DGX-1 / V100-32GB-SMX2 - nvlink is not activated (0 ... | deepspeedai/DeepSpeed

Hi, what are the requirement for NVLINK to function. I have 2 machine - one is regular pcie 3090 - 2 x cards in nvlink - works good and nvlink shows activity via :
nvidia-smi nvlink -gt r
and DGX-1 server - NVLINK is not activated by DeepSpeed. - show activity as N/A, although
nvidia-smi topo - m / nvidia-smi nvlink -s
show all nvlink present and ready to go. DGX-1 server run by bare (not NVIDIA image) Ubuntu 20, pytorch, cuda, driver, nvcc, nccl - all installed, DeepSpeed compiled with 7.0 gpu feature ...

Would appreciate any help - terminal screen available if needed. \

I am testing on GPT-J-6B - fine-tuning - using code from this repo:

https://github.com/mallorbc/Finetune_GPTNEO_GPTJ6B

.......
nvidia-smi nvlink -gt r :
GPU 1: Tesla V100-SXM2-32GB (UUID: GPU-ed46f244-d7b4-5053-89bc-f68119fa49e9)
Link 0: Raw Tx: N/A
Link 0: Raw Rx: N/A
......
Link 5: Raw Tx: N/A
Link 5: Raw Rx: N/A

(gpt) user@user-X9DRG-HF:~/transformers/Finetune_GPTNEO_GPTJ6B/finetuning_repo$ TRANSFORMERS_OFFLINE=1 deepspeed --num_gpus=8 run_clm.py --deepspeed ds_config.json --model_name_or_path gpt2-xl --train_file train.csv --validation_file validation.csv --do_train --do_eval --overwrite_cache --evaluation_strategy="steps" --output_dir finetuned --num_train_epochs 1 --eval_steps 15 --gradient_accumulation_steps 2 --per_device_train_batch_size 1 --use_fast_tokenizer False --learning_rate 5e-06 --warmup_steps 10 --overwrite_output_dir --fp16
[2021-10-10 00:04:17,843] [WARNING] [runner.py:122:fetch_hostfile] Unable to find hostfile, will proceed with training with local resources only.
[2021-10-10 00:04:18,286] [INFO] [runner.py:360:main] cmd = /home/user/gpt/bin/python -u -m deepspeed.launcher.launch --world_info=eyJsb2NhbGhvc3QiOiBbMCwgMSwgMiwgMywgNCwgNSwgNiwgN119 --master_addr=127.0.0.1 --master_port=29500 run_clm.py --deepspeed ds_config.json --model_name_or_path gpt2-xl --train_file train.csv --validation_file validation.csv --do_train --do_eval --overwrite_cache --evaluation_strategy=steps --output_dir finetuned --num_train_epochs 1 --eval_steps 15 --gradient_accumulation_steps 2 --per_device_train_batch_size 1 --use_fast_tokenizer False --learning_rate 5e-06 --warmup_steps 10 --overwrite_output_dir --fp16
[2021-10-10 00:04:19,198] [INFO] [launch.py:80:main] WORLD INFO DICT: {'localhost': [0, 1, 2, 3, 4, 5, 6, 7]}
[2021-10-10 00:04:19,198] [INFO] [launch.py:86:main] nnodes=1, num_local_procs=8, node_rank=0
[2021-10-10 00:04:19,198] [INFO] [launch.py:101:main] global_rank_mapping=defaultdict(<class 'list'>, {'localhost': [0, 1, 2, 3, 4, 5, 6, 7]})
[2021-10-10 00:04:19,198] [INFO] [launch.py:102:main] dist_world_size=8
[2021-10-10 00:04:19,198] [INFO] [launch.py:104:main] Setting CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
[2021-10-10 00:04:20,924] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-10-10 00:04:20,956] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-10-10 00:04:21,018] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-10-10 00:04:21,019] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-10-10 00:04:21,027] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-10-10 00:04:21,051] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-10-10 00:04:21,064] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-10-10 00:04:21,162] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
10/10/2021 00:04:22 - WARNING - main - Process rank: 3, device: cuda:3, n_gpu: 1distributed training: True, 16-bits training: True
10/10/2021 00:04:22 - WARNING - main - Process rank: 1, device: cuda:1, n_gpu: 1distributed training: True, 16-bits training: True
