This is a notebook to keep logs on running the training procedure for the first time, with some simple preprocessing options. Have already sourced the Python 2 virtual environment set up according to instructions in the README from the tools repo and sourced the script to set environment variables:

source start_script

Checking that this has worked by importing Theano and looking at its config:


In [1]:
import theano
print(theano.config.device)


gpu0
Using gpu device 0: Tesla K40c

Looks like it's set up to use the GPU ok.

Running the code should then be as simple as pointing at the right run config json file. Using the following file:


In [2]:
cd ..


/afs/inf.ed.ac.uk/user/s08/s0805516/repos/neukrill-net-work

In [3]:
!cat run_settings/first_pylearn2_run.json


{
    "model type":"pylearn2",
    "yaml file": "default.yaml",
    "preprocessing":{"resize":[48,48]},
    "final_shape":[48,48],
    "augmentation_factor":1,
    "train_split": 0.8
}

Doing practically nothing except resizing to quite a small size. A major problem at this point is likely to be the lack of image normalization.

The YAML file specified is what controls Pylearn2's operation. The file we're using has been cannabalised from the MNIST example bundled with Pylearn2. It's in the repo and looks like this:


In [4]:
!cat yaml_templates/default.yaml


!obj:pylearn2.train.Train {
    dataset: &train !obj:neukrill_net.dense_dataset.DensePNGDataset {
        settings_path: %(settings_path)s,
        run_settings: %(run_settings_path)s,
        training_set_mode: "train"
    },
    model: !obj:pylearn2.models.mlp.MLP {
        batch_size: 128,
        input_space: !obj:pylearn2.space.Conv2DSpace {
            shape: %(final_shape)s,
            num_channels: 1,
            axes: ['c', 0, 1, 'b'],
        },
        layers: [
                 !obj:pylearn2.models.maxout.MaxoutConvC01B {
                     layer_name: 'h0',
                     pad: 0,
                     num_channels: 48,
                     num_pieces: 2,
                     kernel_shape: [8, 8],
                     pool_shape: [4, 4],
                     pool_stride: [2, 2],
                     irange: .005,
                     max_kernel_norm: .9,
                 },
                 !obj:pylearn2.models.maxout.MaxoutConvC01B {
                     layer_name: 'h1',
                     pad: 3,
                     num_channels: 48,
                     num_pieces: 2,
                     kernel_shape: [8, 8],
                     pool_shape: [4, 4],
                     pool_stride: [2, 2],
                     irange: .005,
                     max_kernel_norm: 1.9365,
                 },
                 !obj:pylearn2.models.maxout.MaxoutConvC01B {
                     pad: 3,
                     layer_name: 'h2',
                     num_channels: 24,
                     num_pieces: 4,
                     kernel_shape: [5, 5],
                     pool_shape: [2, 2],
                     pool_stride: [2, 2],
                     irange: .005,
                     max_kernel_norm: 1.9365,
                 },
                 !obj:pylearn2.models.mlp.Softmax {
                     max_col_norm: 1.9365,
                     layer_name: 'y',
                     n_classes: %(n_classes)s,
                     irange: .005
                 }
                ],
    },
    algorithm: !obj:pylearn2.training_algorithms.sgd.SGD {
        learning_rate: .05,
        learning_rule: !obj:pylearn2.training_algorithms.learning_rule.Momentum {
            init_momentum: 0.5,
        },
        train_iteration_mode: 'even_shuffled_sequential',
        monitor_iteration_mode: 'even_sequential',
        monitoring_dataset:
            {
                'valid' : !obj:neukrill_net.dense_dataset.DensePNGDataset  {
                                settings_path: %(settings_path)s,
                                run_settings: %(run_settings_path)s,
                                training_set_mode: "validation"
                          },
                'test'  : !obj:neukrill_net.dense_dataset.DensePNGDataset  {
                                settings_path: %(settings_path)s,
                                run_settings: %(run_settings_path)s,
                                training_set_mode: "test"
                          }
            },
        cost:  !obj:pylearn2.costs.mlp.dropout.Dropout {
            input_include_probs: { 'h0' : .8 },
            input_scales: { 'h0': 1. }
        },
        termination_criterion: !obj:pylearn2.termination_criteria.And {
            criteria: [
                !obj:pylearn2.termination_criteria.MonitorBased {
                    channel_name: "valid_y_misclass",
                    prop_decrease: 0.50,
                    N: 10
                },
                !obj:pylearn2.termination_criteria.EpochCounter {
                    max_epochs: 500
                },
            ]
        },
    },
    extensions:
        [ !obj:pylearn2.train_extensions.best_params.MonitorBasedSaveBest {
             channel_name: 'valid_y_misclass',
             save_path: %(save_path)s
        }, !obj:pylearn2.training_algorithms.learning_rule.MomentumAdjustor {
            start: 1,
            saturate: 10,
            final_momentum: .99
        }
    ]
}

All we need to do is point our train.py script (don't get this confused with either the train module from Pylearn2 or its own train.py script (unimaginative naming problems...)) at the above json:


