experiments/gpt2-hf-ds/hf_ds_gpt2_perf_n16_bs4-mbs8.out

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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. 
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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. 
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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. 
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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. 
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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. 
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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. 
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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. 
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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. 
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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. 
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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. 
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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. 
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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. 
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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. 
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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. 
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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. 
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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. 
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[2021-05-26 04:37:41,622] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
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nn.functional.linear has been overridden with a more memory efficient version. This will persist unless manually reset.
[2021-05-26 04:37:51,493] [INFO] [logging.py:60:log_dist] [Rank 0] DeepSpeed info: version=0.3.17+unknown, git-hash=unknown, git-branch=unknown
[2021-05-26 04:37:51,549] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
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[2021-05-26 04:37:52,017] [INFO] [engine.py:164:__init__] DeepSpeed Flops Profiler Enabled: False
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
[2021-05-26 04:37:53,035] [INFO] [engine.py:636:_configure_optimizer] Using DeepSpeed Optimizer param name adamw as basic optimizer
[2021-05-26 04:37:53,035] [INFO] [engine.py:641:_configure_optimizer] DeepSpeed Basic Optimizer = DeepSpeedCPUAdam
Checking ZeRO support for optimizer=DeepSpeedCPUAdam type=<class 'deepspeed.ops.adam.cpu_adam.DeepSpeedCPUAdam'>
[2021-05-26 04:37:53,035] [INFO] [logging.py:60:log_dist] [Rank 0] Creating fp16 ZeRO stage 3 optimizer
Initializing ZeRO Stage 3
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
[2021-05-26 04:37:53,113] [INFO] [utils.py:588:see_memory_usage] Stage 3 initialize beginning
[2021-05-26 04:37:53,114] [INFO] [utils.py:589:see_memory_usage] MA 2.34 GB         Max_MA 3.81 GB         CA 5.4 GB         Max_CA 5 GB 
[2021-05-26 04:37:53,115] [INFO] [utils.py:597:see_memory_usage] CPU Virtual Memory:  used = 40.02 GB, percent = 21.4%
[2021-05-26 04:37:53,115] [INFO] [stage3.py:624:__init__] Reduce bucket size 67108864
[2021-05-26 04:37:53,115] [INFO] [stage3.py:625:__init__] Allgather bucket size 60397977.6
[2021-05-26 04:37:53,128] [INFO] [stage3.py:39:print_rank_0] FP16 params swapping is False, Max params in CPU is 1000000000.0
[2021-05-26 04:37:53,191] [INFO] [utils.py:588:see_memory_usage] Before creating fp16 partitions
[2021-05-26 04:37:53,192] [INFO] [utils.py:589:see_memory_usage] MA 2.34 GB         Max_MA 2.34 GB         CA 5.4 GB         Max_CA 5 GB 
[2021-05-26 04:37:53,192] [INFO] [utils.py:597:see_memory_usage] CPU Virtual Memory:  used = 40.02 GB, percent = 21.4%
[2021-05-26 04:37:54,059] [INFO] [stage3.py:39:print_rank_0] fp16 group 0 has 1 subgroups
[2021-05-26 04:37:55,731] [INFO] [stage3.py:39:print_rank_0] Swappable FP32 Partitions: count=0 size= 0.00 GB
[2021-05-26 04:37:55,731] [INFO] [stage3.py:39:print_rank_0] In-Memory FP32 Partitions: count=1 size= 3.02 GB
[2021-05-26 04:38:02,821] [INFO] [stage3.py:819:__init__] optimizer state initialized
[2021-05-26 04:38:02,822] [INFO] [stage3.py:39:print_rank_0] Largest partitioned param numel = 811977088
[2021-05-26 04:38:20,030] [INFO] [utils.py:588:see_memory_usage] After initializing ZeRO optimizer
[2021-05-26 04:38:20,031] [INFO] [utils.py:589:see_memory_usage] MA 3.09 GB         Max_MA 4.09 GB         CA 6.92 GB         Max_CA 7 GB 
[2021-05-26 04:38:20,031] [INFO] [utils.py:597:see_memory_usage] CPU Virtual Memory:  used = 94.98 GB, percent = 50.7%
[2021-05-26 04:38:20,031] [INFO] [logging.py:60:log_dist] [Rank 0] DeepSpeed Final Optimizer = adamw
[2021-05-26 04:38:20,031] [INFO] [engine.py:449:_configure_lr_scheduler] DeepSpeed using configured LR scheduler = WarmupLR
[2021-05-26 04:38:20,031] [INFO] [logging.py:60:log_dist] [Rank 0] DeepSpeed LR Scheduler = <deepspeed.runtime.lr_schedules.WarmupLR object at 0x14b579df9a00>
[2021-05-26 04:38:20,031] [INFO] [logging.py:60:log_dist] [Rank 0] step=0, skipped=0, lr=[5e-05], mom=[[0.9, 0.999]]
[2021-05-26 04:38:20,031] [INFO] [config.py:748:print] DeepSpeedEngine configuration:
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   activation_checkpointing_config  {
    "partition_activations": false, 
    "contiguous_memory_optimization": false, 
    "cpu_checkpointing": false, 
    "number_checkpoints": null, 
    "synchronize_checkpoint_boundary": false, 
    "profile": false
}
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   aio_config ................... {'block_size': 1048576, 'queue_depth': 8, 'thread_count': 1, 'single_submit': False, 'overlap_events': True}
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   allreduce_always_fp32 ........ False
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   amp_enabled .................. False
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   amp_params ................... False
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   checkpoint_tag_validation_enabled  True
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   checkpoint_tag_validation_fail  False
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   disable_allgather ............ False
