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: loaded library: 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

/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
loaded library: /usr/lib/x86_64-linux-gnu/libibverbs.so.1
loaded library: /usr/lib/x86_64-linux-gnu/libibverbs.so.1
------------------------ arguments ------------------------
  batch_size ...................................... 512
  batch_size_per_proc ............................. 64
  data_dir ........................................ /dataset/f9f659c5/wdl_ofrecord
  data_part_name_suffix_length .................... 5
  data_part_num ................................... 256
  dataset_format .................................. ofrecord
  ddp ............................................. False
  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 .................................. graph
  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: 0.0665798112750053, latency(ms): 175.7372224330902100 | 2022-04-15 15:24:28.008
timestamp, name, driver_version, utilization.gpu [%], utilization.memory [%], memory.total [MiB], memory.free [MiB], memory.used [MiB]
2022/04/15 15:24:28.897, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30433 MiB, 2077 MiB
2022/04/15 15:24:28.902, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30453 MiB, 2057 MiB
2022/04/15 15:24:28.906, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30605 MiB, 1905 MiB
2022/04/15 15:24:28.910, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30557 MiB, 1953 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]
2022/04/15 15:24:28.913, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30573 MiB, 1937 MiB
timestamp, name, driver_version, utilization.gpu [%], utilization.memory [%], memory.total [MiB], memory.free [MiB], memory.used [MiB]
2022/04/15 15:24:28.914, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30433 MiB, 2077 MiB
2022/04/15 15:24:28.915, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30433 MiB, 2077 MiB
2022/04/15 15:24:28.917, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30437 MiB, 2073 MiB
2022/04/15 15:24:28.917, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30433 MiB, 2077 MiB
timestamp, name, driver_version, utilization.gpu [%], utilization.memory [%], memory.total [MiB], memory.free [MiB], memory.used [MiB]
2022/04/15 15:24:28.918, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30453 MiB, 2057 MiB
2022/04/15 15:24:28.920, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30453 MiB, 2057 MiB
timestamp, name, driver_version, utilization.gpu [%], utilization.memory [%], memory.total [MiB], memory.free [MiB], memory.used [MiB]
2022/04/15 15:24:28.921, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30325 MiB, 2185 MiB
2022/04/15 15:24:28.922, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30453 MiB, 2057 MiB
2022/04/15 15:24:28.923, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30605 MiB, 1905 MiB
2022/04/15 15:24:28.922, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30433 MiB, 2077 MiB
2022/04/15 15:24:28.924, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30605 MiB, 1905 MiB
2022/04/15 15:24:28.926, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30485 MiB, 2025 MiB
2022/04/15 15:24:28.925, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30433 MiB, 2077 MiB
2022/04/15 15:24:28.926, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30605 MiB, 1905 MiB
2022/04/15 15:24:28.928, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30557 MiB, 1953 MiB
2022/04/15 15:24:28.929, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30453 MiB, 2057 MiB
2022/04/15 15:24:28.930, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30557 MiB, 1953 MiB
2022/04/15 15:24:28.932, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30453 MiB, 2057 MiB
2022/04/15 15:24:28.932, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30557 MiB, 1953 MiB
2022/04/15 15:24:28.934, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30573 MiB, 1937 MiB
2022/04/15 15:24:28.934, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30605 MiB, 1905 MiB
2022/04/15 15:24:28.936, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30573 MiB, 1937 MiB
2022/04/15 15:24:28.938, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30605 MiB, 1905 MiB
2022/04/15 15:24:28.938, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30573 MiB, 1937 MiB
2022/04/15 15:24:28.939, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30437 MiB, 2073 MiB