In [ ]:
%pdb


Automatic pdb calling has been turned ON

In [ ]:
%run train.py run_settings/first_pylearn2_run.json


Input shape: (48, 48)
Detector space: (41, 41)
Output space: (20, 20)
Input shape: (20, 20)
Detector space: (19, 19)
Output space: (9, 9)
Input shape: (9, 9)
Detector space: (11, 11)
Output space: (6, 6)
Parameter and initial learning rate summary:
	h0_W: 0.0500000007451
	h0_b: 0.0500000007451
	h1_W: 0.0500000007451
	h1_b: 0.0500000007451
	h2_W: 0.0500000007451
	h2_b: 0.0500000007451
	softmax_b: 0.0500000007451
	softmax_W: 0.0500000007451
Compiling sgd_update...
/afs/inf.ed.ac.uk/user/s08/s0805516/repos/pylearn2/pylearn2/utils/iteration.py:783: UserWarning: dataset is using the old iterator interface which is deprecated and will become officially unsupported as of July 28, 2015. The dataset should implement a `get` method respecting the new interface.
  warnings.warn("dataset is using the old iterator interface which "
Compiling sgd_update done. Time elapsed: 3.973367 seconds
compiling begin_record_entry...
compiling begin_record_entry done. Time elapsed: 0.544542 seconds
Monitored channels: 
	learning_rate
	momentum
	test_h0_kernel_norms_max
	test_h0_kernel_norms_mean
	test_h0_kernel_norms_min
	test_h0_max_x.max_u
	test_h0_max_x.mean_u
	test_h0_max_x.min_u
	test_h0_mean_x.max_u
	test_h0_mean_x.mean_u
	test_h0_mean_x.min_u
	test_h0_min_x.max_u
	test_h0_min_x.mean_u
	test_h0_min_x.min_u
	test_h0_range_x.max_u
	test_h0_range_x.mean_u
	test_h0_range_x.min_u
	test_h1_kernel_norms_max
	test_h1_kernel_norms_mean
	test_h1_kernel_norms_min
	test_h1_max_x.max_u
	test_h1_max_x.mean_u
	test_h1_max_x.min_u
	test_h1_mean_x.max_u
	test_h1_mean_x.mean_u
	test_h1_mean_x.min_u
	test_h1_min_x.max_u
	test_h1_min_x.mean_u
	test_h1_min_x.min_u
	test_h1_range_x.max_u
	test_h1_range_x.mean_u
	test_h1_range_x.min_u
	test_h2_kernel_norms_max
	test_h2_kernel_norms_mean
	test_h2_kernel_norms_min
	test_h2_max_x.max_u
	test_h2_max_x.mean_u
	test_h2_max_x.min_u
	test_h2_mean_x.max_u
	test_h2_mean_x.mean_u
	test_h2_mean_x.min_u
	test_h2_min_x.max_u
	test_h2_min_x.mean_u
	test_h2_min_x.min_u
	test_h2_range_x.max_u
	test_h2_range_x.mean_u
	test_h2_range_x.min_u
	test_objective
	test_y_col_norms_max
	test_y_col_norms_mean
	test_y_col_norms_min
	test_y_max_max_class
	test_y_mean_max_class
	test_y_min_max_class
	test_y_misclass
	test_y_nll
	test_y_row_norms_max
	test_y_row_norms_mean
	test_y_row_norms_min
	total_seconds_last_epoch
	training_seconds_this_epoch
	valid_h0_kernel_norms_max
	valid_h0_kernel_norms_mean
	valid_h0_kernel_norms_min
	valid_h0_max_x.max_u
	valid_h0_max_x.mean_u
	valid_h0_max_x.min_u
	valid_h0_mean_x.max_u
	valid_h0_mean_x.mean_u
	valid_h0_mean_x.min_u
	valid_h0_min_x.max_u
	valid_h0_min_x.mean_u
	valid_h0_min_x.min_u
	valid_h0_range_x.max_u
	valid_h0_range_x.mean_u
	valid_h0_range_x.min_u
	valid_h1_kernel_norms_max
	valid_h1_kernel_norms_mean
	valid_h1_kernel_norms_min
	valid_h1_max_x.max_u
	valid_h1_max_x.mean_u
	valid_h1_max_x.min_u
	valid_h1_mean_x.max_u
	valid_h1_mean_x.mean_u
	valid_h1_mean_x.min_u
	valid_h1_min_x.max_u
	valid_h1_min_x.mean_u
	valid_h1_min_x.min_u
	valid_h1_range_x.max_u
	valid_h1_range_x.mean_u
	valid_h1_range_x.min_u
	valid_h2_kernel_norms_max
	valid_h2_kernel_norms_mean
	valid_h2_kernel_norms_min
	valid_h2_max_x.max_u
	valid_h2_max_x.mean_u
	valid_h2_max_x.min_u
	valid_h2_mean_x.max_u
	valid_h2_mean_x.mean_u
	valid_h2_mean_x.min_u
	valid_h2_min_x.max_u
	valid_h2_min_x.mean_u
	valid_h2_min_x.min_u
	valid_h2_range_x.max_u
	valid_h2_range_x.mean_u
	valid_h2_range_x.min_u
	valid_objective
	valid_y_col_norms_max
	valid_y_col_norms_mean
	valid_y_col_norms_min
	valid_y_max_max_class
	valid_y_mean_max_class
	valid_y_min_max_class
	valid_y_misclass
	valid_y_nll
	valid_y_row_norms_max
	valid_y_row_norms_mean
	valid_y_row_norms_min
Compiling accum...
graph size: 387
graph size: 383
Compiling accum done. Time elapsed: 13.744146 seconds
Monitoring step:
	Epochs seen: 0
	Batches seen: 0
	Examples seen: 0
	learning_rate: 0.0500000156462
	momentum: 0.500000059605
	test_h0_kernel_norms_max: 0.025620367378
	test_h0_kernel_norms_mean: 0.0229787509888
	test_h0_kernel_norms_min: 0.0195152591914
	test_h0_max_x.max_u: 0.0695547536016
	test_h0_max_x.mean_u: 0.0313058644533
	test_h0_max_x.min_u: 0.00327901006676
	test_h0_mean_x.max_u: 0.0611211955547
	test_h0_mean_x.mean_u: 0.0161500163376
	test_h0_mean_x.min_u: -0.0205041710287
	test_h0_min_x.max_u: 0.0150190703571
	test_h0_min_x.mean_u: 0.000894624390639
	test_h0_min_x.min_u: -0.0246901288629