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   dump_state ................... False
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   dynamic_loss_scale_args ...... {'init_scale': 256, 'scale_window': 1000, 'delayed_shift': 2, 'min_scale': 1}
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   elasticity_enabled ........... False
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   flops_profiler_config ........ {
    "enabled": false, 
    "profile_step": 1, 
    "module_depth": -1, 
    "top_modules": 1, 
    "detailed": true, 
    "output_file": null
}
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   fp16_enabled ................. True
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   global_rank .................. 0
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   gradient_accumulation_steps .. 1
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   gradient_clipping ............ 1.0
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   gradient_predivide_factor .... 1.0
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   initial_dynamic_scale ........ 256
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   loss_scale ................... 0
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   memory_breakdown ............. False
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   optimizer_legacy_fusion ...... False
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   optimizer_name ............... adamw
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   optimizer_params ............. {'lr': 5e-05, 'betas': [0.9, 0.999], 'eps': 1e-08, 'weight_decay': 0.0}
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   pipeline ..................... {'stages': 'auto', 'partition': 'best', 'seed_layers': False, 'activation_checkpoint_interval': 0}
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   pld_enabled .................. False
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   pld_params ................... False
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   prescale_gradients ........... False
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   scheduler_name ............... WarmupLR
[2021-05-26 04:38:20,032] [INFO] [config.py:752:print]   scheduler_params ............. {'warmup_min_lr': 0, 'warmup_max_lr': 5e-05, 'warmup_num_steps': 8}
[2021-05-26 04:38:20,033] [INFO] [config.py:752:print]   sparse_attention ............. None
[2021-05-26 04:38:20,033] [INFO] [config.py:752:print]   sparse_gradients_enabled ..... False
[2021-05-26 04:38:20,033] [INFO] [config.py:752:print]   steps_per_print .............. 2000
[2021-05-26 04:38:20,033] [INFO] [config.py:752:print]   tensorboard_enabled .......... False
[2021-05-26 04:38:20,033] [INFO] [config.py:752:print]   tensorboard_job_name ......... DeepSpeedJobName
[2021-05-26 04:38:20,033] [INFO] [config.py:752:print]   tensorboard_output_path ...... 
[2021-05-26 04:38:20,033] [INFO] [config.py:752:print]   train_batch_size ............. 2048
[2021-05-26 04:38:20,033] [INFO] [config.py:752:print]   train_micro_batch_size_per_gpu  32
[2021-05-26 04:38:20,033] [INFO] [config.py:752:print]   wall_clock_breakdown ......... False
[2021-05-26 04:38:20,033] [INFO] [config.py:752:print]   world_size ................... 64
[2021-05-26 04:38:20,033] [INFO] [config.py:752:print]   zero_allow_untested_optimizer  False
[2021-05-26 04:38:20,033] [INFO] [config.py:752:print]   zero_config .................. {
    "stage": 3, 
    "contiguous_gradients": true, 
    "reduce_scatter": false, 
    "reduce_bucket_size": 6.710886e+07, 
    "allgather_partitions": true, 
    "allgather_bucket_size": 5.000000e+08, 
    "overlap_comm": true, 
    "load_from_fp32_weights": true, 
    "elastic_checkpoint": true, 
    "offload_param": {
        "device": "cpu", 
        "nvme_path": null, 
        "buffer_count": 5, 
        "buffer_size": 1.000000e+08, 
        "max_in_cpu": 1.000000e+09, 
        "pin_memory": true
    }, 
    "offload_optimizer": {
        "device": "cpu", 
        "nvme_path": null, 
        "buffer_count": 4, 
        "pin_memory": true, 
        "pipeline_read": false, 
        "pipeline_write": false, 
        "fast_init": false, 
        "pipeline": false
    }, 
    "sub_group_size": 1.000000e+14, 
    "prefetch_bucket_size": 6.039798e+07, 
    "param_persistence_threshold": 8.192000e+04, 
    "max_live_parameters": 1.000000e+09, 
    "max_reuse_distance": 1.000000e+09, 
    "gather_fp16_weights_on_model_save": false, 
    "ignore_unused_parameters": true
}
[2021-05-26 04:38:20,033] [INFO] [config.py:752:print]   zero_enabled ................. True
[2021-05-26 04:38:20,033] [INFO] [config.py:752:print]   zero_optimization_stage ...... 3
[2021-05-26 04:38:20,033] [INFO] [config.py:754:print]   json = {
    "fp16": {
        "enabled": true, 
        "loss_scale": 0, 
        "loss_scale_window": 1000, 
        "initial_scale_power": 8, 
        "hysteresis": 2, 
        "min_loss_scale": 1
    }, 
    "optimizer": {
        "type": "AdamW", 
        "params": {
            "lr": 5e-05, 
            "betas": [0.9, 0.999], 
            "eps": 1e-08, 
            "weight_decay": 0.0
        }
    }, 
    "scheduler": {
        "type": "WarmupLR", 
        "params": {
            "warmup_min_lr": 0, 
            "warmup_max_lr": 5e-05, 
            "warmup_num_steps": 8
        }
    }, 
    "zero_optimization": {
        "stage": 3, 
        "offload_optimizer": {
            "device": "cpu", 
            "pin_memory": true
        }, 
        "offload_param": {
            "device": "cpu", 
            "pin_memory": true
        }, 
        "overlap_comm": true, 
        "contiguous_gradients": true, 
        "sub_group_size": 1.000000e+14, 
        "reduce_bucket_size": 6.710886e+07, 
        "stage3_prefetch_bucket_size": 6.039798e+07, 
        "stage3_param_persistence_threshold": 8.192000e+04, 
        "stage3_max_live_parameters": 1.000000e+09, 
        "stage3_max_reuse_distance": 1.000000e+09, 
        "stage3_gather_fp16_weights_on_model_save": false
    }, 
    "gradient_accumulation_steps": 1, 
    "gradient_clipping": 1.0, 
    "steps_per_print": 2.000000e+03, 
    "train_batch_size": 2.048000e+03, 
    "train_micro_batch_size_per_gpu": 32, 
    "wall_clock_breakdown": false
}
Killing subprocess 22920
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*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