10/10/2021 00:04:22 - WARNING - main - Process rank: 0, device: cuda:0, n_gpu: 1distributed training: True, 16-bits training: True
10/10/2021 00:04:22 - WARNING - main - Process rank: 2, device: cuda:2, n_gpu: 1distributed training: True, 16-bits training: True
10/10/2021 00:04:22 - WARNING - main - Process rank: 7, device: cuda:7, n_gpu: 1distributed training: True, 16-bits training: True
10/10/2021 00:04:22 - WARNING - main - Process rank: 5, device: cuda:5, n_gpu: 1distributed training: True, 16-bits training: True
10/10/2021 00:04:22 - INFO - main - Training/evaluation parameters TrainingArguments(
_n_gpu=1,
adafactor=False,
adam_beta1=0.9,
adam_beta2=0.999,
adam_epsilon=1e-08,
dataloader_drop_last=False,
dataloader_num_workers=0,
dataloader_pin_memory=True,
ddp_find_unused_parameters=None,
debug=[],
deepspeed=ds_config.json,
disable_tqdm=False,
do_eval=True,
do_predict=False,
do_train=True,
eval_accumulation_steps=None,
eval_steps=15,
evaluation_strategy=IntervalStrategy.STEPS,
fp16=True,
fp16_backend=auto,
fp16_full_eval=False,
fp16_opt_level=O1,
gradient_accumulation_steps=2,
gradient_checkpointing=False,
greater_is_better=None,
group_by_length=False,
hub_model_id=None,
hub_strategy=HubStrategy.EVERY_SAVE,
hub_token=<HUB_TOKEN>,
ignore_data_skip=False,
label_names=None,
label_smoothing_factor=0.0,
learning_rate=5e-06,
length_column_name=length,
load_best_model_at_end=False,
local_rank=0,
log_level=-1,
log_level_replica=-1,
log_on_each_node=True,
logging_dir=finetuned/runs/Oct10_00-04-20_user-X9DRG-HF,
logging_first_step=False,
logging_nan_inf_filter=True,
logging_steps=500,
logging_strategy=IntervalStrategy.STEPS,
lr_scheduler_type=SchedulerType.LINEAR,
max_grad_norm=1.0,
max_steps=-1,
metric_for_best_model=None,
mp_parameters=,
no_cuda=False,
num_train_epochs=1.0,
output_dir=finetuned,
overwrite_output_dir=True,
past_index=-1,
per_device_eval_batch_size=8,
per_device_train_batch_size=1,
prediction_loss_only=False,
push_to_hub=False,
push_to_hub_model_id=None,
push_to_hub_organization=None,
push_to_hub_token=<PUSH_TO_HUB_TOKEN>,
remove_unused_columns=True,
report_to=['tensorboard'],
resume_from_checkpoint=None,
run_name=finetuned,
save_on_each_node=False,
save_steps=500,
save_strategy=IntervalStrategy.STEPS,
save_total_limit=None,
seed=42,
sharded_ddp=[],
skip_memory_metrics=True,
tpu_metrics_debug=False,
tpu_num_cores=None,
use_legacy_prediction_loop=False,
warmup_ratio=0.0,
warmup_steps=10,
weight_decay=0.0,
xpu_backend=None,
)
10/10/2021 00:04:22 - WARNING - main - Process rank: 6, device: cuda:6, n_gpu: 1distributed training: True, 16-bits training: True
10/10/2021 00:04:22 - WARNING - main - Process rank: 4, device: cuda:4, n_gpu: 1distributed training: True, 16-bits training: True
10/10/2021 00:04:22 - WARNING - datasets.builder - Using custom data configuration default-9dc66b5cf9d5f9f5
10/10/2021 00:04:22 - WARNING - datasets.builder - Using custom data configuration default-9dc66b5cf9d5f9f5
10/10/2021 00:04:22 - WARNING - datasets.builder - Reusing dataset csv (/home/user/.cache/huggingface/datasets/csv/default-9dc66b5cf9d5f9f5/0.0.0/9144e0a4e8435090117cea53e6c7537173ef2304525df4a077c435d8ee7828ff)
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10/10/2021 00:04:22 - WARNING - datasets.builder - Reusing dataset csv (/home/user/.cache/huggingface/datasets/csv/default-9dc66b5cf9d5f9f5/0.0.0/9144e0a4e8435090117cea53e6c7537173ef2304525df4a077c435d8ee7828ff)
10/10/2021 00:04:22 - WARNING - datasets.builder - Using custom data configuration default-9dc66b5cf9d5f9f5
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10/10/2021 00:04:23 - WARNING - datasets.builder - Reusing dataset csv (/home/user/.cache/huggingface/datasets/csv/default-9dc66b5cf9d5f9f5/0.0.0/9144e0a4e8435090117cea53e6c7537173ef2304525df4a077c435d8ee7828ff)