	test_h0_range_x.max_u: 0.0549388863146
	test_h0_range_x.mean_u: 0.030411247164
	test_h0_range_x.min_u: 0.0161684025079
	test_h1_kernel_norms_max: 0.163002476096
	test_h1_kernel_norms_mean: 0.160210266709
	test_h1_kernel_norms_min: 0.157817587256
	test_h1_max_x.max_u: 0.0124799013138
	test_h1_max_x.mean_u: 0.00550353666767
	test_h1_max_x.min_u: -0.00122586847283
	test_h1_mean_x.max_u: 0.0103779649362
	test_h1_mean_x.mean_u: 0.00287891621701
	test_h1_mean_x.min_u: -0.00506942579523
	test_h1_min_x.max_u: 0.00670026056468
	test_h1_min_x.mean_u: 0.000480789778521
	test_h1_min_x.min_u: -0.00764158414677
	test_h1_range_x.max_u: 0.00772560434416
	test_h1_range_x.mean_u: 0.00502274744213
	test_h1_range_x.min_u: 0.00309842941351
	test_h2_kernel_norms_max: 0.102913320065
	test_h2_kernel_norms_mean: 0.0999667793512
	test_h2_kernel_norms_min: 0.0971000939608
	test_h2_max_x.max_u: 0.00137931655627
	test_h2_max_x.mean_u: 0.000808427110314
	test_h2_max_x.min_u: 0.000285953807179
	test_h2_mean_x.max_u: 0.000732974614948
	test_h2_mean_x.mean_u: 0.000421099801315
	test_h2_mean_x.min_u: 5.88356633671e-05
	test_h2_min_x.max_u: 0.000293726770906
	test_h2_min_x.mean_u: 5.37531268492e-05
	test_h2_min_x.min_u: -0.000307372451061
	test_h2_range_x.max_u: 0.00121322902851
	test_h2_range_x.mean_u: 0.000754674081691
	test_h2_range_x.min_u: 0.00044881858048
	test_objective: 4.79580688477
	test_y_col_norms_max: 0.0886595323682
	test_y_col_norms_mean: 0.0852382704616
	test_y_col_norms_min: 0.0822916701436
	test_y_max_max_class: 0.00826539006084
	test_y_mean_max_class: 0.00826532393694
	test_y_min_max_class: 0.00826526526362
	test_y_misclass: 0.999023616314
	test_y_nll: 4.79579114914
	test_y_row_norms_max: 0.0359390377998
	test_y_row_norms_mean: 0.0318758152425
	test_y_row_norms_min: 0.0280178301036
	total_seconds_last_epoch: 0.0
	training_seconds_this_epoch: 0.0
	valid_h0_kernel_norms_max: 0.0256203617901
	valid_h0_kernel_norms_mean: 0.0229787528515
	valid_h0_kernel_norms_min: 0.0195152573287
	valid_h0_max_x.max_u: 0.0694105625153
	valid_h0_max_x.mean_u: 0.0311431288719
	valid_h0_max_x.min_u: 0.00300892512314
	valid_h0_mean_x.max_u: 0.0612021870911
	valid_h0_mean_x.mean_u: 0.0161678306758
	valid_h0_mean_x.min_u: -0.0205619186163
	valid_h0_min_x.max_u: 0.0139615628868
	valid_h0_min_x.mean_u: 0.000747101788875
	valid_h0_min_x.min_u: -0.0246833171695
	valid_h0_range_x.max_u: 0.0559068731964
	valid_h0_range_x.mean_u: 0.0303960237652
	valid_h0_range_x.min_u: 0.0165484864265
	valid_h1_kernel_norms_max: 0.163002505898
	valid_h1_kernel_norms_mean: 0.160210311413
	valid_h1_kernel_norms_min: 0.157817557454
	valid_h1_max_x.max_u: 0.0124876089394
	valid_h1_max_x.mean_u: 0.00549738807604
	valid_h1_max_x.min_u: -0.0010639752727
	valid_h1_mean_x.max_u: 0.0103793274611
	valid_h1_mean_x.mean_u: 0.00287629244849
	valid_h1_mean_x.min_u: -0.00508263986558
	valid_h1_min_x.max_u: 0.00675621815026
	valid_h1_min_x.mean_u: 0.000497908622492
	valid_h1_min_x.min_u: -0.00762424245477
	valid_h1_range_x.max_u: 0.00757502578199
	valid_h1_range_x.mean_u: 0.00499947974458
	valid_h1_range_x.min_u: 0.00308659533039
	valid_h2_kernel_norms_max: 0.102913297713
	valid_h2_kernel_norms_mean: 0.0999667495489
	valid_h2_kernel_norms_min: 0.0971001237631
	valid_h2_max_x.max_u: 0.00137885136064
	valid_h2_max_x.mean_u: 0.000807397649623
	valid_h2_max_x.min_u: 0.000289376825094
	valid_h2_mean_x.max_u: 0.000732935382985
	valid_h2_mean_x.mean_u: 0.000421148986788
	valid_h2_mean_x.min_u: 5.85719062656e-05
	valid_h2_min_x.max_u: 0.000297168618999
	valid_h2_min_x.mean_u: 5.5023621826e-05
	valid_h2_min_x.min_u: -0.000307764275931
	valid_h2_range_x.max_u: 0.00120884552598
	valid_h2_range_x.mean_u: 0.000752374064177
	valid_h2_range_x.min_u: 0.000442488206318
	valid_objective: 4.79580688477
	valid_y_col_norms_max: 0.0886595696211
	valid_y_col_norms_mean: 0.0852382481098
	valid_y_col_norms_min: 0.0822916552424
	valid_y_max_max_class: 0.00826539844275
	valid_y_mean_max_class: 0.00826532579958
	valid_y_min_max_class: 0.00826526526362
	valid_y_misclass: 0.998980820179
	valid_y_nll: 4.79579162598
	valid_y_row_norms_max: 0.0359390377998
	valid_y_row_norms_mean: 0.0318758152425
	valid_y_row_norms_min: 0.0280178263783
Saving to /disk/scratch/neuroglycerin/models/first_pylearn2_run.pkl...
Saving to /disk/scratch/neuroglycerin/models/first_pylearn2_run.pkl done. Time elapsed: 0.402772 seconds
Time this epoch: 42.365288 seconds
Monitoring step:
	Epochs seen: 1
	Batches seen: 189
	Examples seen: 24192
	learning_rate: 0.0500000156462
	momentum: 0.500000059605