[2021-05-26 04:40:19,839] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:19,839] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,034] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,036] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,052] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,053] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,057] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,059] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,063] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,072] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
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[2021-05-26 04:40:20,124] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,125] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
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[2021-05-26 04:40:20,129] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
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[2021-05-26 04:40:20,141] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,143] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,143] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,144] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,153] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,153] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,202] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,205] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,211] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,215] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,216] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,229] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,239] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,239] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,415] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,418] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,427] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:20,433] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:21,852] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:21,856] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:22,741] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:40:22,761] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
nn.functional.linear has been overridden with a more memory efficient version. This will persist unless manually reset.
[2021-05-26 04:40:28,842] [INFO] [logging.py:60:log_dist] [Rank 0] DeepSpeed info: version=0.3.17+unknown, git-hash=unknown, git-branch=unknown
[2021-05-26 04:40:28,940] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,940] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,945] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,946] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,946] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,946] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,946] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,947] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,947] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,947] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,947] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,947] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,947] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,947] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,948] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,948] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,949] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,949] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,949] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,950] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,950] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,950] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,950] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,951] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,951] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,951] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,951] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,952] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,952] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,952] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,952] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,953] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,953] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,953] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,953] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,953] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,954] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,954] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,954] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,954] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,954] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,954] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,954] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,955] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,955] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,955] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,956] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,956] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,956] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,957] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,957] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,957] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,958] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,958] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,958] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,958] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,959] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,960] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,960] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,960] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,960] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,961] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,961] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:28,963] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:40:29,315] [INFO] [engine.py:164:__init__] DeepSpeed Flops Profiler Enabled: False
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
[2021-05-26 04:40:30,228] [INFO] [engine.py:636:_configure_optimizer] Using DeepSpeed Optimizer param name adamw as basic optimizer
[2021-05-26 04:40:30,228] [INFO] [engine.py:641:_configure_optimizer] DeepSpeed Basic Optimizer = DeepSpeedCPUAdam
Checking ZeRO support for optimizer=DeepSpeedCPUAdam type=<class 'deepspeed.ops.adam.cpu_adam.DeepSpeedCPUAdam'>