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10/10/2021 00:04:23 - WARNING - datasets.builder - Reusing dataset csv (/home/user/.cache/huggingface/datasets/csv/default-9dc66b5cf9d5f9f5/0.0.0/9144e0a4e8435090117cea53e6c7537173ef2304525df4a077c435d8ee7828ff)
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[INFO|configuration_utils.py:531] 2021-10-10 00:04:23,014 >> Offline mode: forcing local_files_only=True
[INFO|configuration_utils.py:584] 2021-10-10 00:04:23,015 >> loading configuration file https://huggingface.co/gpt2-xl/resolve/main/config.json from cache at /home/user/.cache/huggingface/transformers/d2de8fec009fa9b9196047559bcac6c1f02a9c500718b4346bc516354965b1ca.d684cb2afa3f8c44c73bd67537d9aa5ff6044658793e077d7306ef2e37dd79bd
[INFO|configuration_utils.py:621] 2021-10-10 00:04:23,017 >> Model config GPT2Config {
"activation_function": "gelu_new",
"architectures": [
"GPT2LMHeadModel"
],
"attn_pdrop": 0.1,
"bos_token_id": 50256,
"embd_pdrop": 0.1,
"eos_token_id": 50256,
"initializer_range": 0.02,
"layer_norm_epsilon": 1e-05,
"model_type": "gpt2",
"n_ctx": 1024,
"n_embd": 1600,
"n_head": 25,
"n_inner": null,
"n_layer": 48,
"n_positions": 1024,
"output_past": true,
"reorder_and_upcast_attn": false,
"resid_pdrop": 0.1,
"scale_attn_by_inverse_layer_idx": false,
"scale_attn_weights": true,
"summary_activation": null,
"summary_first_dropout": 0.1,
"summary_proj_to_labels": true,
"summary_type": "cls_index",
"summary_use_proj": true,
"task_specific_params": {
"text-generation": {
"do_sample": true,
"max_length": 50
}
},
"transformers_version": "4.12.0.dev0",
"use_cache": true,
"vocab_size": 50257
}

[INFO|tokenization_auto.py:310] 2021-10-10 00:04:23,017 >> Offline mode: forcing local_files_only=True
[INFO|tokenization_auto.py:334] 2021-10-10 00:04:23,017 >> Could not locate the tokenizer configuration file, will try to use the model config instead.
[INFO|configuration_utils.py:531] 2021-10-10 00:04:23,017 >> Offline mode: forcing local_files_only=True
[INFO|configuration_utils.py:584] 2021-10-10 00:04:23,018 >> loading configuration file https://huggingface.co/gpt2-xl/resolve/main/config.json from cache at /home/user/.cache/huggingface/transformers/d2de8fec009fa9b9196047559bcac6c1f02a9c500718b4346bc516354965b1ca.d684cb2afa3f8c44c73bd67537d9aa5ff6044658793e077d7306ef2e37dd79bd
[INFO|configuration_utils.py:621] 2021-10-10 00:04:23,019 >> Model config GPT2Config {
"activation_function": "gelu_new",
"architectures": [
"GPT2LMHeadModel"
],
"attn_pdrop": 0.1,
"bos_token_id": 50256,
"embd_pdrop": 0.1,
"eos_token_id": 50256,
"initializer_range": 0.02,
"layer_norm_epsilon": 1e-05,
"model_type": "gpt2",
"n_ctx": 1024,
"n_embd": 1600,
"n_head": 25,
"n_inner": null,
"n_layer": 48,
"n_positions": 1024,
"output_past": true,
"reorder_and_upcast_attn": false,
"resid_pdrop": 0.1,
"scale_attn_by_inverse_layer_idx": false,
"scale_attn_weights": true,
"summary_activation": null,
"summary_first_dropout": 0.1,
"summary_proj_to_labels": true,
"summary_type": "cls_index",
"summary_use_proj": true,
"task_specific_params": {
"text-generation": {
"do_sample": true,
"max_length": 50
}
},
"transformers_version": "4.12.0.dev0",
"use_cache": true,
"vocab_size": 50257
}

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[INFO|tokenization_utils_base.py:1629] 2021-10-10 00:04:23,020 >> Offline mode: forcing local_files_only=True
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[INFO|tokenization_utils_base.py:1717] 2021-10-10 00:04:23,023 >> Can't load following files from cache: ['added_tokens_file', 'special_tokens_map_file', 'tokenizer_config_file'] and cannot check if these files are necessary for the tokenizer to operate.