	test_h0_kernel_norms_max: 0.119630277157
	test_h0_kernel_norms_mean: 0.0446750447154
	test_h0_kernel_norms_min: 0.0240400601178
	test_h0_max_x.max_u: 0.0877726972103
	test_h0_max_x.mean_u: -0.0394509211183
	test_h0_max_x.min_u: -0.108581222594
	test_h0_mean_x.max_u: 0.0777599066496
	test_h0_mean_x.mean_u: -0.222826212645
	test_h0_mean_x.min_u: -0.584578573704
	test_h0_min_x.max_u: 0.0195010378957
	test_h0_min_x.mean_u: -0.248172312975
	test_h0_min_x.min_u: -0.646384298801
	test_h0_range_x.max_u: 0.537803173065
	test_h0_range_x.mean_u: 0.208721384406
	test_h0_range_x.min_u: 0.0424815453589
	test_h1_kernel_norms_max: 0.178259134293
	test_h1_kernel_norms_mean: 0.164288386703
	test_h1_kernel_norms_min: 0.157976344228
	test_h1_max_x.max_u: 0.728937506676
	test_h1_max_x.mean_u: 0.406539261341
	test_h1_max_x.min_u: 0.155406236649
	test_h1_mean_x.max_u: 0.575318336487
	test_h1_mean_x.mean_u: 0.320599079132
	test_h1_mean_x.min_u: 0.115812256932
	test_h1_min_x.max_u: 0.190403625369
	test_h1_min_x.mean_u: 0.0893200114369
	test_h1_min_x.min_u: 0.00710412999615
	test_h1_range_x.max_u: 0.565589189529
	test_h1_range_x.mean_u: 0.317219287157
	test_h1_range_x.min_u: 0.112690351903
	test_h2_kernel_norms_max: 0.173589587212
	test_h2_kernel_norms_mean: 0.108563363552
	test_h2_kernel_norms_min: 0.0981491953135
	test_h2_max_x.max_u: 1.1296530962
	test_h2_max_x.mean_u: 0.534217238426
	test_h2_max_x.min_u: 0.111819863319
	test_h2_mean_x.max_u: 0.644700169563
	test_h2_mean_x.mean_u: 0.302310168743
	test_h2_mean_x.min_u: 0.054583966732
	test_h2_min_x.max_u: 0.0786329656839
	test_h2_min_x.mean_u: 0.0263672303408
	test_h2_min_x.min_u: -0.0340515673161
	test_h2_range_x.max_u: 1.09922862053
	test_h2_range_x.mean_u: 0.507849991322
	test_h2_range_x.min_u: 0.128865197301
	test_objective: 4.17824888229
	test_y_col_norms_max: 0.514889061451
	test_y_col_norms_mean: 0.162969008088
	test_y_col_norms_min: 0.101006679237
	test_y_max_max_class: 0.0681242123246
	test_y_mean_max_class: 0.0506275594234
	test_y_min_max_class: 0.041659720242
	test_y_misclass: 0.916015684605
	test_y_nll: 4.17635774612
	test_y_row_norms_max: 0.164149001241
	test_y_row_norms_mean: 0.0595046244562
	test_y_row_norms_min: 0.028547193855
	total_seconds_last_epoch: 0.0
	training_seconds_this_epoch: 42.3652915955
	valid_h0_kernel_norms_max: 0.119630292058
	valid_h0_kernel_norms_mean: 0.0446750298142
	valid_h0_kernel_norms_min: 0.0240400545299
	valid_h0_max_x.max_u: 0.0871249958873
	valid_h0_max_x.mean_u: -0.0393340885639
	valid_h0_max_x.min_u: -0.108536668122
	valid_h0_mean_x.max_u: 0.0778748095036
	valid_h0_mean_x.mean_u: -0.223461583257
	valid_h0_mean_x.min_u: -0.586237847805
	valid_h0_min_x.max_u: 0.0187591761351
	valid_h0_min_x.mean_u: -0.24818123877
	valid_h0_min_x.min_u: -0.646384358406
	valid_h0_range_x.max_u: 0.537847697735
	valid_h0_range_x.mean_u: 0.208847150207
	valid_h0_range_x.min_u: 0.0422600880265
	valid_h1_kernel_norms_max: 0.17825910449
	valid_h1_kernel_norms_mean: 0.164288416505
	valid_h1_kernel_norms_min: 0.157976314425
	valid_h1_max_x.max_u: 0.728963315487
	valid_h1_max_x.mean_u: 0.406164675951
	valid_h1_max_x.min_u: 0.155447885394
	valid_h1_mean_x.max_u: 0.576275587082
	valid_h1_mean_x.mean_u: 0.320993304253
	valid_h1_mean_x.min_u: 0.115926712751
	valid_h1_min_x.max_u: 0.186443910003
	valid_h1_min_x.mean_u: 0.0852651894093
	valid_h1_min_x.min_u: 0.00356428069063
	valid_h1_range_x.max_u: 0.568383038044
	valid_h1_range_x.mean_u: 0.320899426937
	valid_h1_range_x.min_u: 0.112883076072
	valid_h2_kernel_norms_max: 0.173589587212
	valid_h2_kernel_norms_mean: 0.108563423157
	valid_h2_kernel_norms_min: 0.0981492251158
	valid_h2_max_x.max_u: 1.12555992603
	valid_h2_max_x.mean_u: 0.531945824623
	valid_h2_max_x.min_u: 0.111693903804
	valid_h2_mean_x.max_u: 0.645218133926
	valid_h2_mean_x.mean_u: 0.302555888891
	valid_h2_mean_x.min_u: 0.0546179562807
	valid_h2_min_x.max_u: 0.0830293595791
	valid_h2_min_x.mean_u: 0.0270454064012
	valid_h2_min_x.min_u: -0.0341226831079
	valid_h2_range_x.max_u: 1.09422528744
	valid_h2_range_x.mean_u: 0.504900336266
	valid_h2_range_x.min_u: 0.128659635782
	valid_objective: 4.14758968353
	valid_y_col_norms_max: 0.514889240265
	valid_y_col_norms_mean: 0.162969052792
	valid_y_col_norms_min: 0.101006694138
	valid_y_max_max_class: 0.0662094578147
	valid_y_mean_max_class: 0.0503454096615
	valid_y_min_max_class: 0.0423163473606
	valid_y_misclass: 0.912363946438
	valid_y_nll: 4.13866329193
	valid_y_row_norms_max: 0.164148956537
	valid_y_row_norms_mean: 0.0595046319067
	valid_y_row_norms_min: 0.0285471752286