[2021-05-26 04:40:30,228] [INFO] [logging.py:60:log_dist] [Rank 0] Creating fp16 ZeRO stage 3 optimizer
Initializing ZeRO Stage 3
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
[2021-05-26 04:40:30,309] [INFO] [utils.py:588:see_memory_usage] Stage 3 initialize beginning
[2021-05-26 04:40:30,311] [INFO] [utils.py:589:see_memory_usage] MA 2.34 GB         Max_MA 3.81 GB         CA 5.4 GB         Max_CA 5 GB 
[2021-05-26 04:40:30,311] [INFO] [utils.py:597:see_memory_usage] CPU Virtual Memory:  used = 40.02 GB, percent = 21.4%
[2021-05-26 04:40:30,311] [INFO] [stage3.py:624:__init__] Reduce bucket size 67108864
[2021-05-26 04:40:30,311] [INFO] [stage3.py:625:__init__] Allgather bucket size 60397977.6
[2021-05-26 04:40:30,325] [INFO] [stage3.py:39:print_rank_0] FP16 params swapping is False, Max params in CPU is 1000000000.0
[2021-05-26 04:40:30,392] [INFO] [utils.py:588:see_memory_usage] Before creating fp16 partitions
[2021-05-26 04:40:30,392] [INFO] [utils.py:589:see_memory_usage] MA 2.34 GB         Max_MA 2.34 GB         CA 5.4 GB         Max_CA 5 GB 
[2021-05-26 04:40:30,393] [INFO] [utils.py:597:see_memory_usage] CPU Virtual Memory:  used = 40.02 GB, percent = 21.4%
[2021-05-26 04:40:31,251] [INFO] [stage3.py:39:print_rank_0] fp16 group 0 has 1 subgroups
[2021-05-26 04:40:32,871] [INFO] [stage3.py:39:print_rank_0] Swappable FP32 Partitions: count=0 size= 0.00 GB
[2021-05-26 04:40:32,871] [INFO] [stage3.py:39:print_rank_0] In-Memory FP32 Partitions: count=1 size= 3.02 GB
[2021-05-26 04:40:39,984] [INFO] [stage3.py:819:__init__] optimizer state initialized
[2021-05-26 04:40:39,984] [INFO] [stage3.py:39:print_rank_0] Largest partitioned param numel = 811977088
[2021-05-26 04:40:56,470] [INFO] [utils.py:588:see_memory_usage] After initializing ZeRO optimizer
[2021-05-26 04:40:56,471] [INFO] [utils.py:589:see_memory_usage] MA 3.09 GB         Max_MA 4.09 GB         CA 6.92 GB         Max_CA 7 GB 
[2021-05-26 04:40:56,471] [INFO] [utils.py:597:see_memory_usage] CPU Virtual Memory:  used = 94.99 GB, percent = 50.7%
[2021-05-26 04:40:56,472] [INFO] [logging.py:60:log_dist] [Rank 0] DeepSpeed Final Optimizer = adamw
[2021-05-26 04:40:56,472] [INFO] [engine.py:449:_configure_lr_scheduler] DeepSpeed using configured LR scheduler = WarmupLR
[2021-05-26 04:40:56,472] [INFO] [logging.py:60:log_dist] [Rank 0] DeepSpeed LR Scheduler = <deepspeed.runtime.lr_schedules.WarmupLR object at 0x15077cec1a00>
[2021-05-26 04:40:56,472] [INFO] [logging.py:60:log_dist] [Rank 0] step=0, skipped=0, lr=[5e-05], mom=[[0.9, 0.999]]
[2021-05-26 04:40:56,472] [INFO] [config.py:748:print] DeepSpeedEngine configuration:
[2021-05-26 04:40:56,472] [INFO] [config.py:752:print]   activation_checkpointing_config  {
    "partition_activations": false, 
    "contiguous_memory_optimization": false, 
    "cpu_checkpointing": false, 
    "number_checkpoints": null, 
    "synchronize_checkpoint_boundary": false, 
    "profile": false
}
[2021-05-26 04:40:56,472] [INFO] [config.py:752:print]   aio_config ................... {'block_size': 1048576, 'queue_depth': 8, 'thread_count': 1, 'single_submit': False, 'overlap_events': True}
[2021-05-26 04:40:56,472] [INFO] [config.py:752:print]   allreduce_always_fp32 ........ False
[2021-05-26 04:40:56,472] [INFO] [config.py:752:print]   amp_enabled .................. False
[2021-05-26 04:40:56,472] [INFO] [config.py:752:print]   amp_params ................... False
[2021-05-26 04:40:56,472] [INFO] [config.py:752:print]   checkpoint_tag_validation_enabled  True
[2021-05-26 04:40:56,472] [INFO] [config.py:752:print]   checkpoint_tag_validation_fail  False
[2021-05-26 04:40:56,472] [INFO] [config.py:752:print]   disable_allgather ............ False
[2021-05-26 04:40:56,472] [INFO] [config.py:752:print]   dump_state ................... False
[2021-05-26 04:40:56,472] [INFO] [config.py:752:print]   dynamic_loss_scale_args ...... {'init_scale': 256, 'scale_window': 1000, 'delayed_shift': 2, 'min_scale': 1}
[2021-05-26 04:40:56,472] [INFO] [config.py:752:print]   elasticity_enabled ........... False
[2021-05-26 04:40:56,472] [INFO] [config.py:752:print]   flops_profiler_config ........ {
    "enabled": false, 
    "profile_step": 1, 
    "module_depth": -1, 
    "top_modules": 1, 
    "detailed": true, 
    "output_file": null
}
[2021-05-26 04:40:56,472] [INFO] [config.py:752:print]   fp16_enabled ................. True
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   global_rank .................. 0
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   gradient_accumulation_steps .. 1
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   gradient_clipping ............ 1.0
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   gradient_predivide_factor .... 1.0
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   initial_dynamic_scale ........ 256
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   loss_scale ................... 0
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   memory_breakdown ............. False
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   optimizer_legacy_fusion ...... False
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   optimizer_name ............... adamw
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   optimizer_params ............. {'lr': 5e-05, 'betas': [0.9, 0.999], 'eps': 1e-08, 'weight_decay': 0.0}
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   pipeline ..................... {'stages': 'auto', 'partition': 'best', 'seed_layers': False, 'activation_checkpoint_interval': 0}
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   pld_enabled .................. False
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   pld_params ................... False
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   prescale_gradients ........... False
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   scheduler_name ............... WarmupLR
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   scheduler_params ............. {'warmup_min_lr': 0, 'warmup_max_lr': 5e-05, 'warmup_num_steps': 8}
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   sparse_attention ............. None
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   sparse_gradients_enabled ..... False
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   steps_per_print .............. 2000
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   tensorboard_enabled .......... False
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   tensorboard_job_name ......... DeepSpeedJobName
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   tensorboard_output_path ...... 
