31
12381
00_data
{"\"inputs\"": [], "\"name\"": "\"data\"", "\"op\"": "\"null\""}
12381
01_hybridsequential0_batchnorm0_gamma
{"\"attrs\"": {"\"__dtype__\"": "\"0\"", "\"__init__\"": "\"ones\"", "\"__lr_mult__\"": "\"1.0\"", "\"__shape__\"": "\"(0,)\"", "\"__storage_type__\"": "\"0\"", "\"__wd_mult__\"": "\"1.0\""}, "\"inputs\"": [], "\"name\"": "\"hybridsequential0_batchnorm0_gamma\"", "\"op\"": "\"null\""}
12381
02_hybridsequential0_batchnorm0_beta
{"\"attrs\"": {"\"__dtype__\"": "\"0\"", "\"__init__\"": "\"zeros\"", "\"__lr_mult__\"": "\"1.0\"", "\"__shape__\"": "\"(0,)\"", "\"__storage_type__\"": "\"0\"", "\"__wd_mult__\"": "\"1.0\""}, "\"inputs\"": [], "\"name\"": "\"hybridsequential0_batchnorm0_beta\"", "\"op\"": "\"null\""}
12381
03_hybridsequential0_batchnorm0_running_mean
{"\"attrs\"": {"\"__dtype__\"": "\"0\"", "\"__init__\"": "\"zeros\"", "\"__lr_mult__\"": "\"1.0\"", "\"__shape__\"": "\"(0,)\"", "\"__storage_type__\"": "\"0\"", "\"__wd_mult__\"": "\"1.0\""}, "\"inputs\"": [], "\"name\"": "\"hybridsequential0_batchnorm0_running_mean\"", "\"op\"": "\"null\""}
12381
04_hybridsequential0_batchnorm0_running_var
{"\"attrs\"": {"\"__dtype__\"": "\"0\"", "\"__init__\"": "\"ones\"", "\"__lr_mult__\"": "\"1.0\"", "\"__shape__\"": "\"(0,)\"", "\"__storage_type__\"": "\"0\"", "\"__wd_mult__\"": "\"1.0\""}, "\"inputs\"": [], "\"name\"": "\"hybridsequential0_batchnorm0_running_var\"", "\"op\"": "\"null\""}
12381
05_hybridsequential0_batchnorm0_fwd
{"\"attrs\"": {"\"axis\"": "\"1\"", "\"eps\"": "\"1e-05\"", "\"fix_gamma\"": "\"False\"", "\"momentum\"": "\"0.9\"", "\"use_global_stats\"": "\"False\""}, "\"inputs\"": [[0, 0, 0], [1, 0, 0], [2, 0, 0], [3, 0, 1], [4, 0, 1]], "\"name\"": "\"hybridsequential0_batchnorm0_fwd\"", "\"op\"": "\"BatchNorm\""}
12381
06_hybridsequential0_dense0_weight
{"\"attrs\"": {"\"__dtype__\"": "\"0\"", "\"__lr_mult__\"": "\"1.0\"", "\"__shape__\"": "\"(1024, 0)\"", "\"__storage_type__\"": "\"0\"", "\"__wd_mult__\"": "\"1.0\""}, "\"inputs\"": [], "\"name\"": "\"hybridsequential0_dense0_weight\"", "\"op\"": "\"null\""}
12381
07_hybridsequential0_dense0_bias
{"\"attrs\"": {"\"__dtype__\"": "\"0\"", "\"__init__\"": "\"zeros\"", "\"__lr_mult__\"": "\"1.0\"", "\"__shape__\"": "\"(1024,)\"", "\"__storage_type__\"": "\"0\"", "\"__wd_mult__\"": "\"1.0\""}, "\"inputs\"": [], "\"name\"": "\"hybridsequential0_dense0_bias\"", "\"op\"": "\"null\""}
12381
08_hybridsequential0_dense0_fwd
{"\"attrs\"": {"\"flatten\"": "\"True\"", "\"no_bias\"": "\"False\"", "\"num_hidden\"": "\"1024\""}, "\"inputs\"": [[5, 0, 0], [6, 0, 0], [7, 0, 0]], "\"name\"": "\"hybridsequential0_dense0_fwd\"", "\"op\"": "\"FullyConnected\""}
12381
09_hybridsequential0_dense0_relu_fwd
{"\"attrs\"": {"\"act_type\"": "\"relu\""}, "\"inputs\"": [[8, 0, 0]], "\"name\"": "\"hybridsequential0_dense0_relu_fwd\"", "\"op\"": "\"Activation\""}
12381
10_hybridsequential0_dropout0_fwd