[INFO|tokenization_utils_base.py:1742] 2021-10-10 00:04:23,023 >> loading file https://huggingface.co/gpt2-xl/resolve/main/vocab.json from cache at /home/user/.cache/huggingface/transformers/8560a2df03f812b276794ae6935255d0590522553a4c8103155472b07591a21b.c7ed1f96aac49e745788faa77ba0a26a392643a50bb388b9c04ff469e555241f
[INFO|tokenization_utils_base.py:1742] 2021-10-10 00:04:23,023 >> loading file https://huggingface.co/gpt2-xl/resolve/main/merges.txt from cache at /home/user/.cache/huggingface/transformers/18fe27e0b70062b3e45fc4e827d5449d9fe85875937594da927e48cb657366d1.5d12962c5ee615a4c803841266e9c3be9a691a924f72d395d3a6c6c81157788b
[INFO|tokenization_utils_base.py:1742] 2021-10-10 00:04:23,023 >> loading file https://huggingface.co/gpt2-xl/resolve/main/tokenizer.json from cache at /home/user/.cache/huggingface/transformers/aabb8839163cd911f810ab23f5ae8c966b9b9ea60622c429020611caa389b04b.cf2d0ecb83b6df91b3dbb53f1d1e4c311578bfd3aa0e04934215a49bf9898df0
[INFO|configuration_utils.py:531] 2021-10-10 00:04:23,023 >> Offline mode: forcing local_files_only=True
[INFO|configuration_utils.py:584] 2021-10-10 00:04:23,024 >> loading configuration file https://huggingface.co/gpt2-xl/resolve/main/config.json from cache at /home/user/.cache/huggingface/transformers/d2de8fec009fa9b9196047559bcac6c1f02a9c500718b4346bc516354965b1ca.d684cb2afa3f8c44c73bd67537d9aa5ff6044658793e077d7306ef2e37dd79bd
[INFO|configuration_utils.py:621] 2021-10-10 00:04:23,025 >> Model config GPT2Config {
"activation_function": "gelu_new",
"architectures": [
"GPT2LMHeadModel"
],
"attn_pdrop": 0.1,
"bos_token_id": 50256,
"embd_pdrop": 0.1,
"eos_token_id": 50256,
"initializer_range": 0.02,
"layer_norm_epsilon": 1e-05,
"model_type": "gpt2",
"n_ctx": 1024,
"n_embd": 1600,
"n_head": 25,
"n_inner": null,
"n_layer": 48,
"n_positions": 1024,
"output_past": true,
"reorder_and_upcast_attn": false,
"resid_pdrop": 0.1,
"scale_attn_by_inverse_layer_idx": false,
"scale_attn_weights": true,
"summary_activation": null,
"summary_first_dropout": 0.1,
"summary_proj_to_labels": true,
"summary_type": "cls_index",
"summary_use_proj": true,
"task_specific_params": {
"text-generation": {
"do_sample": true,
"max_length": 50
}
},
"transformers_version": "4.12.0.dev0",
"use_cache": true,
"vocab_size": 50257
}

10/10/2021 00:04:23 - WARNING - datasets.builder - Reusing dataset csv (/home/user/.cache/huggingface/datasets/csv/default-9dc66b5cf9d5f9f5/0.0.0/9144e0a4e8435090117cea53e6c7537173ef2304525df4a077c435d8ee7828ff)
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[INFO|modeling_utils.py:1225] 2021-10-10 00:04:23,138 >> Offline mode: forcing local_files_only=True
[INFO|modeling_utils.py:1324] 2021-10-10 00:04:23,139 >> loading weights file https://huggingface.co/gpt2-xl/resolve/main/pytorch_model.bin from cache at /home/user/.cache/huggingface/transformers/96569b907e56747ce3e593c6a13d8475b8c733a64aab8af8f602b90d94c4af71.8fbbcdf404c82c5967934d411f1462fa0574d639f2aa398aa3754fced1bb26c0
[INFO|modeling_utils.py:1589] 2021-10-10 00:04:45,762 >> All model checkpoint weights were used when initializing GPT2LMHeadModel.

[INFO|modeling_utils.py:1597] 2021-10-10 00:04:45,763 >> All the weights of GPT2LMHeadModel were initialized from the model checkpoint at gpt2-xl.
If your task is similar to the task the model of the checkpoint was trained on, you can already use GPT2LMHeadModel for predictions without further training.