Saving to /disk/scratch/neuroglycerin/models/first_pylearn2_run.pkl...
Saving to /disk/scratch/neuroglycerin/models/first_pylearn2_run.pkl done. Time elapsed: 0.272643 seconds
Time this epoch: 42.344463 seconds
Monitoring step:
	Epochs seen: 2
	Batches seen: 378
	Examples seen: 48384
	learning_rate: 0.0500000156462
	momentum: 0.554444611073
	test_h0_kernel_norms_max: 0.209845691919
	test_h0_kernel_norms_mean: 0.0957242920995
	test_h0_kernel_norms_min: 0.0244844965637
	test_h0_max_x.max_u: 0.200352042913
	test_h0_max_x.mean_u: 0.00634754262865
	test_h0_max_x.min_u: -0.0850978121161
	test_h0_mean_x.max_u: 0.117207296193
	test_h0_mean_x.mean_u: -0.396451234818
	test_h0_mean_x.min_u: -0.804564297199
	test_h0_min_x.max_u: 0.0272604301572
	test_h0_min_x.mean_u: -0.46067199111
	test_h0_min_x.min_u: -0.910667657852
	test_h0_range_x.max_u: 0.873636364937
	test_h0_range_x.mean_u: 0.467019468546
	test_h0_range_x.min_u: 0.0543017201126
	test_h1_kernel_norms_max: 0.501127421856
	test_h1_kernel_norms_mean: 0.22133846581
	test_h1_kernel_norms_min: 0.162283405662
	test_h1_max_x.max_u: 2.85028910637
	test_h1_max_x.mean_u: 1.04021894932
	test_h1_max_x.min_u: -0.0126008475199
	test_h1_mean_x.max_u: 0.865136742592
	test_h1_mean_x.mean_u: -0.116089887917
	test_h1_mean_x.min_u: -1.00601768494
	test_h1_min_x.max_u: -0.113007441163
	test_h1_min_x.mean_u: -1.01708626747
	test_h1_min_x.min_u: -2.24564099312
	test_h1_range_x.max_u: 4.86607980728
	test_h1_range_x.mean_u: 2.057305336
	test_h1_range_x.min_u: 0.257792323828
	test_h2_kernel_norms_max: 0.436911284924
	test_h2_kernel_norms_mean: 0.170230612159
	test_h2_kernel_norms_min: 0.0996099039912
	test_h2_max_x.max_u: 5.733086586
	test_h2_max_x.mean_u: 3.39873337746
	test_h2_max_x.min_u: 0.718877494335
	test_h2_mean_x.max_u: 0.780628621578
	test_h2_mean_x.mean_u: 0.427675038576
	test_h2_mean_x.min_u: 0.0342684164643
	test_h2_min_x.max_u: -0.124309390783
	test_h2_min_x.mean_u: -1.29148459435
	test_h2_min_x.min_u: -2.32623887062
	test_h2_range_x.max_u: 7.97482538223
	test_h2_range_x.mean_u: 4.6902179718
	test_h2_range_x.min_u: 0.883309841156
	test_objective: 3.49535536766
	test_y_col_norms_max: 0.831780970097
	test_y_col_norms_mean: 0.290325641632
	test_y_col_norms_min: 0.148055061698
	test_y_max_max_class: 0.892422378063
	test_y_mean_max_class: 0.374676644802
	test_y_min_max_class: 0.0861578956246
	test_y_misclass: 0.7919921875
	test_y_nll: 3.54511523247
	test_y_row_norms_max: 0.328452318907
	test_y_row_norms_mean: 0.103720292449
	test_y_row_norms_min: 0.0298915319145
	total_seconds_last_epoch: 47.7596664429
	training_seconds_this_epoch: 42.344455719
	valid_h0_kernel_norms_max: 0.209845721722
	valid_h0_kernel_norms_mean: 0.0957242697477
	valid_h0_kernel_norms_min: 0.0244844835252
	valid_h0_max_x.max_u: 0.199420377612
	valid_h0_max_x.mean_u: 0.00478140218183
	valid_h0_max_x.min_u: -0.0860378965735
	valid_h0_mean_x.max_u: 0.117339596152
	valid_h0_mean_x.mean_u: -0.397686719894
	valid_h0_mean_x.min_u: -0.806932985783
	valid_h0_min_x.max_u: 0.024752497673
	valid_h0_min_x.mean_u: -0.46079492569
	valid_h0_min_x.min_u: -0.910667419434
	valid_h0_range_x.max_u: 0.872015595436
	valid_h0_range_x.mean_u: 0.465576380491
	valid_h0_range_x.min_u: 0.0554380491376
	valid_h1_kernel_norms_max: 0.501127481461
	valid_h1_kernel_norms_mean: 0.221338480711
	valid_h1_kernel_norms_min: 0.162283465266
	valid_h1_max_x.max_u: 2.73578166962
	valid_h1_max_x.mean_u: 1.01325666904
	valid_h1_max_x.min_u: -0.015496565029
	valid_h1_mean_x.max_u: 0.861131668091
	valid_h1_mean_x.mean_u: -0.123113930225
	valid_h1_mean_x.min_u: -1.01675236225
	valid_h1_min_x.max_u: -0.128132730722
	valid_h1_min_x.mean_u: -1.01643753052
	valid_h1_min_x.min_u: -2.2457382679
	valid_h1_range_x.max_u: 4.74751996994
	valid_h1_range_x.mean_u: 2.02969408035
	valid_h1_range_x.min_u: 0.255120128393
	valid_h2_kernel_norms_max: 0.436911404133
	valid_h2_kernel_norms_mean: 0.17023062706
	valid_h2_kernel_norms_min: 0.0996099114418
	valid_h2_max_x.max_u: 5.67662525177
	valid_h2_max_x.mean_u: 3.3808825016
	valid_h2_max_x.min_u: 0.705309808254
	valid_h2_mean_x.max_u: 0.783128023148
	valid_h2_mean_x.mean_u: 0.427880227566
	valid_h2_mean_x.min_u: 0.0258177462965
	valid_h2_min_x.max_u: -0.119625985622
	valid_h2_min_x.mean_u: -1.29079389572
	valid_h2_min_x.min_u: -2.28750252724
	valid_h2_range_x.max_u: 7.8768157959
	valid_h2_range_x.mean_u: 4.67167615891
	valid_h2_range_x.min_u: 0.86976402998
	valid_objective: 3.4253821373
	valid_y_col_norms_max: 0.831781148911
	valid_y_col_norms_mean: 0.29032561183
