198 ActivityProfilerController.cpp:314] Completed Stage: Warm Up
224
+ [default4]:07/03/2024 23:29:04 [INFO|DP=0|PP=1|TP=0|ip-26-0-169-86]: iteration: 4 / 20 | consumed_tokens: 16.8M | elapsed_time_per_iteration_ms: 33K | tokens_per_sec: 127K | tokens_per_sec_per_gpu: 15.9K | global_batch_size: 1.02K | lm_loss: 11.7 | lr: 8.58e-05 | model_tflops_per_gpu: 144 | hardware_tflops_per_gpu: 144 | grad_norm: 24.5 | cuda_memory_allocated: 2.44G | cuda_max_memory_reserved: 8.57G | hd_total_memory_tb: 312G | hd_used_memory_tb: 68.8G | hd_free_memory_tb: 243G
225
+ [default0]:07/03/2024 23:29:04 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Memory usage: 3048.84MiB. Peak allocated 14380.05MiB. Peak reserved: 14646.00MiB
226
+ [default0]:07/03/2024 23:29:04 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Memory usage: 3048.84MiB. Peak allocated 3048.88MiB. Peak reserved: 14646.00MiB
227
+ [default4]:07/03/2024 23:29:38 [INFO|DP=0|PP=1|TP=0|ip-26-0-169-86]: iteration: 5 / 20 | consumed_tokens: 21M | elapsed_time_per_iteration_ms: 33.3K | tokens_per_sec: 126K | tokens_per_sec_per_gpu: 15.7K | global_batch_size: 1.02K | lm_loss: 10 | lr: 8.11e-05 | model_tflops_per_gpu: 143 | hardware_tflops_per_gpu: 143 | grad_norm: 11
228
+ [default0]:07/03/2024 23:29:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-86]: Memory usage: 3048.84MiB. Peak allocated 14380.05MiB. Peak reserved: 14646.00MiB
229
+ [default4]:07/03/2024 23:30:11 [INFO|DP=0|PP=1|TP=0|ip-26-0-169-86]: iteration: 6 / 20 | consumed_tokens: 25.2M | elapsed_time_per_iteration_ms: 33.1K | tokens_per_sec: 127K | tokens_per_sec_per_gpu: 15.9K | global_batch_size: 1.02K | lm_loss: 9.46 | lr: 7.63e-05 | model_tflops_per_gpu: 144 | hardware_tflops_per_gpu: 144 | grad_norm: 7.2
230
+ [default0]:STAGE:2024-07-03 23:31:36 2274198:2274198 ActivityProfilerController.cpp:320] Completed Stage: Collection
231
+ [default0]:STAGE:2024-07-03 23:31:45 2274198:2274198 ActivityProfilerController.cpp:324] Completed Stage: Post Processing
232
+ [default1]:[rank1]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=175141, OpType=_REDUCE_SCATTER_BASE, NumelIn=33554432, NumelOut=8388608, Timeout(ms)=600000) ran for 600016 milliseconds before timing out.
233
+ [default6]:[rank6]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=13834, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600052 milliseconds before timing out.
234
+ [default2]:[rank2]:[E ProcessGroupNCCL.cpp:563] [Rank 2] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=175141, OpType=_REDUCE_SCATTER_BASE, NumelIn=33554432, NumelOut=8388608, Timeout(ms)=600000) ran for 600054 milliseconds before timing out.
235
+ [default7]:[rank7]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=13834, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600052 milliseconds before timing out.
236
+ [default3]:[rank3]:[E ProcessGroupNCCL.cpp:563] [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=175141, OpType=_REDUCE_SCATTER_BASE, NumelIn=33554432, NumelOut=8388608, Timeout(ms)=600000) ran for 600092 milliseconds before timing out.
237
+ [default5]:[rank5]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=13834, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600055 milliseconds before timing out.
238
+ [default4]:[rank4]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=13834, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600065 milliseconds before timing out.
