loaded library: /usr/lib/x86_64-linux-gnu/libibverbs.so.1
*****************************************
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. 
*****************************************
loaded library: /usr/lib/x86_64-linux-gnu/libibverbs.so.1
loaded library: /usr/lib/x86_64-linux-gnu/libibverbs.so.1
loaded library: /usr/lib/x86_64-linux-gnu/libibverbs.so.1
loaded library: /usr/lib/x86_64-linux-gnu/libibverbs.so.1
loaded library: loaded library: loaded library: /usr/lib/x86_64-linux-gnu/libibverbs.so.1/usr/lib/x86_64-linux-gnu/libibverbs.so.1

/usr/lib/x86_64-linux-gnu/libibverbs.so.1
loaded library: /usr/lib/x86_64-linux-gnu/libibverbs.so.1
------------------------ arguments ------------------------
  batch_size ...................................... 131072
  batch_size_per_proc ............................. 16384
  data_dir ........................................ /dataset/f9f659c5/wdl_ofrecord
  data_part_name_suffix_length .................... 5
  data_part_num ................................... 256
  dataset_format .................................. ofrecord
  ddp ............................................. True
  deep_dropout_rate ............................... 0.5
  deep_embedding_vec_size ......................... 16
  deep_vocab_size ................................. 2322444
  eval_after_training ............................. False
  eval_batchs ..................................... 20
  eval_interval ................................... 0
  execution_mode .................................. eager
  hidden_size ..................................... 1024
  hidden_units_num ................................ 2
  learning_rate ................................... 0.001
  loss_print_every_n_iter ......................... 100
  max_iter ........................................ 1100
  model_load_dir .................................. 
  model_save_dir .................................. ./checkpoint
  num_deep_sparse_fields .......................... 26
  num_dense_fields ................................ 13
  num_wide_sparse_fields .......................... 2
  save_initial_model .............................. False
  save_model_after_each_eval ...................... False
  test_name ....................................... noname_test
  wide_vocab_size ................................. 2322444
-------------------- end of arguments ---------------------
[rank:0] iter: 100/1100, loss: 0.5027823448181152, latency(ms): 100.9998421743512154 | 2022-04-28 02:21:21.067
timestamp, name, driver_version, utilization.gpu [%], utilization.memory [%], memory.total [MiB], memory.free [MiB], memory.used [MiB]
2022/04/28 02:21:21.211, Tesla V100-SXM2-32GB, 470.57.02, 8 %, 2 %, 32510 MiB, 29888 MiB, 2622 MiB
2022/04/28 02:21:21.218, Tesla V100-SXM2-32GB, 470.57.02, 1 %, 1 %, 32510 MiB, 29908 MiB, 2602 MiB
2022/04/28 02:21:21.224, Tesla V100-SXM2-32GB, 470.57.02, 39 %, 13 %, 32510 MiB, 29984 MiB, 2526 MiB
2022/04/28 02:21:21.231, Tesla V100-SXM2-32GB, 470.57.02, 81 %, 23 %, 32510 MiB, 29960 MiB, 2550 MiB
timestamp, name, driver_version, utilization.gpu [%], utilization.memory [%], memory.total [MiB], memory.free [MiB], memory.used [MiB]
2022/04/28 02:21:21.239, Tesla V100-SXM2-32GB, 470.57.02, 1 %, 1 %, 32510 MiB, 29968 MiB, 2542 MiB
timestamp, name, driver_version, utilization.gpu [%], utilization.memory [%], memory.total [MiB], memory.free [MiB], memory.used [MiB]
2022/04/28 02:21:21.242, Tesla V100-SXM2-32GB, 470.57.02, 8 %, 2 %, 32510 MiB, 29888 MiB, 2622 MiB
timestamp, name, driver_version, utilization.gpu [%], utilization.memory [%], memory.total [MiB], memory.free [MiB], memory.used [MiB]