	valid_y_col_norms_min: 0.148055061698
	valid_y_max_max_class: 0.8895637393
	valid_y_mean_max_class: 0.371127307415
	valid_y_min_max_class: 0.0873955860734
	valid_y_misclass: 0.783967316151
	valid_y_nll: 3.46552085876
	valid_y_row_norms_max: 0.328452348709
	valid_y_row_norms_mean: 0.103720247746
	valid_y_row_norms_min: 0.0298915486783
Saving to /disk/scratch/neuroglycerin/models/first_pylearn2_run.pkl...
Saving to /disk/scratch/neuroglycerin/models/first_pylearn2_run.pkl done. Time elapsed: 0.272255 seconds
Time this epoch: 42.376332 seconds
Monitoring step:
	Epochs seen: 3
	Batches seen: 567
	Examples seen: 72576
	learning_rate: 0.0500000156462
	momentum: 0.608888745308
	test_h0_kernel_norms_max: 0.359491884708
	test_h0_kernel_norms_mean: 0.134614363313
	test_h0_kernel_norms_min: 0.024905398488
	test_h0_max_x.max_u: 0.423915982246
	test_h0_max_x.mean_u: 0.0890484005213
	test_h0_max_x.min_u: -0.0862857550383
	test_h0_mean_x.max_u: 0.121149219573
	test_h0_mean_x.mean_u: -0.404546886683
	test_h0_mean_x.min_u: -0.728514194489
	test_h0_min_x.max_u: -0.0107742007822
	test_h0_min_x.mean_u: -0.496399521828
	test_h0_min_x.min_u: -0.863461852074
	test_h0_range_x.max_u: 1.18968904018
	test_h0_range_x.mean_u: 0.585447967052
	test_h0_range_x.min_u: 0.108081080019
	test_h1_kernel_norms_max: 0.617425322533
	test_h1_kernel_norms_mean: 0.278276771307
	test_h1_kernel_norms_min: 0.168387040496
	test_h1_max_x.max_u: 3.59739923477
	test_h1_max_x.mean_u: 1.67295086384
	test_h1_max_x.min_u: 0.00620114803314
	test_h1_mean_x.max_u: 1.05822396278
	test_h1_mean_x.mean_u: -0.0799116566777
	test_h1_mean_x.min_u: -1.12907385826
	test_h1_min_x.max_u: -0.076726295054
	test_h1_min_x.mean_u: -1.39848601818
	test_h1_min_x.min_u: -3.1450252533
	test_h1_range_x.max_u: 5.78718328476
	test_h1_range_x.mean_u: 3.07143688202
	test_h1_range_x.min_u: 0.536547243595
	test_h2_kernel_norms_max: 0.619913458824
	test_h2_kernel_norms_mean: 0.248795241117
	test_h2_kernel_norms_min: 0.100504353642
	test_h2_max_x.max_u: 6.73342561722
	test_h2_max_x.mean_u: 3.97779417038
	test_h2_max_x.min_u: 1.6889333725
	test_h2_mean_x.max_u: 0.673189640045
	test_h2_mean_x.mean_u: 0.349344611168
	test_h2_mean_x.min_u: -0.0794017761946
	test_h2_min_x.max_u: -0.252630829811
	test_h2_min_x.mean_u: -2.25534701347
	test_h2_min_x.min_u: -3.62425899506
	test_h2_range_x.max_u: 9.86682987213
	test_h2_range_x.mean_u: 6.2331404686
	test_h2_range_x.min_u: 1.9765740633
	test_objective: 3.38402199745
	test_y_col_norms_max: 1.02679502964
	test_y_col_norms_mean: 0.416194468737
	test_y_col_norms_min: 0.178296118975
	test_y_max_max_class: 0.889362454414
	test_y_mean_max_class: 0.445143610239
	test_y_min_max_class: 0.121569037437
	test_y_misclass: 0.767252624035
	test_y_nll: 3.57071065903
	test_y_row_norms_max: 0.423833578825
	test_y_row_norms_mean: 0.151956483722
	test_y_row_norms_min: 0.0329562090337
	total_seconds_last_epoch: 47.7502403259
	training_seconds_this_epoch: 42.3763389587
	valid_h0_kernel_norms_max: 0.359492003918
	valid_h0_kernel_norms_mean: 0.13461433351
	valid_h0_kernel_norms_min: 0.0249053966254
	valid_h0_max_x.max_u: 0.412712156773
	valid_h0_max_x.mean_u: 0.0861949026585
	valid_h0_max_x.min_u: -0.0869294703007
	valid_h0_mean_x.max_u: 0.121100381017
	valid_h0_mean_x.mean_u: -0.405968815088
	valid_h0_mean_x.min_u: -0.731344103813
	valid_h0_min_x.max_u: -0.011479396373
	valid_h0_min_x.mean_u: -0.495568722486
	valid_h0_min_x.min_u: -0.863550662994
	valid_h0_range_x.max_u: 1.1776227951
	valid_h0_range_x.mean_u: 0.581763625145
	valid_h0_range_x.min_u: 0.108674034476
	valid_h1_kernel_norms_max: 0.617425024509
	valid_h1_kernel_norms_mean: 0.278276890516
	valid_h1_kernel_norms_min: 0.168387085199
	valid_h1_max_x.max_u: 3.46933794022
	valid_h1_max_x.mean_u: 1.634745121
	valid_h1_max_x.min_u: -0.0142243849114
	valid_h1_mean_x.max_u: 1.05815958977
	valid_h1_mean_x.mean_u: -0.08995449543
	valid_h1_mean_x.min_u: -1.1476982832
	valid_h1_min_x.max_u: -0.0819198489189
	valid_h1_min_x.mean_u: -1.39712274075
	valid_h1_min_x.min_u: -3.13098526001
	valid_h1_range_x.max_u: 5.65823078156
	valid_h1_range_x.mean_u: 3.03186798096
	valid_h1_range_x.min_u: 0.529259443283
	valid_h2_kernel_norms_max: 0.619913220406
	valid_h2_kernel_norms_mean: 0.248795226216
	valid_h2_kernel_norms_min: 0.100504390895
	valid_h2_max_x.max_u: 6.68678617477
	valid_h2_max_x.mean_u: 3.95872044563
	valid_h2_max_x.min_u: 1.6506909132
	valid_h2_mean_x.max_u: 0.684168934822
	valid_h2_mean_x.mean_u: 0.353794693947
	valid_h2_mean_x.min_u: -0.0889124572277