239
+ [default6]:[rank6]: Traceback (most recent call last):
240
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
241
+ [default6]:[rank6]: trainer.train(dataloader)
242
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
243
+ [default6]:[rank6]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
244
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
245
+ [default6]:[rank6]: outputs = self.pipeline_engine.train_batch_iter(
246
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
247
+ [default6]:[rank6]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
248
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
249
+ [default6]:[rank6]: output = model(**micro_batch)
250
+ [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
251
+ [default6]:[rank6]: return self._call_impl(*args, **kwargs)
252
+ [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
253
+ [default6]:[rank6]: return forward_call(*args, **kwargs)
254
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
255
+ [default6]:[rank6]: sharded_logits = self.model(
256
+ [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
257
+ [default6]:[rank6]: return self._call_impl(*args, **kwargs)
258
+ [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
259
+ [default6]:[rank6]: return forward_call(*args, **kwargs)
260
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
261
+ [default6]:[rank6]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
262
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
263
+ [default6]:[rank6]: hidden_encoder_states = encoder_block(**hidden_encoder_states)
264
+ [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
265
+ [default6]:[rank6]: return self._call_impl(*args, **kwargs)
266
+ [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
267
+ [default6]:[rank6]: return forward_call(*args, **kwargs)
268
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward
269
+ [default6]:[rank6]: new_kwargs[name] = recv_from_pipeline_state_buffer(
270
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer
271
+ [default6]:[rank6]: pipeline_state.run_communication()
272
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication
273
+ [default6]:[rank6]: recv_activation_tensor = recv_activation()
274
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__
275
+ [default6]:[rank6]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0]
276
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors
277
+ [default6]:[rank6]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag)
278
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors
279
+ [default6]:[rank6]: meta = self._recv_meta(from_rank=from_rank, tag=tag)
280
+ [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 267, in _recv_meta
281
+ [default6]:[rank6]: self.second_metadata = torch.empty(second_metadata_num_elements, dtype=torch.long, device=self.device)
282
+ [default6]:[rank6]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate more than 1EB memory.
283
+ [default7]:[rank7]: Traceback (most recent call last):
284
+ [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
285
+ [default7]:[rank7]: trainer.train(dataloader)
286
+ [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
287
+ [default7]:[rank7]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
288
+ [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
289
+ [default7]:[rank7]: outputs = self.pipeline_engine.train_batch_iter(
290
+ [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
291
+ [default7]:[rank7]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
292
+ [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
293
+ [default7]:[rank7]: output = model(**micro_batch)
294
+ [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
295
+ [default7]:[rank7]: return self._call_impl(*args, **kwargs)
296
+ [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
297
+ [default7]:[rank7]: return forward_call(*args, **kwargs)
298
+ [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
299
+ [default7]:[rank7]: sharded_logits = self.model(
300
+ [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
301
+ [default7]:[rank7]: return self._call_impl(*args, **kwargs)
302
+ [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
303
+ [default7]:[rank7]: return forward_call(*args, **kwargs)
304
+ [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
305
+ [default7]:[rank7]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
306
+ [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
307
+ [default7]:[rank7]: hidden_encoder_states = encoder_block(**hidden_encoder_states)
308
+ [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
309
+ [default7]:[rank7]: return self._call_impl(*args, **kwargs)
310
+ [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
311
+ [default7]:[rank7]: return forward_call(*args, **kwargs)
312
+ [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward
313
+ [default7]:[rank7]: new_kwargs[name] = recv_from_pipeline_state_buffer(
314
+ [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer
315
+ [default7]:[rank7]: pipeline_state.run_communication()
316
+ [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication
317
+ [default7]:[rank7]: recv_activation_tensor = recv_activation()
318
+ [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__
319
+ [default7]:[rank7]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0]
320
+ [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors
321
+ [default7]:[rank7]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag)
322
+ [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors
323
+ [default7]:[rank7]: meta = self._recv_meta(from_rank=from_rank, tag=tag)
324
+ [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 267, in _recv_meta
325
+ [default7]:[rank7]: self.second_metadata = torch.empty(second_metadata_num_elements, dtype=torch.long, device=self.device)
326
+ [default7]:[rank7]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate more than 1EB memory.