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   train_batch_size ............. 1024
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   train_micro_batch_size_per_gpu  16
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   wall_clock_breakdown ......... False
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   world_size ................... 64
[2021-05-26 04:40:56,473] [INFO] [config.py:752:print]   zero_allow_untested_optimizer  False
[2021-05-26 04:40:56,474] [INFO] [config.py:752:print]   zero_config .................. {
    "stage": 3, 
    "contiguous_gradients": true, 
    "reduce_scatter": false, 
    "reduce_bucket_size": 6.710886e+07, 
    "allgather_partitions": true, 
    "allgather_bucket_size": 5.000000e+08, 
    "overlap_comm": true, 
    "load_from_fp32_weights": true, 
    "elastic_checkpoint": true, 
    "offload_param": {
        "device": "cpu", 
        "nvme_path": null, 
        "buffer_count": 5, 
        "buffer_size": 1.000000e+08, 
        "max_in_cpu": 1.000000e+09, 
        "pin_memory": true
    }, 
    "offload_optimizer": {
        "device": "cpu", 
        "nvme_path": null, 
        "buffer_count": 4, 
        "pin_memory": true, 
        "pipeline_read": false, 
        "pipeline_write": false, 
        "fast_init": false, 
        "pipeline": false
    }, 
    "sub_group_size": 1.000000e+14, 
    "prefetch_bucket_size": 6.039798e+07, 
    "param_persistence_threshold": 8.192000e+04, 
    "max_live_parameters": 1.000000e+09, 
    "max_reuse_distance": 1.000000e+09, 
    "gather_fp16_weights_on_model_save": false, 
    "ignore_unused_parameters": true
}
[2021-05-26 04:40:56,474] [INFO] [config.py:752:print]   zero_enabled ................. True
[2021-05-26 04:40:56,474] [INFO] [config.py:752:print]   zero_optimization_stage ...... 3
[2021-05-26 04:40:56,474] [INFO] [config.py:754:print]   json = {
    "fp16": {
        "enabled": true, 
        "loss_scale": 0, 
        "loss_scale_window": 1000, 
        "initial_scale_power": 8, 
        "hysteresis": 2, 
        "min_loss_scale": 1
    }, 
    "optimizer": {
        "type": "AdamW", 
        "params": {
            "lr": 5e-05, 
            "betas": [0.9, 0.999], 
            "eps": 1e-08, 
            "weight_decay": 0.0
        }
    }, 
    "scheduler": {
        "type": "WarmupLR", 
        "params": {
            "warmup_min_lr": 0, 
            "warmup_max_lr": 5e-05, 
            "warmup_num_steps": 8
        }
    }, 
    "zero_optimization": {
        "stage": 3, 
        "offload_optimizer": {
            "device": "cpu", 
            "pin_memory": true
        }, 
        "offload_param": {
            "device": "cpu", 
            "pin_memory": true
        }, 
        "overlap_comm": true, 
        "contiguous_gradients": true, 
        "sub_group_size": 1.000000e+14, 
        "reduce_bucket_size": 6.710886e+07, 
        "stage3_prefetch_bucket_size": 6.039798e+07, 
        "stage3_param_persistence_threshold": 8.192000e+04, 
        "stage3_max_live_parameters": 1.000000e+09, 
        "stage3_max_reuse_distance": 1.000000e+09, 
        "stage3_gather_fp16_weights_on_model_save": false
    }, 
    "gradient_accumulation_steps": 1, 
    "gradient_clipping": 1.0, 
    "steps_per_print": 2.000000e+03, 
    "train_batch_size": 1.024000e+03, 
    "train_micro_batch_size_per_gpu": 16, 
    "wall_clock_breakdown": false
}
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*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
*****************************************
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. 
*****************************************
[2021-05-26 04:50:54,815] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,820] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,835] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,835] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,839] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,844] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,852] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,858] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,859] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,862] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,862] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,871] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,875] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,876] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,876] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,878] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,883] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,883] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,893] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,894] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,895] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,896] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,896] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,896] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,898] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,902] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,903] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,907] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,910] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,913] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,913] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,914] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,914] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,917] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,919] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,920] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,923] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,923] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,923] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,924] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,927] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,927] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,929] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,929] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,932] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,933] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,935] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,936] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,937] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,937] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,937] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,938] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,938] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,950] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,951] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,955] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,956] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,958] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:54,984] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:55,000] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:55,005] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:55,012] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:56,695] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
[2021-05-26 04:50:56,696] [INFO] [distributed.py:46:init_distributed] Initializing torch distributed with backend: nccl
nn.functional.linear has been overridden with a more memory efficient version. This will persist unless manually reset.