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[INFO|trainer.py:434] 2021-10-10 00:05:05,020 >> Using amp fp16 backend
[2021-10-10 00:05:05,026] [INFO] [logging.py:68:log_dist] [Rank 0] DeepSpeed info: version=0.5.5+cd7967d, git-hash=cd7967d, git-branch=master
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[2021-10-10 00:05:14,451] [INFO] [logging.py:68:log_dist] [Rank 0] initializing deepspeed groups
[2021-10-10 00:05:14,451] [INFO] [logging.py:68:log_dist] [Rank 0] initializing deepspeed model parallel group with size 1
[2021-10-10 00:05:15,992] [INFO] [logging.py:68:log_dist] [Rank 0] initializing deepspeed expert parallel group with size 1
[2021-10-10 00:05:16,003] [INFO] [logging.py:68:log_dist] [Rank 0] creating expert data parallel process group with ranks: [0, 1, 2, 3, 4, 5, 6, 7]
[2021-10-10 00:05:16,014] [INFO] [logging.py:68:log_dist] [Rank 0] creating expert parallel process group with ranks: [0]
[2021-10-10 00:05:16,024] [INFO] [logging.py:68:log_dist] [Rank 0] creating expert parallel process group with ranks: [1]
[2021-10-10 00:05:16,025] [INFO] [logging.py:68:log_dist] [Rank 0] creating expert parallel process group with ranks: [2]
[2021-10-10 00:05:16,035] [INFO] [logging.py:68:log_dist] [Rank 0] creating expert parallel process group with ranks: [3]
[2021-10-10 00:05:16,046] [INFO] [logging.py:68:log_dist] [Rank 0] creating expert parallel process group with ranks: [4]
[2021-10-10 00:05:16,057] [INFO] [logging.py:68:log_dist] [Rank 0] creating expert parallel process group with ranks: [5]
[2021-10-10 00:05:16,057] [INFO] [logging.py:68:log_dist] [Rank 0] creating expert parallel process group with ranks: [6]
[2021-10-10 00:05:16,068] [INFO] [logging.py:68:log_dist] [Rank 0] creating expert parallel process group with ranks: [7]
[2021-10-10 00:05:18,134] [INFO] [engine.py:204:init] DeepSpeed Flops Profiler Enabled: False
Using /home/user/.cache/torch_extensions as PyTorch extensions root...
Using /home/user/.cache/torch_extensions as PyTorch extensions root...
Using /home/user/.cache/torch_extensions as PyTorch extensions root...
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Detected CUDA files, patching ldflags
Emitting ninja build file /home/user/.cache/torch_extensions/fused_adam/build.ninja...
Building extension module fused_adam...
Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)
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Loading extension module fused_adam...
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[2021-10-10 00:05:20,163] [INFO] [engine.py:862:_configure_optimizer] Using DeepSpeed Optimizer param name adamw as basic optimizer
Loading extension module fused_adam...
Time to load fused_adam op: 0.904491662979126 seconds
[2021-10-10 00:05:20,215] [INFO] [engine.py:870:_configure_optimizer] DeepSpeed Basic Optimizer = FusedAdam
[2021-10-10 00:05:20,215] [INFO] [utils.py:43:is_zero_supported_optimizer] Checking ZeRO support for optimizer=FusedAdam type=<class 'deepspeed.ops.adam.fused_adam.FusedAdam'>
[2021-10-10 00:05:20,215] [INFO] [logging.py:68:log_dist] [Rank 0] Creating fp16 ZeRO stage 2 optimizer
[2021-10-10 00:05:20,215] [INFO] [stage2.py:111:init] Reduce bucket size 500000000.0
[2021-10-10 00:05:20,215] [INFO] [stage2.py:112:init] Allgather bucket size 500000000.0
[2021-10-10 00:05:20,215] [INFO] [stage2.py:113:init] CPU Offload: False
[2021-10-10 00:05:20,215] [INFO] [stage2.py:114:init] Round robin gradient partitioning: False
Using /home/user/.cache/torch_extensions as PyTorch extensions root...
Loading extension module fused_adam...
Time to load fused_adam op: 0.9040207862854004 seconds
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Loading extension module fused_adam...
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Using /home/user/.cache/torch_extensions as PyTorch extensions root...
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Emitting ninja build file /home/user/.cache/torch_extensions/utils/build.ninja...
Building extension module utils...
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Rank: 4 partition count [8] and sizes[(194701400, False)]
[W ProcessGroupNCCL.cpp:1569] Rank 4 using best-guess GPU 4 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device.
Rank: 5 partition count [8] and sizes[(194701400, False)]
[W ProcessGroupNCCL.cpp:1569] Rank 5 using best-guess GPU 5 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device.
Rank: 0 partition count [8] and sizes[(194701400, False)]
[W ProcessGroupNCCL.cpp:1569] Rank 0 using best-guess GPU 0 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device.
Rank: 3 partition count [8] and sizes[(194701400, False)]
[W ProcessGroupNCCL.cpp:1569] Rank 3 using best-guess GPU 3 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device.
Rank: 6 partition count [8] and sizes[(194701400, False)]
[W ProcessGroupNCCL.cpp:1569] Rank 6 using best-guess GPU 6 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device.
Rank: 2 partition count [8] and sizes[(194701400, False)]
[W ProcessGroupNCCL.cpp:1569] Rank 2 using best-guess GPU 2 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device.
Rank: 1 partition count [8] and sizes[(194701400, False)]
[W ProcessGroupNCCL.cpp:1569] Rank 1 using best-guess GPU 1 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device.
Rank: 7 partition count [8] and sizes[(194701400, False)]
[W ProcessGroupNCCL.cpp:1569] Rank 7 using best-guess GPU 7 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device.
Using /home/user/.cache/torch_extensions as PyTorch extensions root...