{"\"attrs\"": {"\"axes\"": "\"()\"", "\"cudnn_off\"": "\"False\"", "\"p\"": "\"0.4\""}, "\"inputs\"": [[9, 0, 0]], "\"name\"": "\"hybridsequential0_dropout0_fwd\"", "\"op\"": "\"Dropout\""}
12381
11_hybridsequential0_dense1_weight
{"\"attrs\"": {"\"__dtype__\"": "\"0\"", "\"__lr_mult__\"": "\"1.0\"", "\"__shape__\"": "\"(2, 0)\"", "\"__storage_type__\"": "\"0\"", "\"__wd_mult__\"": "\"1.0\""}, "\"inputs\"": [], "\"name\"": "\"hybridsequential0_dense1_weight\"", "\"op\"": "\"null\""}
12381
12_hybridsequential0_dense1_bias
{"\"attrs\"": {"\"__dtype__\"": "\"0\"", "\"__init__\"": "\"zeros\"", "\"__lr_mult__\"": "\"1.0\"", "\"__shape__\"": "\"(2,)\"", "\"__storage_type__\"": "\"0\"", "\"__wd_mult__\"": "\"1.0\""}, "\"inputs\"": [], "\"name\"": "\"hybridsequential0_dense1_bias\"", "\"op\"": "\"null\""}
12381
13_hybridsequential0_dense1_fwd
{"\"attrs\"": {"\"flatten\"": "\"True\"", "\"no_bias\"": "\"False\"", "\"num_hidden\"": "\"2\""}, "\"inputs\"": [[10, 0, 0], [11, 0, 0], [12, 0, 0]], "\"name\"": "\"hybridsequential0_dense1_fwd\"", "\"op\"": "\"FullyConnected\""}
12381
misc
{"\"arg_nodes\"": [0, 1, 2, 3, 4, 6, 7, 11, 12], "\"attrs\"": {"\"mxnet_version\"": ["\"int\"", 10500]}, "\"heads\"": [[13, 0, 0]], "\"node_row_ptr\"": [0, 1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 14, 15, 16, 17]}
12381
openml-python
MXNet_1.5.0.
wall_clock_time_millis_training
10047.000169754028
wall_clock_time_millis_training
9680.001258850098
wall_clock_time_millis_training
8780.998706817627
wall_clock_time_millis_training
8724.992513656616
wall_clock_time_millis_training
8671.000480651855
wall_clock_time_millis_training
8637.994289398193
wall_clock_time_millis_training
8710.515975952148
wall_clock_time_millis_training
8685.988187789917
wall_clock_time_millis_training
8911.524772644043
wall_clock_time_millis_training
8963.99998664856
wall_clock_time_millis_testing
3.0014514923095703
wall_clock_time_millis_testing
1.0001659393310547
wall_clock_time_millis_testing
1.0018348693847656
wall_clock_time_millis_testing
1.0008811950683594
wall_clock_time_millis_testing
0.9982585906982422
wall_clock_time_millis_testing
0.99945068359375
wall_clock_time_millis_testing
0.9999275207519531
wall_clock_time_millis_testing
0.99945068359375
wall_clock_time_millis_testing
2.002239227294922
wall_clock_time_millis_testing
0.9989738464355469
wall_clock_time_millis
10050.001621246338
wall_clock_time_millis
9681.001424789429
wall_clock_time_millis
8782.000541687012
wall_clock_time_millis
8725.993394851685
wall_clock_time_millis
8671.998739242554
wall_clock_time_millis
8638.993740081787
wall_clock_time_millis
8711.5159034729
wall_clock_time_millis
8686.98763847351
wall_clock_time_millis
8913.527011871338
wall_clock_time_millis
8964.998960494995
predictive_accuracy
0.74
predictive_accuracy
0.72
predictive_accuracy
0.74
predictive_accuracy
0.76
predictive_accuracy
0.73
predictive_accuracy
0.74
predictive_accuracy
0.77
predictive_accuracy
0.78
predictive_accuracy
0.76
predictive_accuracy
0.68