[2021-05-26 04:51:02,757] [INFO] [logging.py:60:log_dist] [Rank 0] DeepSpeed info: version=0.3.17+unknown, git-hash=unknown, git-branch=unknown
[2021-05-26 04:51:02,861] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,862] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,862] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,864] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,864] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,864] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,865] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,865] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,865] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,865] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,866] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,866] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,866] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,867] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,868] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,868] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,868] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,868] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,868] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,868] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,868] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,868] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,868] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,869] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,869] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,869] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,869] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,870] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,870] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,870] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,871] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,871] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,871] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,872] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,872] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,872] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,872] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,872] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,872] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,872] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,872] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,872] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,872] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,872] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,872] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,872] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,872] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,872] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,872] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,872] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,872] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,873] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,873] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,873] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,873] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,873] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,873] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,873] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,873] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,874] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,875] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,877] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,879] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:02,891] [INFO] [utils.py:11:_initialize_parameter_parallel_groups] data_parallel_size: 64, parameter_parallel_size: 64
[2021-05-26 04:51:03,229] [INFO] [engine.py:164:__init__] DeepSpeed Flops Profiler Enabled: False
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
[2021-05-26 04:51:04,136] [INFO] [engine.py:636:_configure_optimizer] Using DeepSpeed Optimizer param name adamw as basic optimizer
[2021-05-26 04:51:04,136] [INFO] [engine.py:641:_configure_optimizer] DeepSpeed Basic Optimizer = DeepSpeedCPUAdam
Checking ZeRO support for optimizer=DeepSpeedCPUAdam type=<class 'deepspeed.ops.adam.cpu_adam.DeepSpeedCPUAdam'>
[2021-05-26 04:51:04,136] [INFO] [logging.py:60:log_dist] [Rank 0] Creating fp16 ZeRO stage 3 optimizer
Initializing ZeRO Stage 3
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
[2021-05-26 04:51:04,212] [INFO] [utils.py:588:see_memory_usage] Stage 3 initialize beginning
[2021-05-26 04:51:04,213] [INFO] [utils.py:589:see_memory_usage] MA 2.34 GB         Max_MA 3.81 GB         CA 5.4 GB         Max_CA 5 GB 
[2021-05-26 04:51:04,213] [INFO] [utils.py:597:see_memory_usage] CPU Virtual Memory:  used = 40.07 GB, percent = 21.4%
[2021-05-26 04:51:04,213] [INFO] [stage3.py:624:__init__] Reduce bucket size 67108864
[2021-05-26 04:51:04,213] [INFO] [stage3.py:625:__init__] Allgather bucket size 60397977.6
Adam Optimizer #0 is created with AVX512 arithmetic capability.
Config: alpha=0.000050, betas=(0.900000, 0.999000), weight_decay=0.000000, adam_w=1
[2021-05-26 04:51:04,227] [INFO] [stage3.py:39:print_rank_0] FP16 params swapping is False, Max params in CPU is 1000000000.0
[2021-05-26 04:51:04,290] [INFO] [utils.py:588:see_memory_usage] Before creating fp16 partitions
[2021-05-26 04:51:04,291] [INFO] [utils.py:589:see_memory_usage] MA 2.34 GB         Max_MA 2.34 GB         CA 5.4 GB         Max_CA 5 GB 