	valid_h2_min_x.max_u: -0.251966834068
	valid_h2_min_x.mean_u: -2.23872900009
	valid_h2_min_x.min_u: -3.58449077606
	valid_h2_range_x.max_u: 9.84970664978
	valid_h2_range_x.mean_u: 6.19744825363
	valid_h2_range_x.min_u: 1.96390032768
	valid_objective: 3.3347492218
	valid_y_col_norms_max: 1.02679443359
	valid_y_col_norms_mean: 0.416194468737
	valid_y_col_norms_min: 0.178296133876
	valid_y_max_max_class: 0.869118571281
	valid_y_mean_max_class: 0.442211717367
	valid_y_min_max_class: 0.119910597801
	valid_y_misclass: 0.760190188885
	valid_y_nll: 3.51235342026
	valid_y_row_norms_max: 0.42383363843
	valid_y_row_norms_mean: 0.151956483722
	valid_y_row_norms_min: 0.0329562090337
Saving to /disk/scratch/neuroglycerin/models/first_pylearn2_run.pkl...
Saving to /disk/scratch/neuroglycerin/models/first_pylearn2_run.pkl done. Time elapsed: 0.273824 seconds
Time this epoch: 42.388099 seconds
Monitoring step:
	Epochs seen: 4
	Batches seen: 756
	Examples seen: 96768
	learning_rate: 0.0500000156462
	momentum: 0.66333335638
	test_h0_kernel_norms_max: 0.535991132259
	test_h0_kernel_norms_mean: 0.171290040016
	test_h0_kernel_norms_min: 0.024702694267
	test_h0_max_x.max_u: 0.740340292454
	test_h0_max_x.mean_u: 0.183671623468
	test_h0_max_x.min_u: -0.076398961246
	test_h0_mean_x.max_u: -0.0416524931788
	test_h0_mean_x.mean_u: -0.35616850853
	test_h0_mean_x.min_u: -0.663487792015
	test_h0_min_x.max_u: -0.0539095699787
	test_h0_min_x.mean_u: -0.46822822094
	test_h0_min_x.min_u: -0.921264529228
	test_h0_range_x.max_u: 1.5639591217
	test_h0_range_x.mean_u: 0.651899695396
	test_h0_range_x.min_u: 0.115356437862
	test_h1_kernel_norms_max: 0.684282183647
	test_h1_kernel_norms_mean: 0.346445083618
	test_h1_kernel_norms_min: 0.176242485642
	test_h1_max_x.max_u: 3.49669742584
	test_h1_max_x.mean_u: 1.88570189476
	test_h1_max_x.min_u: 0.168029218912
	test_h1_mean_x.max_u: 0.96785825491
	test_h1_mean_x.mean_u: -0.0977243930101
	test_h1_mean_x.min_u: -1.26161932945
	test_h1_min_x.max_u: -0.207417115569
	test_h1_min_x.mean_u: -1.45882332325
	test_h1_min_x.min_u: -3.07610177994
	test_h1_range_x.max_u: 5.17167949677
	test_h1_range_x.mean_u: 3.34452581406
	test_h1_range_x.min_u: 1.04329109192
	test_h2_kernel_norms_max: 0.818537294865
	test_h2_kernel_norms_mean: 0.38146084547
	test_h2_kernel_norms_min: 0.122520282865
	test_h2_max_x.max_u: 6.13806724548
	test_h2_max_x.mean_u: 3.65382933617
	test_h2_max_x.min_u: 1.94014763832
	test_h2_mean_x.max_u: 0.623040258884
	test_h2_mean_x.mean_u: 0.21900857985
	test_h2_mean_x.min_u: -0.314087599516
	test_h2_min_x.max_u: -0.503148674965
	test_h2_min_x.mean_u: -2.40146183968
	test_h2_min_x.min_u: -3.71244502068
	test_h2_range_x.max_u: 8.82101535797
	test_h2_range_x.mean_u: 6.05529165268
	test_h2_range_x.min_u: 2.67890644073
	test_objective: 3.05075836182
	test_y_col_norms_max: 1.17799651623
	test_y_col_norms_mean: 0.529372990131
	test_y_col_norms_min: 0.227641910315
	test_y_max_max_class: 0.93388569355
	test_y_mean_max_class: 0.516840696335
	test_y_min_max_class: 0.122493587434
	test_y_misclass: 0.713541567326
	test_y_nll: 3.26237106323
	test_y_row_norms_max: 0.519736468792
	test_y_row_norms_mean: 0.196485057473
	test_y_row_norms_min: 0.0358680747449
	total_seconds_last_epoch: 47.779548645
	training_seconds_this_epoch: 42.3880958557
	valid_h0_kernel_norms_max: 0.535991072655
	valid_h0_kernel_norms_mean: 0.171290010214
	valid_h0_kernel_norms_min: 0.0247026830912
	valid_h0_max_x.max_u: 0.740047574043
	valid_h0_max_x.mean_u: 0.180688634515
	valid_h0_max_x.min_u: -0.078162394464
	valid_h0_mean_x.max_u: -0.0417144857347
	valid_h0_mean_x.mean_u: -0.357597321272
	valid_h0_mean_x.min_u: -0.667439103127
	valid_h0_min_x.max_u: -0.0539243780077
	valid_h0_min_x.mean_u: -0.467552632093
	valid_h0_min_x.min_u: -0.924739778042
	valid_h0_range_x.max_u: 1.54138708115
	valid_h0_range_x.mean_u: 0.648241400719
	valid_h0_range_x.min_u: 0.114996165037
	valid_h1_kernel_norms_max: 0.684282183647
	valid_h1_kernel_norms_mean: 0.34644523263
	valid_h1_kernel_norms_min: 0.176242440939
	valid_h1_max_x.max_u: 3.39933252335
	valid_h1_max_x.mean_u: 1.83645772934
	valid_h1_max_x.min_u: 0.175201371312
	valid_h1_mean_x.max_u: 0.961535811424
	valid_h1_mean_x.mean_u: -0.108643122017
	valid_h1_mean_x.min_u: -1.27830088139
	valid_h1_min_x.max_u: -0.206127047539
	valid_h1_min_x.mean_u: -1.45465874672
	valid_h1_min_x.min_u: -3.06814908981
	valid_h1_range_x.max_u: 5.05137586594
	valid_h1_range_x.mean_u: 3.29111647606
	valid_h1_range_x.min_u: 1.02838253975
	valid_h2_kernel_norms_max: 0.818537354469