327
+ [default5]:[rank5]: Traceback (most recent call last):
328
+ [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
329
+ [default5]:[rank5]: trainer.train(dataloader)
330
+ [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
331
+ [default5]:[rank5]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
332
+ [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
333
+ [default5]:[rank5]: outputs = self.pipeline_engine.train_batch_iter(
334
+ [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
335
+ [default5]:[rank5]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
336
+ [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
337
+ [default5]:[rank5]: output = model(**micro_batch)
338
+ [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
339
+ [default5]:[rank5]: return self._call_impl(*args, **kwargs)
340
+ [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
341
+ [default5]:[rank5]: return forward_call(*args, **kwargs)
342
+ [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
343
+ [default5]:[rank5]: sharded_logits = self.model(
344
+ [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
345
+ [default5]:[rank5]: return self._call_impl(*args, **kwargs)
346
+ [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
347
+ [default5]:[rank5]: return forward_call(*args, **kwargs)
348
+ [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
349
+ [default5]:[rank5]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
350
+ [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
351
+ [default5]:[rank5]: hidden_encoder_states = encoder_block(**hidden_encoder_states)
352
+ [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
353
+ [default5]:[rank5]: return self._call_impl(*args, **kwargs)
354
+ [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
355
+ [default5]:[rank5]: return forward_call(*args, **kwargs)
356
+ [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward
357
+ [default5]:[rank5]: new_kwargs[name] = recv_from_pipeline_state_buffer(
358
+ [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer
359
+ [default5]:[rank5]: pipeline_state.run_communication()
360
+ [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication
361
+ [default5]:[rank5]: recv_activation_tensor = recv_activation()
362
+ [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__
363
+ [default5]:[rank5]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0]
364
+ [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors
365
+ [default5]:[rank5]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag)
366
+ [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors
367
+ [default5]:[rank5]: meta = self._recv_meta(from_rank=from_rank, tag=tag)
368
+ [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 267, in _recv_meta
369
+ [default5]:[rank5]: self.second_metadata = torch.empty(second_metadata_num_elements, dtype=torch.long, device=self.device)
370
+ [default5]:[rank5]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate more than 1EB memory.
371
+ [default4]:[rank4]: Traceback (most recent call last):
372
+ [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
373
+ [default4]:[rank4]: trainer.train(dataloader)
374
+ [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
375
+ [default4]:[rank4]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
376
+ [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
377
+ [default4]:[rank4]: outputs = self.pipeline_engine.train_batch_iter(
378
+ [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
379
+ [default4]:[rank4]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
380
+ [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
381
+ [default4]:[rank4]: output = model(**micro_batch)
382
+ [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
383
+ [default4]:[rank4]: return self._call_impl(*args, **kwargs)
384
+ [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
385
+ [default4]:[rank4]: return forward_call(*args, **kwargs)
386
+ [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
387
+ [default4]:[rank4]: sharded_logits = self.model(
388
+ [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
389
+ [default4]:[rank4]: return self._call_impl(*args, **kwargs)
390
+ [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
391
+ [default4]:[rank4]: return forward_call(*args, **kwargs)
392
+ [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
393
+ [default4]:[rank4]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
394
+ [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
395
+ [default4]:[rank4]: hidden_encoder_states = encoder_block(**hidden_encoder_states)
396
+ [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
397
+ [default4]:[rank4]: return self._call_impl(*args, **kwargs)
398
+ [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
399
+ [default4]:[rank4]: return forward_call(*args, **kwargs)
400
+ [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward
401
+ [default4]:[rank4]: new_kwargs[name] = recv_from_pipeline_state_buffer(
402
+ [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer
403
+ [default4]:[rank4]: pipeline_state.run_communication()
404
+ [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication
405
+ [default4]:[rank4]: recv_activation_tensor = recv_activation()
406
+ [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__
407
+ [default4]:[rank4]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0]
408
+ [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors
409
+ [default4]:[rank4]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag)
410
+ [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors
411
+ [default4]:[rank4]: meta = self._recv_meta(from_rank=from_rank, tag=tag)
412
+ [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 267, in _recv_meta
413
+ [default4]:[rank4]: self.second_metadata = torch.empty(second_metadata_num_elements, dtype=torch.long, device=self.device)
414
+ [default4]:[rank4]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate more than 1EB memory.
415
+ [default6]:[rank6]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 1] Timeout at NCCL work: 13834, last enqueued NCCL work: 13834, last completed NCCL work: 13833.
416
+ [default6]:[rank6]:[E ProcessGroupNCCL.cpp:577] [Rank 1] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
417
+ [default6]:[rank6]:[E ProcessGroupNCCL.cpp:583] [Rank 1] To avoid data inconsistency, we are taking the entire process down.
418
+ [default6]:[rank6]:[E ProcessGroupNCCL.cpp:1414] [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=13834, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600052 milliseconds before timing out.