[2021-05-26 04:51:04,291] [INFO] [utils.py:597:see_memory_usage] CPU Virtual Memory:  used = 40.07 GB, percent = 21.4%
[2021-05-26 04:51:05,151] [INFO] [stage3.py:39:print_rank_0] fp16 group 0 has 1 subgroups
[2021-05-26 04:51:06,824] [INFO] [stage3.py:39:print_rank_0] Swappable FP32 Partitions: count=0 size= 0.00 GB
[2021-05-26 04:51:06,824] [INFO] [stage3.py:39:print_rank_0] In-Memory FP32 Partitions: count=1 size= 3.02 GB
[2021-05-26 04:51:14,301] [INFO] [stage3.py:819:__init__] optimizer state initialized
[2021-05-26 04:51:14,302] [INFO] [stage3.py:39:print_rank_0] Largest partitioned param numel = 811977088
[2021-05-26 04:51:31,916] [INFO] [utils.py:588:see_memory_usage] After initializing ZeRO optimizer
[2021-05-26 04:51:31,917] [INFO] [utils.py:589:see_memory_usage] MA 3.09 GB         Max_MA 4.09 GB         CA 6.92 GB         Max_CA 7 GB 
[2021-05-26 04:51:31,917] [INFO] [utils.py:597:see_memory_usage] CPU Virtual Memory:  used = 95.03 GB, percent = 50.7%
[2021-05-26 04:51:31,918] [INFO] [logging.py:60:log_dist] [Rank 0] DeepSpeed Final Optimizer = adamw
[2021-05-26 04:51:31,918] [INFO] [engine.py:449:_configure_lr_scheduler] DeepSpeed using configured LR scheduler = WarmupLR
[2021-05-26 04:51:31,918] [INFO] [logging.py:60:log_dist] [Rank 0] DeepSpeed LR Scheduler = <deepspeed.runtime.lr_schedules.WarmupLR object at 0x149d553afa00>
[2021-05-26 04:51:31,918] [INFO] [logging.py:60:log_dist] [Rank 0] step=0, skipped=0, lr=[5e-05], mom=[[0.9, 0.999]]
[2021-05-26 04:51:31,918] [INFO] [config.py:748:print] DeepSpeedEngine configuration:
[2021-05-26 04:51:31,918] [INFO] [config.py:752:print]   activation_checkpointing_config  {
    "partition_activations": false, 
    "contiguous_memory_optimization": false, 
    "cpu_checkpointing": false, 
    "number_checkpoints": null, 
    "synchronize_checkpoint_boundary": false, 
    "profile": false
}
[2021-05-26 04:51:31,918] [INFO] [config.py:752:print]   aio_config ................... {'block_size': 1048576, 'queue_depth': 8, 'thread_count': 1, 'single_submit': False, 'overlap_events': True}
[2021-05-26 04:51:31,918] [INFO] [config.py:752:print]   allreduce_always_fp32 ........ False
[2021-05-26 04:51:31,918] [INFO] [config.py:752:print]   amp_enabled .................. False
[2021-05-26 04:51:31,918] [INFO] [config.py:752:print]   amp_params ................... False
[2021-05-26 04:51:31,918] [INFO] [config.py:752:print]   checkpoint_tag_validation_enabled  True
[2021-05-26 04:51:31,918] [INFO] [config.py:752:print]   checkpoint_tag_validation_fail  False
[2021-05-26 04:51:31,918] [INFO] [config.py:752:print]   disable_allgather ............ False
[2021-05-26 04:51:31,918] [INFO] [config.py:752:print]   dump_state ................... False
[2021-05-26 04:51:31,918] [INFO] [config.py:752:print]   dynamic_loss_scale_args ...... {'init_scale': 256, 'scale_window': 1000, 'delayed_shift': 2, 'min_scale': 1}
[2021-05-26 04:51:31,918] [INFO] [config.py:752:print]   elasticity_enabled ........... False
[2021-05-26 04:51:31,918] [INFO] [config.py:752:print]   flops_profiler_config ........ {
    "enabled": false, 
    "profile_step": 1, 
    "module_depth": -1, 
    "top_modules": 1, 
    "detailed": true, 
    "output_file": null
}
[2021-05-26 04:51:31,918] [INFO] [config.py:752:print]   fp16_enabled ................. True
[2021-05-26 04:51:31,918] [INFO] [config.py:752:print]   global_rank .................. 0
[2021-05-26 04:51:31,918] [INFO] [config.py:752:print]   gradient_accumulation_steps .. 1
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   gradient_clipping ............ 1.0
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   gradient_predivide_factor .... 1.0
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   initial_dynamic_scale ........ 256
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   loss_scale ................... 0
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   memory_breakdown ............. False
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   optimizer_legacy_fusion ...... False
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   optimizer_name ............... adamw
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   optimizer_params ............. {'lr': 5e-05, 'betas': [0.9, 0.999], 'eps': 1e-08, 'weight_decay': 0.0}
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   pipeline ..................... {'stages': 'auto', 'partition': 'best', 'seed_layers': False, 'activation_checkpoint_interval': 0}
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   pld_enabled .................. False
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   pld_params ................... False
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   prescale_gradients ........... False
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   scheduler_name ............... WarmupLR
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   scheduler_params ............. {'warmup_min_lr': 0, 'warmup_max_lr': 5e-05, 'warmup_num_steps': 8}
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   sparse_attention ............. None
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   sparse_gradients_enabled ..... False
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   steps_per_print .............. 2000
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   tensorboard_enabled .......... False
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   tensorboard_job_name ......... DeepSpeedJobName
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   tensorboard_output_path ...... 