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[2021-10-10 00:05:29,913] [INFO] [utils.py:806:see_memory_usage] Before initializing optimizer states
[2021-10-10 00:05:29,913] [INFO] [utils.py:807:see_memory_usage] MA 3.67 GB Max_MA 4.04 GB CA 7.03 GB Max_CA 7 GB
[2021-10-10 00:05:29,914] [INFO] [utils.py:815:see_memory_usage] CPU Virtual Memory: used = 67.33 GB, percent = 13.4%
[2021-10-10 00:05:29,958] [INFO] [utils.py:806:see_memory_usage] After initializing optimizer states
[2021-10-10 00:05:29,959] [INFO] [utils.py:807:see_memory_usage] MA 5.12 GB Max_MA 5.85 GB CA 9.21 GB Max_CA 9 GB
[2021-10-10 00:05:29,959] [INFO] [utils.py:815:see_memory_usage] CPU Virtual Memory: used = 67.33 GB, percent = 13.4%
[2021-10-10 00:05:29,959] [INFO] [stage2.py:474:init] optimizer state initialized
[2021-10-10 00:05:29,992] [INFO] [utils.py:806:see_memory_usage] After initializing ZeRO optimizer
[2021-10-10 00:05:29,992] [INFO] [utils.py:807:see_memory_usage] MA 5.12 GB Max_MA 5.12 GB CA 9.21 GB Max_CA 9 GB
[2021-10-10 00:05:29,993] [INFO] [utils.py:815:see_memory_usage] CPU Virtual Memory: used = 67.33 GB, percent = 13.4%
[2021-10-10 00:05:29,993] [INFO] [logging.py:68:log_dist] [Rank 0] DeepSpeed Final Optimizer = adamw
[2021-10-10 00:05:29,993] [INFO] [engine.py:586:_configure_lr_scheduler] DeepSpeed using configured LR scheduler = WarmupLR
[2021-10-10 00:05:29,993] [INFO] [logging.py:68:log_dist] [Rank 0] DeepSpeed LR Scheduler = <deepspeed.runtime.lr_schedules.WarmupLR object at 0x7fed99e7b520>
[2021-10-10 00:05:29,993] [INFO] [logging.py:68:log_dist] [Rank 0] step=0, skipped=0, lr=[5e-06], mom=[[0.9, 0.999]]
[2021-10-10 00:05:29,993] [INFO] [config.py:940:print] DeepSpeedEngine configuration:
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] activation_checkpointing_config {
"partition_activations": false,
"contiguous_memory_optimization": false,
"cpu_checkpointing": false,
"number_checkpoints": null,
"synchronize_checkpoint_boundary": false,
"profile": false
}
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] aio_config ................... {'block_size': 1048576, 'queue_depth': 8, 'thread_count': 1, 'single_submit': False, 'overlap_events': True}
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] allreduce_always_fp32 ........ False
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] amp_enabled .................. False
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] amp_params ................... False
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] checkpoint_tag_validation_enabled True
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] checkpoint_tag_validation_fail False
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] curriculum_enabled ........... False
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] curriculum_params ............ False
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] dataloader_drop_last ......... False
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] disable_allgather ............ False
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] dump_state ................... False
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] dynamic_loss_scale_args ...... {'init_scale': 65536, 'scale_window': 1000, 'delayed_shift': 2, 'min_scale': 1}
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] eigenvalue_enabled ........... False
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] eigenvalue_gas_boundary_resolution 1
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] eigenvalue_layer_name ........ bert.encoder.layer
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] eigenvalue_layer_num ......... 0
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] eigenvalue_max_iter .......... 100
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] eigenvalue_stability ......... 1e-06
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] eigenvalue_tol ............... 0.01
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] eigenvalue_verbose ........... False
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] elasticity_enabled ........... False
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] flops_profiler_config ........ {
"enabled": false,
"profile_step": 1,
"module_depth": -1,
"top_modules": 1,
"detailed": true,
"output_file": null
}
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] fp16_enabled ................. True
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] fp16_master_weights_and_gradients False
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] fp16_mixed_quantize .......... False
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] global_rank .................. 0
[2021-10-10 00:05:29,994] [INFO] [config.py:944:print] gradient_accumulation_steps .. 2
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] gradient_clipping ............ 1.0
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] gradient_predivide_factor .... 1.0
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] initial_dynamic_scale ........ 65536
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] loss_scale ................... 0
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] memory_breakdown ............. False
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] optimizer_legacy_fusion ...... False
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] optimizer_name ............... adamw
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] optimizer_params ............. {'lr': 5e-06, 'betas': [0.9, 0.999], 'eps': 1e-08, 'weight_decay': 0.0}
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] pipeline ..................... {'stages': 'auto', 'partition': 'best', 'seed_layers': False, 'activation_checkpoint_interval': 0}
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] pld_enabled .................. False
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] pld_params ................... False
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] prescale_gradients ........... False
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] quantize_change_rate ......... 0.001
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] quantize_groups .............. 1
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] quantize_offset .............. 1000
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] quantize_period .............. 1000
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] quantize_rounding ............ 0
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] quantize_start_bits .......... 16
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] quantize_target_bits ......... 8
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] quantize_training_enabled .... False
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] quantize_type ................ 0
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] quantize_verbose ............. False
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] scheduler_name ............... WarmupLR
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] scheduler_params ............. {'warmup_min_lr': 0, 'warmup_max_lr': 5e-06, 'warmup_num_steps': 10}
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] sparse_attention ............. None
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] sparse_gradients_enabled ..... False
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] steps_per_print .............. 2000
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] tensorboard_enabled .......... False
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] tensorboard_job_name ......... DeepSpeedJobName
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] tensorboard_output_path ......