419
+ [default6]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
420
+ [default6]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7ffa8926d897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
421
+ [default6]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7ffa8a546c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
422
+ [default6]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7ffa8a54ba80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
423
+ [default6]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7ffa8a54cdcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
424
+ [default6]:frame #4: <unknown function> + 0xd3e95 (0x7ffad5fe5e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
425
+ [default6]:frame #5: <unknown function> + 0x8609 (0x7ffadb02c609 in /lib/x86_64-linux-gnu/libpthread.so.0)
426
+ [default6]:frame #6: clone + 0x43 (0x7ffadadf7353 in /lib/x86_64-linux-gnu/libc.so.6)
427
+ [default6]:
428
+ [default6]:terminate called after throwing an instance of 'c10::DistBackendError'
429
+ [default6]: what(): [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=13834, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600052 milliseconds before timing out.
430
+ [default6]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
431
+ [default6]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7ffa8926d897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
432
+ [default6]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7ffa8a546c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
433
+ [default6]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7ffa8a54ba80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
434
+ [default6]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7ffa8a54cdcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
435
+ [default6]:frame #4: <unknown function> + 0xd3e95 (0x7ffad5fe5e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
436
+ [default6]:frame #5: <unknown function> + 0x8609 (0x7ffadb02c609 in /lib/x86_64-linux-gnu/libpthread.so.0)
437
+ [default6]:frame #6: clone + 0x43 (0x7ffadadf7353 in /lib/x86_64-linux-gnu/libc.so.6)
438
+ [default6]:
439
+ [default6]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1418 (most recent call first):
440
+ [default6]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7ffa8926d897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
441
+ [default6]:frame #1: <unknown function> + 0xe32119 (0x7ffa8a1d0119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
442
+ [default6]:frame #2: <unknown function> + 0xd3e95 (0x7ffad5fe5e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
443
+ [default6]:frame #3: <unknown function> + 0x8609 (0x7ffadb02c609 in /lib/x86_64-linux-gnu/libpthread.so.0)
444
+ [default6]:frame #4: clone + 0x43 (0x7ffadadf7353 in /lib/x86_64-linux-gnu/libc.so.6)
445
+ [default6]:
446
+ [default7]:[rank7]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 1] Timeout at NCCL work: 13834, last enqueued NCCL work: 13834, last completed NCCL work: 13833.
447
+ [default7]:[rank7]:[E ProcessGroupNCCL.cpp:577] [Rank 1] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
448
+ [default7]:[rank7]:[E ProcessGroupNCCL.cpp:583] [Rank 1] To avoid data inconsistency, we are taking the entire process down.
449
+ [default7]:[rank7]:[E ProcessGroupNCCL.cpp:1414] [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=13834, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600052 milliseconds before timing out.
450
+ [default7]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
451
+ [default7]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f08104fd897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
452
+ [default7]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f08117d6c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
453
+ [default7]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f08117dba80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
454
+ [default7]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f08117dcdcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
455
+ [default7]:frame #4: <unknown function> + 0xd3e95 (0x7f085d275e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
456
+ [default7]:frame #5: <unknown function> + 0x8609 (0x7f08622bc609 in /lib/x86_64-linux-gnu/libpthread.so.0)
457
+ [default7]:frame #6: clone + 0x43 (0x7f0862087353 in /lib/x86_64-linux-gnu/libc.so.6)
458
+ [default7]:
459
+ [default7]:terminate called after throwing an instance of 'c10::DistBackendError'
460
+ [default7]: what(): [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=13834, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600052 milliseconds before timing out.
461
+ [default7]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
462
+ [default7]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f08104fd897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
463
+ [default7]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f08117d6c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
464
+ [default7]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f08117dba80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
465
+ [default7]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f08117dcdcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
466
+ [default7]:frame #4: <unknown function> + 0xd3e95 (0x7f085d275e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
467
+ [default7]:frame #5: <unknown function> + 0x8609 (0x7f08622bc609 in /lib/x86_64-linux-gnu/libpthread.so.0)
468
+ [default7]:frame #6: clone + 0x43 (0x7f0862087353 in /lib/x86_64-linux-gnu/libc.so.6)
469
+ [default7]:
470
+ [default7]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1418 (most recent call first):
471
+ [default7]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f08104fd897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
472
+ [default7]:frame #1: <unknown function> + 0xe32119 (0x7f0811460119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
473
+ [default7]:frame #2: <unknown function> + 0xd3e95 (0x7f085d275e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
474
+ [default7]:frame #3: <unknown function> + 0x8609 (0x7f08622bc609 in /lib/x86_64-linux-gnu/libpthread.so.0)
475
+ [default7]:frame #4: clone + 0x43 (0x7f0862087353 in /lib/x86_64-linux-gnu/libc.so.6)
476
+ [default7]:
477
+ [default5]:[rank5]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 1] Timeout at NCCL work: 13834, last enqueued NCCL work: 13834, last completed NCCL work: 13833.
