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: loaded library: /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
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: 0.0669986978173256, latency(ms): 176.8381198868155479 | 2022-04-28 10:51:23.178
timestamp, name, driver_version, utilization.gpu [%], utilization.memory [%], memory.total [MiB], memory.free [MiB], memory.used [MiB]
2022/04/28 10:51:23.327, Tesla V100-SXM2-32GB, 470.57.02, 54 %, 5 %, 32510 MiB, 30427 MiB, 2083 MiB
timestamp, name, driver_version, utilization.gpu [%], utilization.memory [%], memory.total [MiB], memory.free [MiB], memory.used [MiB]
2022/04/28 10:51:23.334, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30447 MiB, 2063 MiB
2022/04/28 10:51:23.338, Tesla V100-SXM2-32GB, 470.57.02, 54 %, 5 %, 32510 MiB, 30427 MiB, 2083 MiB
2022/04/28 10:51:23.339, Tesla V100-SXM2-32GB, 470.57.02, 32 %, 2 %, 32510 MiB, 30599 MiB, 1911 MiB
timestamp, name, driver_version, utilization.gpu [%], utilization.memory [%], memory.total [MiB], memory.free [MiB], memory.used [MiB]
2022/04/28 10:51:23.343, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30447 MiB, 2063 MiB
timestamp, name, driver_version, utilization.gpu [%], utilization.memory [%], memory.total [MiB], memory.free [MiB], memory.used [MiB]
2022/04/28 10:51:23.343, Tesla V100-SXM2-32GB, 470.57.02, 9 %, 0 %, 32510 MiB, 30551 MiB, 1959 MiB
2022/04/28 10:51:23.349, Tesla V100-SXM2-32GB, 470.57.02, 32 %, 2 %, 32510 MiB, 30599 MiB, 1911 MiB
2022/04/28 10:51:23.348, Tesla V100-SXM2-32GB, 470.57.02, 54 %, 5 %, 32510 MiB, 30427 MiB, 2083 MiB
2022/04/28 10:51:23.349, Tesla V100-SXM2-32GB, 470.57.02, 69 %, 5 %, 32510 MiB, 30567 MiB, 1943 MiB
2022/04/28 10:51:23.349, Tesla V100-SXM2-32GB, 470.57.02, 54 %, 5 %, 32510 MiB, 30427 MiB, 2083 MiB
2022/04/28 10:51:23.356, Tesla V100-SXM2-32GB, 470.57.02, 9 %, 0 %, 32510 MiB, 30551 MiB, 1959 MiB
2022/04/28 10:51:23.356, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30447 MiB, 2063 MiB
2022/04/28 10:51:23.357, Tesla V100-SXM2-32GB, 470.57.02, 11 %, 1 %, 32510 MiB, 30431 MiB, 2079 MiB
2022/04/28 10:51:23.357, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30447 MiB, 2063 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 10:51:23.363, Tesla V100-SXM2-32GB, 470.57.02, 69 %, 5 %, 32510 MiB, 30567 MiB, 1943 MiB
2022/04/28 10:51:23.363, Tesla V100-SXM2-32GB, 470.57.02, 32 %, 2 %, 32510 MiB, 30599 MiB, 1911 MiB
2022/04/28 10:51:23.363, Tesla V100-SXM2-32GB, 470.57.02, 45 %, 4 %, 32510 MiB, 30319 MiB, 2191 MiB
timestamp, name, driver_version, utilization.gpu [%], utilization.memory [%], memory.total [MiB], memory.free [MiB], memory.used [MiB]
2022/04/28 10:51:23.364, Tesla V100-SXM2-32GB, 470.57.02, 32 %, 2 %, 32510 MiB, 30599 MiB, 1911 MiB
timestamp, name, driver_version, utilization.gpu [%], utilization.memory [%], memory.total [MiB], memory.free [MiB], memory.used [MiB]
2022/04/28 10:51:23.364, Tesla V100-SXM2-32GB, 470.57.02, 54 %, 5 %, 32510 MiB, 30427 MiB, 2083 MiB
2022/04/28 10:51:23.367, Tesla V100-SXM2-32GB, 470.57.02, 54 %, 5 %, 32510 MiB, 30427 MiB, 2083 MiB
2022/04/28 10:51:23.368, Tesla V100-SXM2-32GB, 470.57.02, 11 %, 1 %, 32510 MiB, 30431 MiB, 2079 MiB
2022/04/28 10:51:23.369, Tesla V100-SXM2-32GB, 470.57.02, 9 %, 0 %, 32510 MiB, 30551 MiB, 1959 MiB
2022/04/28 10:51:23.369, Tesla V100-SXM2-32GB, 470.57.02, 49 %, 4 %, 32510 MiB, 30479 MiB, 2031 MiB
2022/04/28 10:51:23.369, Tesla V100-SXM2-32GB, 470.57.02, 9 %, 0 %, 32510 MiB, 30551 MiB, 1959 MiB
2022/04/28 10:51:23.369, Tesla V100-SXM2-32GB, 470.57.02, 54 %, 5 %, 32510 MiB, 30427 MiB, 2083 MiB
2022/04/28 10:51:23.370, Tesla V100-SXM2-32GB, 470.57.02, 54 %, 5 %, 32510 MiB, 30427 MiB, 2083 MiB
2022/04/28 10:51:23.372, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30447 MiB, 2063 MiB
2022/04/28 10:51:23.376, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30447 MiB, 2063 MiB
2022/04/28 10:51:23.377, Tesla V100-SXM2-32GB, 470.57.02, 45 %, 4 %, 32510 MiB, 30319 MiB, 2191 MiB
2022/04/28 10:51:23.378, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30567 MiB, 1943 MiB
2022/04/28 10:51:23.379, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30567 MiB, 1943 MiB
2022/04/28 10:51:23.379, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30447 MiB, 2063 MiB