2022/04/28 02:21:21.246, Tesla V100-SXM2-32GB, 470.57.02, 45 %, 25 %, 32510 MiB, 29900 MiB, 2610 MiB
timestamp, name, driver_version, utilization.gpu [%], utilization.memory [%], memory.total [MiB], memory.free [MiB], memory.used [MiB]
2022/04/28 02:21:21.248, Tesla V100-SXM2-32GB, 470.57.02, 8 %, 2 %, 32510 MiB, 29888 MiB, 2622 MiB
timestamp, name, driver_version, utilization.gpu [%], utilization.memory [%], memory.total [MiB], memory.free [MiB], memory.used [MiB]
timestamp, name, driver_version, utilization.gpu [%], utilization.memory [%], memory.total [MiB], memory.free [MiB], memory.used [MiB]
2022/04/28 02:21:21.250, Tesla V100-SXM2-32GB, 470.57.02, 1 %, 1 %, 32510 MiB, 29908 MiB, 2602 MiB
2022/04/28 02:21:21.250, Tesla V100-SXM2-32GB, 470.57.02, 8 %, 2 %, 32510 MiB, 29888 MiB, 2622 MiB
2022/04/28 02:21:21.252, Tesla V100-SXM2-32GB, 470.57.02, 38 %, 12 %, 32510 MiB, 29844 MiB, 2666 MiB
2022/04/28 02:21:21.254, Tesla V100-SXM2-32GB, 470.57.02, 8 %, 2 %, 32510 MiB, 29888 MiB, 2622 MiB
2022/04/28 02:21:21.255, Tesla V100-SXM2-32GB, 470.57.02, 1 %, 1 %, 32510 MiB, 29908 MiB, 2602 MiB
2022/04/28 02:21:21.255, Tesla V100-SXM2-32GB, 470.57.02, 8 %, 2 %, 32510 MiB, 29888 MiB, 2622 MiB
2022/04/28 02:21:21.256, Tesla V100-SXM2-32GB, 470.57.02, 39 %, 13 %, 32510 MiB, 29984 MiB, 2526 MiB
2022/04/28 02:21:21.256, Tesla V100-SXM2-32GB, 470.57.02, 8 %, 2 %, 32510 MiB, 29888 MiB, 2622 MiB
2022/04/28 02:21:21.258, Tesla V100-SXM2-32GB, 470.57.02, 1 %, 1 %, 32510 MiB, 29908 MiB, 2602 MiB
2022/04/28 02:21:21.260, Tesla V100-SXM2-32GB, 470.57.02, 45 %, 15 %, 32510 MiB, 29924 MiB, 2586 MiB
timestamp, name, driver_version, utilization.gpu [%], utilization.memory [%], memory.total [MiB], memory.free [MiB], memory.used [MiB]
2022/04/28 02:21:21.263, Tesla V100-SXM2-32GB, 470.57.02, 1 %, 1 %, 32510 MiB, 29908 MiB, 2602 MiB
2022/04/28 02:21:21.263, Tesla V100-SXM2-32GB, 470.57.02, 39 %, 13 %, 32510 MiB, 29984 MiB, 2526 MiB
2022/04/28 02:21:21.265, Tesla V100-SXM2-32GB, 470.57.02, 1 %, 1 %, 32510 MiB, 29908 MiB, 2602 MiB
2022/04/28 02:21:21.265, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29960 MiB, 2550 MiB
2022/04/28 02:21:21.266, Tesla V100-SXM2-32GB, 470.57.02, 1 %, 1 %, 32510 MiB, 29908 MiB, 2602 MiB
2022/04/28 02:21:21.267, Tesla V100-SXM2-32GB, 470.57.02, 39 %, 13 %, 32510 MiB, 29984 MiB, 2526 MiB
2022/04/28 02:21:21.269, Tesla V100-SXM2-32GB, 470.57.02, 8 %, 2 %, 32510 MiB, 29888 MiB, 2622 MiB
2022/04/28 02:21:21.272, Tesla V100-SXM2-32GB, 470.57.02, 39 %, 13 %, 32510 MiB, 29984 MiB, 2526 MiB
2022/04/28 02:21:21.272, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29960 MiB, 2550 MiB
2022/04/28 02:21:21.273, Tesla V100-SXM2-32GB, 470.57.02, 39 %, 13 %, 32510 MiB, 29984 MiB, 2526 MiB
2022/04/28 02:21:21.274, Tesla V100-SXM2-32GB, 470.57.02, 1 %, 1 %, 32510 MiB, 29968 MiB, 2542 MiB
2022/04/28 02:21:21.275, Tesla V100-SXM2-32GB, 470.57.02, 39 %, 13 %, 32510 MiB, 29984 MiB, 2526 MiB
2022/04/28 02:21:21.276, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29960 MiB, 2550 MiB
2022/04/28 02:21:21.279, Tesla V100-SXM2-32GB, 470.57.02, 1 %, 1 %, 32510 MiB, 29908 MiB, 2602 MiB
2022/04/28 02:21:21.281, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29960 MiB, 2550 MiB
2022/04/28 02:21:21.281, Tesla V100-SXM2-32GB, 470.57.02, 1 %, 1 %, 32510 MiB, 29968 MiB, 2542 MiB
2022/04/28 02:21:21.283, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29960 MiB, 2550 MiB
2022/04/28 02:21:21.283, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29900 MiB, 2610 MiB
2022/04/28 02:21:21.284, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29960 MiB, 2550 MiB
2022/04/28 02:21:21.285, Tesla V100-SXM2-32GB, 470.57.02, 1 %, 1 %, 32510 MiB, 29968 MiB, 2542 MiB