2022/04/15 15:24:28.940, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30557 MiB, 1953 MiB
2022/04/15 15:24:28.942, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30437 MiB, 2073 MiB
2022/04/15 15:24:28.943, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30557 MiB, 1953 MiB
2022/04/15 15:24:28.944, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30437 MiB, 2073 MiB
2022/04/15 15:24:28.945, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30325 MiB, 2185 MiB
2022/04/15 15:24:28.946, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30573 MiB, 1937 MiB
2022/04/15 15:24:28.947, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30325 MiB, 2185 MiB
2022/04/15 15:24:28.949, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30573 MiB, 1937 MiB
2022/04/15 15:24:28.949, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30325 MiB, 2185 MiB
2022/04/15 15:24:28.950, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30485 MiB, 2025 MiB
2022/04/15 15:24:28.951, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30437 MiB, 2073 MiB
2022/04/15 15:24:28.952, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30485 MiB, 2025 MiB
2022/04/15 15:24:28.958, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30437 MiB, 2073 MiB
2022/04/15 15:24:28.958, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30485 MiB, 2025 MiB
2022/04/15 15:24:28.961, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30325 MiB, 2185 MiB
2022/04/15 15:24:28.965, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30325 MiB, 2185 MiB
2022/04/15 15:24:28.967, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30485 MiB, 2025 MiB
2022/04/15 15:24:28.970, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30485 MiB, 2025 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]
2022/04/15 15:24:29.837, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30433 MiB, 2077 MiB
2022/04/15 15:24:29.837, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30433 MiB, 2077 MiB
2022/04/15 15:24:29.839, Tesla V100-SXM2-32GB, 470.57.02, 100 %, 0 %, 32510 MiB, 30453 MiB, 2057 MiB
2022/04/15 15:24:29.839, Tesla V100-SXM2-32GB, 470.57.02, 100 %, 0 %, 32510 MiB, 30453 MiB, 2057 MiB
2022/04/15 15:24:29.840, Tesla V100-SXM2-32GB, 470.57.02, 100 %, 0 %, 32510 MiB, 30605 MiB, 1905 MiB
2022/04/15 15:24:29.840, Tesla V100-SXM2-32GB, 470.57.02, 100 %, 0 %, 32510 MiB, 30605 MiB, 1905 MiB
2022/04/15 15:24:29.842, Tesla V100-SXM2-32GB, 470.57.02, 100 %, 0 %, 32510 MiB, 30557 MiB, 1953 MiB
2022/04/15 15:24:29.842, Tesla V100-SXM2-32GB, 470.57.02, 100 %, 0 %, 32510 MiB, 30557 MiB, 1953 MiB
2022/04/15 15:24:29.843, Tesla V100-SXM2-32GB, 470.57.02, 100 %, 0 %, 32510 MiB, 30573 MiB, 1937 MiB
2022/04/15 15:24:29.844, Tesla V100-SXM2-32GB, 470.57.02, 100 %, 0 %, 32510 MiB, 30573 MiB, 1937 MiB
2022/04/15 15:24:29.845, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30437 MiB, 2073 MiB
2022/04/15 15:24:29.845, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30437 MiB, 2073 MiB
2022/04/15 15:24:29.846, Tesla V100-SXM2-32GB, 470.57.02, 100 %, 0 %, 32510 MiB, 30325 MiB, 2185 MiB
2022/04/15 15:24:29.847, Tesla V100-SXM2-32GB, 470.57.02, 100 %, 0 %, 32510 MiB, 30325 MiB, 2185 MiB
2022/04/15 15:24:29.848, Tesla V100-SXM2-32GB, 470.57.02, 100 %, 0 %, 32510 MiB, 30485 MiB, 2025 MiB
2022/04/15 15:24:29.849, Tesla V100-SXM2-32GB, 470.57.02, 100 %, 0 %, 32510 MiB, 30485 MiB, 2025 MiB
[rank:0] iter: 200/1100, loss: 0.0613985247910023, latency(ms): 21.8177231401205063 | 2022-04-15 15:24:30.189
[rank:0] iter: 300/1100, loss: 0.0614683441817760, latency(ms): 3.1469083204865456 | 2022-04-15 15:24:30.504
[rank:0] iter: 400/1100, loss: 0.0618508756160736, latency(ms): 3.0413244664669037 | 2022-04-15 15:24:30.808
[rank:0] iter: 500/1100, loss: 0.0618835985660553, latency(ms): 3.5512510687112808 | 2022-04-15 15:24:31.163
[rank:0] iter: 600/1100, loss: 0.0611942373216152, latency(ms): 3.5795041918754578 | 2022-04-15 15:24:31.521
[rank:0] iter: 700/1100, loss: 0.0586648099124432, latency(ms): 3.3684371411800385 | 2022-04-15 15:24:31.858
[rank:0] iter: 800/1100, loss: 0.0603685192763805, latency(ms): 3.3453674241900444 | 2022-04-15 15:24:32.193
[rank:0] iter: 900/1100, loss: 0.0611195899546146, latency(ms): 3.1025375053286552 | 2022-04-15 15:24:32.503
[rank:0] iter: 1000/1100, loss: 0.0605405457317829, latency(ms): 3.7378174439072609 | 2022-04-15 15:24:32.877
[rank:0] iter: 1100/1100, loss: 0.0596767291426659, latency(ms): 3.2354526966810226 | 2022-04-15 15:24:33.200