2022/04/28 10:51:23.380, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30447 MiB, 2063 MiB
2022/04/28 10:51:23.381, Tesla V100-SXM2-32GB, 470.57.02, 32 %, 2 %, 32510 MiB, 30599 MiB, 1911 MiB
2022/04/28 10:51:23.386, Tesla V100-SXM2-32GB, 470.57.02, 32 %, 2 %, 32510 MiB, 30599 MiB, 1911 MiB
2022/04/28 10:51:23.386, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30479 MiB, 2031 MiB
2022/04/28 10:51:23.387, Tesla V100-SXM2-32GB, 470.57.02, 11 %, 1 %, 32510 MiB, 30431 MiB, 2079 MiB
2022/04/28 10:51:23.388, Tesla V100-SXM2-32GB, 470.57.02, 11 %, 1 %, 32510 MiB, 30431 MiB, 2079 MiB
2022/04/28 10:51:23.388, Tesla V100-SXM2-32GB, 470.57.02, 32 %, 2 %, 32510 MiB, 30599 MiB, 1911 MiB
2022/04/28 10:51:23.389, Tesla V100-SXM2-32GB, 470.57.02, 32 %, 2 %, 32510 MiB, 30599 MiB, 1911 MiB
2022/04/28 10:51:23.390, Tesla V100-SXM2-32GB, 470.57.02, 9 %, 0 %, 32510 MiB, 30551 MiB, 1959 MiB
2022/04/28 10:51:23.395, Tesla V100-SXM2-32GB, 470.57.02, 9 %, 0 %, 32510 MiB, 30551 MiB, 1959 MiB
2022/04/28 10:51:23.396, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30319 MiB, 2191 MiB
2022/04/28 10:51:23.397, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30319 MiB, 2191 MiB
2022/04/28 10:51:23.397, Tesla V100-SXM2-32GB, 470.57.02, 9 %, 0 %, 32510 MiB, 30551 MiB, 1959 MiB
2022/04/28 10:51:23.398, Tesla V100-SXM2-32GB, 470.57.02, 9 %, 0 %, 32510 MiB, 30551 MiB, 1959 MiB
2022/04/28 10:51:23.399, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30567 MiB, 1943 MiB
2022/04/28 10:51:23.404, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30567 MiB, 1943 MiB
2022/04/28 10:51:23.405, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30479 MiB, 2031 MiB
2022/04/28 10:51:23.406, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30479 MiB, 2031 MiB
2022/04/28 10:51:23.406, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30567 MiB, 1943 MiB
2022/04/28 10:51:23.407, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30567 MiB, 1943 MiB
2022/04/28 10:51:23.408, Tesla V100-SXM2-32GB, 470.57.02, 11 %, 1 %, 32510 MiB, 30431 MiB, 2079 MiB
2022/04/28 10:51:23.417, Tesla V100-SXM2-32GB, 470.57.02, 11 %, 1 %, 32510 MiB, 30431 MiB, 2079 MiB
2022/04/28 10:51:23.419, Tesla V100-SXM2-32GB, 470.57.02, 11 %, 1 %, 32510 MiB, 30431 MiB, 2079 MiB
2022/04/28 10:51:23.420, Tesla V100-SXM2-32GB, 470.57.02, 11 %, 1 %, 32510 MiB, 30431 MiB, 2079 MiB
2022/04/28 10:51:23.422, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30319 MiB, 2191 MiB
2022/04/28 10:51:23.425, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30319 MiB, 2191 MiB
2022/04/28 10:51:23.427, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30319 MiB, 2191 MiB
2022/04/28 10:51:23.427, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30319 MiB, 2191 MiB
2022/04/28 10:51:23.428, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30479 MiB, 2031 MiB
2022/04/28 10:51:23.435, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30479 MiB, 2031 MiB
2022/04/28 10:51:23.436, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30479 MiB, 2031 MiB
2022/04/28 10:51:23.437, Tesla V100-SXM2-32GB, 470.57.02, 0 %, 0 %, 32510 MiB, 30479 MiB, 2031 MiB
[rank:0] iter: 200/1100, loss: 0.0611650831997395, latency(ms): 6.2676991149783134 | 2022-04-28 10:51:23.804
[rank:0] iter: 300/1100, loss: 0.0618557929992676, latency(ms): 3.7256254255771637 | 2022-04-28 10:51:24.177
[rank:0] iter: 400/1100, loss: 0.0615133196115494, latency(ms): 3.3904532343149185 | 2022-04-28 10:51:24.516
[rank:0] iter: 500/1100, loss: 0.0619509071111679, latency(ms): 3.7535682320594788 | 2022-04-28 10:51:24.891
[rank:0] iter: 600/1100, loss: 0.0611266046762466, latency(ms): 3.2999579235911369 | 2022-04-28 10:51:25.221
[rank:0] iter: 700/1100, loss: 0.0589693561196327, latency(ms): 3.2554339990019798 | 2022-04-28 10:51:25.547
[rank:0] iter: 800/1100, loss: 0.0600591786205769, latency(ms): 3.1649114564061165 | 2022-04-28 10:51:25.863
[rank:0] iter: 900/1100, loss: 0.0610814765095711, latency(ms): 3.0630441009998322 | 2022-04-28 10:51:26.170
[rank:0] iter: 1000/1100, loss: 0.0602616444230080, latency(ms): 3.4293961897492409 | 2022-04-28 10:51:26.513
[rank:0] iter: 1100/1100, loss: 0.0595859959721565, latency(ms): 3.2121686264872551 | 2022-04-28 10:51:26.834