478
+ [default5]:[rank5]:[E ProcessGroupNCCL.cpp:577] [Rank 1] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
479
+ [default5]:[rank5]:[E ProcessGroupNCCL.cpp:583] [Rank 1] To avoid data inconsistency, we are taking the entire process down.
480
+ [default5]:[rank5]:[E ProcessGroupNCCL.cpp:1414] [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=13834, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600055 milliseconds before timing out.
481
+ [default5]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
482
+ [default5]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f80e58fb897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
483
+ [default5]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f80e6bd4c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
484
+ [default5]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f80e6bd9a80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
485
+ [default5]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f80e6bdadcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
486
+ [default5]:frame #4: <unknown function> + 0xd3e95 (0x7f8132673e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
487
+ [default5]:frame #5: <unknown function> + 0x8609 (0x7f81376ba609 in /lib/x86_64-linux-gnu/libpthread.so.0)
488
+ [default5]:frame #6: clone + 0x43 (0x7f8137485353 in /lib/x86_64-linux-gnu/libc.so.6)
489
+ [default5]:
490
+ [default5]:terminate called after throwing an instance of 'c10::DistBackendError'
491
+ [default5]: what(): [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=13834, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600055 milliseconds before timing out.
492
+ [default5]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
493
+ [default5]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f80e58fb897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
494
+ [default5]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f80e6bd4c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
495
+ [default5]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f80e6bd9a80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
496
+ [default5]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f80e6bdadcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
497
+ [default5]:frame #4: <unknown function> + 0xd3e95 (0x7f8132673e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
498
+ [default5]:frame #5: <unknown function> + 0x8609 (0x7f81376ba609 in /lib/x86_64-linux-gnu/libpthread.so.0)
499
+ [default5]:frame #6: clone + 0x43 (0x7f8137485353 in /lib/x86_64-linux-gnu/libc.so.6)
500
+ [default5]:
501
+ [default5]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1418 (most recent call first):
502
+ [default5]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f80e58fb897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
503
+ [default5]:frame #1: <unknown function> + 0xe32119 (0x7f80e685e119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
504
+ [default5]:frame #2: <unknown function> + 0xd3e95 (0x7f8132673e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
505
+ [default5]:frame #3: <unknown function> + 0x8609 (0x7f81376ba609 in /lib/x86_64-linux-gnu/libpthread.so.0)
506
+ [default5]:frame #4: clone + 0x43 (0x7f8137485353 in /lib/x86_64-linux-gnu/libc.so.6)
507
+ [default5]:
508
+ [default4]:[rank4]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 1] Timeout at NCCL work: 13834, last enqueued NCCL work: 13834, last completed NCCL work: 13833.
509
+ [default4]:[rank4]:[E ProcessGroupNCCL.cpp:577] [Rank 1] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
510
+ [default4]:[rank4]:[E ProcessGroupNCCL.cpp:583] [Rank 1] To avoid data inconsistency, we are taking the entire process down.
511
+ [default4]:[rank4]:[E ProcessGroupNCCL.cpp:1414] [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=13834, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600065 milliseconds before timing out.
512
+ [default4]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
513
+ [default4]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f4c6224c897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
514
+ [default4]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f4c63525c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
515
+ [default4]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f4c6352aa80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
516
+ [default4]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f4c6352bdcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
517
+ [default4]:frame #4: <unknown function> + 0xd3e95 (0x7f4caefc4e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
518
+ [default4]:frame #5: <unknown function> + 0x8609 (0x7f4cb400b609 in /lib/x86_64-linux-gnu/libpthread.so.0)
519
+ [default4]:frame #6: clone + 0x43 (0x7f4cb3dd6353 in /lib/x86_64-linux-gnu/libc.so.6)
520
+ [default4]:
521
+ [default4]:terminate called after throwing an instance of 'c10::DistBackendError'
522
+ [default4]: what(): [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=13834, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600065 milliseconds before timing out.