[2021-10-10 00:05:29,995] [INFO] [config.py:944:print] train_batch_size ............. 16
[2021-10-10 00:05:29,996] [INFO] [config.py:944:print] train_micro_batch_size_per_gpu 1
[2021-10-10 00:05:29,996] [INFO] [config.py:944:print] use_quantizer_kernel ......... False
[2021-10-10 00:05:29,996] [INFO] [config.py:944:print] wall_clock_breakdown ......... False
[2021-10-10 00:05:29,996] [INFO] [config.py:944:print] world_size ................... 8
[2021-10-10 00:05:29,996] [INFO] [config.py:944:print] zero_allow_untested_optimizer False
[2021-10-10 00:05:29,996] [INFO] [config.py:944:print] zero_config .................. {
"stage": 2,
"contiguous_gradients": true,
"reduce_scatter": true,
"reduce_bucket_size": 5.000000e+08,
"allgather_partitions": true,
"allgather_bucket_size": 5.000000e+08,
"overlap_comm": true,
"load_from_fp32_weights": true,
"elastic_checkpoint": true,
"offload_param": null,
"offload_optimizer": null,
"sub_group_size": 1.000000e+09,
"prefetch_bucket_size": 5.000000e+07,
"param_persistence_threshold": 1.000000e+05,
"max_live_parameters": 1.000000e+09,
"max_reuse_distance": 1.000000e+09,
"gather_fp16_weights_on_model_save": false,
"ignore_unused_parameters": true,
"round_robin_gradients": false,
"legacy_stage1": false
}
[2021-10-10 00:05:29,996] [INFO] [config.py:944:print] zero_enabled ................. True
[2021-10-10 00:05:29,996] [INFO] [config.py:944:print] zero_optimization_stage ...... 2
[2021-10-10 00:05:29,996] [INFO] [config.py:946:print] json = {
"fp16": {
"enabled": true,
"loss_scale": 0,
"loss_scale_window": 1000,
"initial_scale_power": 16,
"hysteresis": 2,
"min_loss_scale": 1
},
"optimizer": {
"type": "AdamW",
"params": {
"lr": 5e-06,
"betas": [0.9, 0.999],
"eps": 1e-08,
"weight_decay": 0.0
}
},
"scheduler": {
"type": "WarmupLR",
"params": {
"warmup_min_lr": 0,
"warmup_max_lr": 5e-06,
"warmup_num_steps": 10
}
},
"zero_optimization": {
"stage": 2,
"allgather_partitions": true,
"allgather_bucket_size": 5.000000e+08,
"overlap_comm": true,
"reduce_scatter": true,
"reduce_bucket_size": 5.000000e+08,
"contiguous_gradients": true,
"cpu_offload": false
},
"gradient_accumulation_steps": 2,
"gradient_clipping": 1.0,
"steps_per_print": 2.000000e+03,
"train_batch_size": 16,
"train_micro_batch_size_per_gpu": 1,
"wall_clock_breakdown": false
}
Using /home/user/.cache/torch_extensions as PyTorch extensions root...
No modifications detected for re-loaded extension module utils, skipping build step...
Loading extension module utils...