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   train_batch_size ............. 512
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   train_micro_batch_size_per_gpu  8
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   wall_clock_breakdown ......... False
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   world_size ................... 64
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   zero_allow_untested_optimizer  False
[2021-05-26 04:51:31,919] [INFO] [config.py:752:print]   zero_config .................. {
    "stage": 3, 
    "contiguous_gradients": true, 
    "reduce_scatter": false, 
    "reduce_bucket_size": 6.710886e+07, 
    "allgather_partitions": true, 
    "allgather_bucket_size": 5.000000e+08, 
    "overlap_comm": true, 
    "load_from_fp32_weights": true, 
    "elastic_checkpoint": true, 
    "offload_param": {
        "device": "cpu", 
        "nvme_path": null, 
        "buffer_count": 5, 
        "buffer_size": 1.000000e+08, 
        "max_in_cpu": 1.000000e+09, 
        "pin_memory": true
    }, 
    "offload_optimizer": {
        "device": "cpu", 
        "nvme_path": null, 
        "buffer_count": 4, 
        "pin_memory": true, 
        "pipeline_read": false, 
        "pipeline_write": false, 
        "fast_init": false, 
        "pipeline": false
    }, 
    "sub_group_size": 1.000000e+14, 
    "prefetch_bucket_size": 6.039798e+07, 
    "param_persistence_threshold": 8.192000e+04, 
    "max_live_parameters": 1.000000e+09, 
    "max_reuse_distance": 1.000000e+09, 
    "gather_fp16_weights_on_model_save": false, 
    "ignore_unused_parameters": true
}
[2021-05-26 04:51:31,920] [INFO] [config.py:752:print]   zero_enabled ................. True
[2021-05-26 04:51:31,920] [INFO] [config.py:752:print]   zero_optimization_stage ...... 3
[2021-05-26 04:51:31,920] [INFO] [config.py:754:print]   json = {
    "fp16": {
        "enabled": true, 
        "loss_scale": 0, 
        "loss_scale_window": 1000, 
        "initial_scale_power": 8, 
        "hysteresis": 2, 
        "min_loss_scale": 1
    }, 
    "optimizer": {
        "type": "AdamW", 
        "params": {
            "lr": 5e-05, 
            "betas": [0.9, 0.999], 
            "eps": 1e-08, 
            "weight_decay": 0.0
        }
    }, 
    "scheduler": {
        "type": "WarmupLR", 
        "params": {
            "warmup_min_lr": 0, 
            "warmup_max_lr": 5e-05, 
            "warmup_num_steps": 8
        }
    }, 
    "zero_optimization": {
        "stage": 3, 
        "offload_optimizer": {
            "device": "cpu", 
            "pin_memory": true
        }, 
        "offload_param": {
            "device": "cpu", 
            "pin_memory": true
        }, 
        "overlap_comm": true, 
        "contiguous_gradients": true, 
        "sub_group_size": 1.000000e+14, 
        "reduce_bucket_size": 6.710886e+07, 
        "stage3_prefetch_bucket_size": 6.039798e+07, 
        "stage3_param_persistence_threshold": 8.192000e+04, 
        "stage3_max_live_parameters": 1.000000e+09, 
        "stage3_max_reuse_distance": 1.000000e+09, 
        "stage3_gather_fp16_weights_on_model_save": false
    }, 
    "gradient_accumulation_steps": 1, 
    "gradient_clipping": 1.0, 
    "steps_per_print": 2.000000e+03, 
    "train_batch_size": 512, 
    "train_micro_batch_size_per_gpu": 8, 
    "wall_clock_breakdown": false
}
[2021-05-26 04:56:04,854] [INFO] [stage3.py:2708:_overflow_clean_up] [deepscale] OVERFLOW! Rank 0 Skipping step. Attempted loss scale: 256, reducing to 256
{'train_runtime': 273.0148, 'train_samples_per_second': 3.663, 'train_steps_per_second': 0.007, 'epoch': 1.0}
{'train_runtime': 273.0144, 'train_samples_per_second': 3.663, 'train_steps_per_second': 0.007, 'epoch': 1.0}
{'train_runtime': 273.0144, 'train_samples_per_second': 3.663, 'train_steps_per_second': 0.007, 'epoch': 1.0}
{'train_runtime': 273.0145, 'train_samples_per_second': 3.663, 'train_steps_per_second': 0.007, 'epoch': 1.0}
{'train_runtime': 273.0148, 'train_samples_per_second': 3.663, 'train_steps_per_second': 0.007, 'epoch': 1.0}
{'train_runtime': 273.0146, 'train_samples_per_second': 3.663, 'train_steps_per_second': 0.007, 'epoch': 1.0}
{'train_runtime': 273.0144, 'train_samples_per_second': 3.663, 'train_steps_per_second': 0.007, 'epoch': 1.0}
{'train_runtime': 273.0145, 'train_samples_per_second': 3.663, 'train_steps_per_second': 0.007, 'epoch': 1.0}
{'train_runtime': 272.9369, 'train_samples_per_second': 3.664, 'train_steps_per_second': 0.007, 'epoch': 1.0}
{'train_runtime': 273.0143, 'train_samples_per_second': 3.663, 'train_steps_per_second': 0.007, 'epoch': 1.0}
{'train_runtime': 273.0147, 'train_samples_per_second': 3.663, 'train_steps_per_second': 0.007, 'epoch': 1.0}
{'train_runtime': 273.0148, 'train_samples_per_second': 3.663, 'train_steps_per_second': 0.007, 'epoch': 1.0}
{'train_runtime': 273.0125, 'train_samples_per_second': 3.663, 'train_steps_per_second': 0.007, 'epoch': 1.0}
{'train_runtime': 273.0143, 'train_samples_per_second': 3.663, 'train_steps_per_second': 0.007, 'epoch': 1.0}
{'train_runtime': 273.0146, 'train_samples_per_second': 3.663, 'train_steps_per_second': 0.007, 'epoch': 1.0}
{'train_runtime': 273.0149, 'train_samples_per_second': 3.663, 'train_steps_per_second': 0.007, 'epoch': 1.0}
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,861] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,862] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,863] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,864] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:04,866] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False
[2021-05-26 04:56:05,256] [INFO] [engine.py:1867:save_fp16_model] Did not save the model output_dir/pytorch_model.bin because `stage3_gather_fp16_weights_on_model_save` is False