2022/04/28 02:21:21.289, Tesla V100-SXM2-32GB, 470.57.02, 39 %, 13 %, 32510 MiB, 29984 MiB, 2526 MiB
2022/04/28 02:21:21.290, Tesla V100-SXM2-32GB, 470.57.02, 1 %, 1 %, 32510 MiB, 29968 MiB, 2542 MiB
2022/04/28 02:21:21.291, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29900 MiB, 2610 MiB
2022/04/28 02:21:21.292, Tesla V100-SXM2-32GB, 470.57.02, 1 %, 1 %, 32510 MiB, 29968 MiB, 2542 MiB
2022/04/28 02:21:21.293, Tesla V100-SXM2-32GB, 470.57.02, 38 %, 12 %, 32510 MiB, 29844 MiB, 2666 MiB
2022/04/28 02:21:21.294, Tesla V100-SXM2-32GB, 470.57.02, 1 %, 1 %, 32510 MiB, 29968 MiB, 2542 MiB
2022/04/28 02:21:21.294, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29900 MiB, 2610 MiB
2022/04/28 02:21:21.298, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29960 MiB, 2550 MiB
2022/04/28 02:21:21.300, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29900 MiB, 2610 MiB
2022/04/28 02:21:21.300, Tesla V100-SXM2-32GB, 470.57.02, 38 %, 12 %, 32510 MiB, 29844 MiB, 2666 MiB
2022/04/28 02:21:21.301, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29900 MiB, 2610 MiB
2022/04/28 02:21:21.302, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29924 MiB, 2586 MiB
2022/04/28 02:21:21.303, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29900 MiB, 2610 MiB
2022/04/28 02:21:21.304, Tesla V100-SXM2-32GB, 470.57.02, 38 %, 12 %, 32510 MiB, 29844 MiB, 2666 MiB
2022/04/28 02:21:21.310, Tesla V100-SXM2-32GB, 470.57.02, 1 %, 1 %, 32510 MiB, 29968 MiB, 2542 MiB
2022/04/28 02:21:21.312, Tesla V100-SXM2-32GB, 470.57.02, 38 %, 12 %, 32510 MiB, 29844 MiB, 2666 MiB
2022/04/28 02:21:21.312, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29924 MiB, 2586 MiB
2022/04/28 02:21:21.314, Tesla V100-SXM2-32GB, 470.57.02, 38 %, 12 %, 32510 MiB, 29844 MiB, 2666 MiB
2022/04/28 02:21:21.315, Tesla V100-SXM2-32GB, 470.57.02, 38 %, 12 %, 32510 MiB, 29844 MiB, 2666 MiB
2022/04/28 02:21:21.316, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29924 MiB, 2586 MiB
2022/04/28 02:21:21.320, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29900 MiB, 2610 MiB
2022/04/28 02:21:21.322, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29924 MiB, 2586 MiB
2022/04/28 02:21:21.323, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29924 MiB, 2586 MiB
2022/04/28 02:21:21.324, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29924 MiB, 2586 MiB
2022/04/28 02:21:21.328, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29844 MiB, 2666 MiB
2022/04/28 02:21:21.334, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 29924 MiB, 2586 MiB
[rank:0] iter: 200/1100, loss: 0.4680253863334656, latency(ms): 42.8444217145442963 | 2022-04-28 02:21:25.351
[rank:0] iter: 300/1100, loss: 0.4603089988231659, latency(ms): 39.3384018912911415 | 2022-04-28 02:21:29.285
[rank:0] iter: 400/1100, loss: 0.4516502320766449, latency(ms): 39.4663725048303604 | 2022-04-28 02:21:33.232
[rank:0] iter: 500/1100, loss: 0.4500622153282166, latency(ms): 39.6678371727466583 | 2022-04-28 02:21:37.199
[rank:0] iter: 600/1100, loss: 0.4461638331413269, latency(ms): 39.8423748463392258 | 2022-04-28 02:21:41.183
[rank:0] iter: 700/1100, loss: 0.4398828148841858, latency(ms): 42.6921729370951653 | 2022-04-28 02:21:45.452
[rank:0] iter: 800/1100, loss: 0.4423809945583344, latency(ms): 40.7053591310977936 | 2022-04-28 02:21:49.523
[rank:0] iter: 900/1100, loss: 0.4324552118778229, latency(ms): 40.2127928659319878 | 2022-04-28 02:21:53.544
[rank:0] iter: 1000/1100, loss: 0.4310615658760071, latency(ms): 39.4916423410177231 | 2022-04-28 02:21:57.493
[rank:0] iter: 1100/1100, loss: 0.4326523542404175, latency(ms): 40.4023817181587219 | 2022-04-28 02:22:01.533