Time to load utils op: 0.0005140304565429688 seconds
[INFO|trainer.py:1196] 2021-10-10 00:05:29,997 >> ***** Running training *****
[INFO|trainer.py:1197] 2021-10-10 00:05:29,997 >> Num examples = 1081
[INFO|trainer.py:1198] 2021-10-10 00:05:29,997 >> Num Epochs = 1
[INFO|trainer.py:1199] 2021-10-10 00:05:29,997 >> Instantaneous batch size per device = 1
[INFO|trainer.py:1200] 2021-10-10 00:05:29,997 >> Total train batch size (w. parallel, distributed & accumulation) = 16
[INFO|trainer.py:1201] 2021-10-10 00:05:29,997 >> Gradient Accumulation steps = 2
[INFO|trainer.py:1202] 2021-10-10 00:05:29,997 >> Total optimization steps = 68
22%|█████████▍ | 15/68 [00:15<00:53, 1.00s/it][INFO|trainer.py:2243] 2021-10-10 00:05:45,547 >> ***** Running Evaluation *****
[INFO|trainer.py:2245] 2021-10-10 00:05:45,547 >> Num examples = 274
[INFO|trainer.py:2248] 2021-10-10 00:05:45,547 >> Batch size = 8
{'eval_loss': 3.603515625, 'eval_runtime': 4.5688, 'eval_samples_per_second': 59.972, 'eval_steps_per_second': 1.094, 'epoch': 0.22}
44%|██████████████████▉ | 30/68 [00:35<00:38, 1.02s/it][INFO|trainer.py:2243] 2021-10-10 00:06:05,226 >> ***** Running Evaluation *****
[INFO|trainer.py:2245] 2021-10-10 00:06:05,226 >> Num examples = 274
[INFO|trainer.py:2248] 2021-10-10 00:06:05,226 >> Batch size = 8
{'eval_loss': 3.2109375, 'eval_runtime': 4.586, 'eval_samples_per_second': 59.747, 'eval_steps_per_second': 1.09, 'epoch': 0.44}
66%|████████████████████████████▍ | 45/68 [00:54<00:23, 1.02s/it][INFO|trainer.py:2243] 2021-10-10 00:06:24,942 >> ***** Running Evaluation *****
[INFO|trainer.py:2245] 2021-10-10 00:06:24,942 >> Num examples = 274
[INFO|trainer.py:2248] 2021-10-10 00:06:24,942 >> Batch size = 8
{'eval_loss': 3.046875, 'eval_runtime': 4.6037, 'eval_samples_per_second': 59.517, 'eval_steps_per_second': 1.086, 'epoch': 0.66}
88%|█████████████████████████████████████▉ | 60/68 [01:14<00:08, 1.02s/it][INFO|trainer.py:2243] 2021-10-10 00:06:44,684 >> ***** Running Evaluation *****
[INFO|trainer.py:2245] 2021-10-10 00:06:44,684 >> Num examples = 274
[INFO|trainer.py:2248] 2021-10-10 00:06:44,684 >> Batch size = 8
{'eval_loss': 2.966796875, 'eval_runtime': 4.6098, 'eval_samples_per_second': 59.438, 'eval_steps_per_second': 1.085, 'epoch': 0.88}
99%|██████████████████████████████████████████▎| 67/68 [01:26<00:01, 1.17s/it]
...
Training completed. Do not forget to share your model on huggingface.co/models =)

{'train_runtime': 87.3723, 'train_samples_per_second': 12.372, 'train_steps_per_second': 0.778, 'train_loss': 3.9335650275735294, 'epoch': 1.0}
100%|███████████████████████████████████████████| 68/68 [01:27<00:00, 1.28s/it]
[INFO|trainer.py:1995] 2021-10-10 00:06:57,382 >> Saving model checkpoint to finetuned
[INFO|configuration_utils.py:413] 2021-10-10 00:06:57,383 >> Configuration saved in finetuned/config.json
[INFO|modeling_utils.py:1041] 2021-10-10 00:07:12,168 >> Model weights saved in finetuned/pytorch_model.bin
[INFO|tokenization_utils_base.py:2034] 2021-10-10 00:07:12,169 >> tokenizer config file saved in finetuned/tokenizer_config.json
[INFO|tokenization_utils_base.py:2040] 2021-10-10 00:07:12,170 >> Special tokens file saved in finetuned/special_tokens_map.json
***** train metrics *****
epoch = 1.0
train_loss = 3.9336
train_runtime = 0:01:27.37
train_samples = 1081
train_samples_per_second = 12.372
train_steps_per_second = 0.778
10/10/2021 00:07:12 - INFO - main - *** Evaluate ***
[INFO|trainer.py:2243] 2021-10-10 00:07:12,291 >> ***** Running Evaluation *****
[INFO|trainer.py:2245] 2021-10-10 00:07:12,291 >> Num examples = 274
[INFO|trainer.py:2248] 2021-10-10 00:07:12,291 >> Batch size = 8
100%|█████████████████████████████████████████████| 5/5 [00:04<00:00, 1.18it/s]
***** eval metrics *****
epoch = 1.0
eval_loss = 2.9434
eval_runtime = 0:00:04.59
eval_samples = 274
eval_samples_per_second = 59.676
eval_steps_per_second = 1.089
perplexity = 18.9795
(gpt) user@user-X9DRG-HF:~/transformers/Finetune_GPTNEO_GPTJ6B/finetuning_repo$

pip install deepspeed
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