523
+ [default4]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
524
+ [default4]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f4c6224c897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
525
+ [default4]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f4c63525c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
526
+ [default4]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f4c6352aa80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
527
+ [default4]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f4c6352bdcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
528
+ [default4]:frame #4: <unknown function> + 0xd3e95 (0x7f4caefc4e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
529
+ [default4]:frame #5: <unknown function> + 0x8609 (0x7f4cb400b609 in /lib/x86_64-linux-gnu/libpthread.so.0)
530
+ [default4]:frame #6: clone + 0x43 (0x7f4cb3dd6353 in /lib/x86_64-linux-gnu/libc.so.6)
531
+ [default4]:
532
+ [default4]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1418 (most recent call first):
533
+ [default4]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f4c6224c897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
534
+ [default4]:frame #1: <unknown function> + 0xe32119 (0x7f4c631af119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
535
+ [default4]:frame #2: <unknown function> + 0xd3e95 (0x7f4caefc4e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
536
+ [default4]:frame #3: <unknown function> + 0x8609 (0x7f4cb400b609 in /lib/x86_64-linux-gnu/libpthread.so.0)
537
+ [default4]:frame #4: clone + 0x43 (0x7f4cb3dd6353 in /lib/x86_64-linux-gnu/libc.so.6)
538
+ [default4]:
539
+ W0703 23:40:16.055000 139973789022016 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2274198 closing signal SIGTERM
540
+ W0703 23:40:16.055000 139973789022016 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2274199 closing signal SIGTERM
541
+ W0703 23:40:16.055000 139973789022016 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2274200 closing signal SIGTERM
542
+ W0703 23:40:16.055000 139973789022016 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2274201 closing signal SIGTERM
543
+ E0703 23:40:20.862000 139973789022016 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: -6) local_rank: 4 (pid: 2274202) of binary: /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10
544
+ Traceback (most recent call last):
545
+ File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in <module>
546
+ sys.exit(main())
547
+ File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper
548
+ return f(*args, **kwargs)
549
+ File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 879, in main
550
+ run(args)
551
+ File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 870, in run
552
+ elastic_launch(
553
+ File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 132, in __call__
554
+ return launch_agent(self._config, self._entrypoint, list(args))
555
+ File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 263, in launch_agent
556
+ raise ChildFailedError(
557
+ torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
558
+ ============================================================
559
+ /fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py FAILED
560
+ ------------------------------------------------------------
561
+ Failures:
562
+ [1]:
563
+ time : 2024-07-03_23:40:16
564
+ host : ip-26-0-169-86.ec2.internal
565
+ rank : 5 (local_rank: 5)
566
+ exitcode : -6 (pid: 2274203)
567
+ error_file: <N/A>
568
+ traceback : Signal 6 (SIGABRT) received by PID 2274203
569
+ [2]:
570
+ time : 2024-07-03_23:40:16
571
+ host : ip-26-0-169-86.ec2.internal
572
+ rank : 6 (local_rank: 6)
573
+ exitcode : -6 (pid: 2274204)
574
+ error_file: <N/A>
575
+ traceback : Signal 6 (SIGABRT) received by PID 2274204
576
+ [3]:
577
+ time : 2024-07-03_23:40:16
578
+ host : ip-26-0-169-86.ec2.internal
579
+ rank : 7 (local_rank: 7)
580
+ exitcode : -6 (pid: 2274205)
581
+ error_file: <N/A>
582
+ traceback : Signal 6 (SIGABRT) received by PID 2274205
583
+ ------------------------------------------------------------
584
+ Root Cause (first observed failure):
585
+ [0]:
586
+ time : 2024-07-03_23:40:16
587
+ host : ip-26-0-169-86.ec2.internal
588
+ rank : 4 (local_rank: 4)
589
+ exitcode : -6 (pid: 2274202)
590
+ error_file: <N/A>
591
+ traceback : Signal 6 (SIGABRT) received by PID 2274202
592
+ ============================================================
593
+ srun: error: ip-26-0-169-86: task 0: Exited with exit code 1
594
+ 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.
595
+
llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-4/profiler/ip-26-0-169-86_2274198.1720050009949646955.pt.trace.json.tmp ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:781117f0f97d49fb807e3801f4455014e1c21e39c28f6f79eb5423cb8f7b16e3
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+ size 848259944
llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-4/status.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ oom