	valid_h2_kernel_norms_mean: 0.381460815668
	valid_h2_kernel_norms_min: 0.122520335019
	valid_h2_max_x.max_u: 5.98397874832
	valid_h2_max_x.mean_u: 3.59713220596
	valid_h2_max_x.min_u: 1.89372837543
	valid_h2_mean_x.max_u: 0.626972794533
	valid_h2_mean_x.mean_u: 0.224481761456
	valid_h2_mean_x.min_u: -0.299534231424
	valid_h2_min_x.max_u: -0.499290496111
	valid_h2_min_x.mean_u: -2.39320921898
	valid_h2_min_x.min_u: -3.75206446648
	valid_h2_range_x.max_u: 8.58625030518
	valid_h2_range_x.mean_u: 5.99034118652
	valid_h2_range_x.min_u: 2.63856244087
	valid_objective: 3.00071382523
	valid_y_col_norms_max: 1.17799651623
	valid_y_col_norms_mean: 0.529372990131
	valid_y_col_norms_min: 0.227641835809
	valid_y_max_max_class: 0.935289204121
	valid_y_mean_max_class: 0.517929375172
	valid_y_min_max_class: 0.128187343478
	valid_y_misclass: 0.712975561619
	valid_y_nll: 3.18759393692
	valid_y_row_norms_max: 0.519736647606
	valid_y_row_norms_mean: 0.196485117078
	valid_y_row_norms_min: 0.0358680672944
Saving to /disk/scratch/neuroglycerin/models/first_pylearn2_run.pkl...
Saving to /disk/scratch/neuroglycerin/models/first_pylearn2_run.pkl done. Time elapsed: 0.277758 seconds
Time this epoch: 42.368445 seconds
Monitoring step:
	Epochs seen: 5
	Batches seen: 945
	Examples seen: 120960
	learning_rate: 0.0500000156462
	momentum: 0.717777788639
	test_h0_kernel_norms_max: 0.900000452995
	test_h0_kernel_norms_mean: 0.900000214577
	test_h0_kernel_norms_min: 0.900000095367
	test_h0_max_x.max_u: 1.939e+06
	test_h0_max_x.mean_u: 3.320e+05
	test_h0_max_x.min_u: 1.990e+04
	test_h0_mean_x.max_u: 4.637e+05
	test_h0_mean_x.mean_u: 4.917e+04
	test_h0_mean_x.min_u: -8.022e+04
	test_h0_min_x.max_u: 2208.58837891
	test_h0_min_x.mean_u: -9.869e+04
	test_h0_min_x.min_u: -1.054e+06
	test_h0_range_x.max_u: 2.992e+06
	test_h0_range_x.mean_u: 4.306e+05
	test_h0_range_x.min_u: 4.431e+04
	test_h1_kernel_norms_max: 1.93650281429
	test_h1_kernel_norms_mean: 1.9365003109
	test_h1_kernel_norms_min: 1.93649756908
	test_h1_max_x.max_u: 1.533e+07
	test_h1_max_x.mean_u: 4.080e+06
	test_h1_max_x.min_u: -5.492e+05
	test_h1_mean_x.max_u: 1.188e+07
	test_h1_mean_x.mean_u: 6.131e+05
	test_h1_mean_x.min_u: -6.223e+06
	test_h1_min_x.max_u: 5.085e+06
	test_h1_min_x.mean_u: -3.631e+06
	test_h1_min_x.min_u: -1.278e+07
	test_h1_range_x.max_u: 1.267e+07
	test_h1_range_x.mean_u: 7.710e+06
	test_h1_range_x.min_u: 3.007e+06
	test_h2_kernel_norms_max: 1.93650114536
	test_h2_kernel_norms_mean: 1.9365003109
	test_h2_kernel_norms_min: 1.93649792671
	test_h2_max_x.max_u: 1.391e+08
	test_h2_max_x.mean_u: 2.639e+07
	test_h2_max_x.min_u: -3.500e+06
	test_h2_mean_x.max_u: 5.973e+07
	test_h2_mean_x.mean_u: -9.866e+06
	test_h2_mean_x.min_u: -4.494e+07
	test_h2_min_x.max_u: 9.322e+06
	test_h2_min_x.mean_u: -7.069e+07
	test_h2_min_x.min_u: -1.410e+08
	test_h2_range_x.max_u: 1.527e+08
	test_h2_range_x.mean_u: 9.708e+07
	test_h2_range_x.min_u: 3.226e+07
	test_objective: 1.218e+14
	test_y_col_norms_max: 2.399e+05
	test_y_col_norms_mean: 2.458e+04
	test_y_col_norms_min: 1.99148583412
	test_y_max_max_class: 1.00000011921
	test_y_mean_max_class: 1.00000011921
	test_y_min_max_class: 1.00000011921
	test_y_misclass: 0.998698055744
	test_y_nll: 1.204e+14
	test_y_row_norms_max: 7.442e+04
	test_y_row_norms_mean: 1.593e+04
	test_y_row_norms_min: 1282.77807617
	total_seconds_last_epoch: 47.797203064
	training_seconds_this_epoch: 42.3684425354
	valid_h0_kernel_norms_max: 0.900000274181
	valid_h0_kernel_norms_mean: 0.900000035763
	valid_h0_kernel_norms_min: 0.899999976158
	valid_h0_max_x.max_u: 1.939e+06
	valid_h0_max_x.mean_u: 3.320e+05
	valid_h0_max_x.min_u: 1.990e+04
	valid_h0_mean_x.max_u: 4.637e+05
	valid_h0_mean_x.mean_u: 4.917e+04
	valid_h0_mean_x.min_u: -8.022e+04
	valid_h0_min_x.max_u: 2208.72729492
	valid_h0_min_x.mean_u: -9.869e+04
	valid_h0_min_x.min_u: -1.054e+06
	valid_h0_range_x.max_u: 2.992e+06
	valid_h0_range_x.mean_u: 4.306e+05
	valid_h0_range_x.min_u: 4.431e+04
	valid_h1_kernel_norms_max: 1.93650209904
	valid_h1_kernel_norms_mean: 1.93649935722
	valid_h1_kernel_norms_min: 1.93649697304
	valid_h1_max_x.max_u: 1.533e+07
	valid_h1_max_x.mean_u: 4.080e+06
	valid_h1_max_x.min_u: -5.492e+05
	valid_h1_mean_x.max_u: 1.188e+07
	valid_h1_mean_x.mean_u: 6.131e+05
	valid_h1_mean_x.min_u: -6.223e+06
	valid_h1_min_x.max_u: 5.085e+06
	valid_h1_min_x.mean_u: -3.631e+06
	valid_h1_min_x.min_u: -1.278e+07
	valid_h1_range_x.max_u: 1.267e+07
	valid_h1_range_x.mean_u: 7.710e+06
	valid_h1_range_x.min_u: 3.007e+06
	valid_h2_kernel_norms_max: 1.93650174141
	valid_h2_kernel_norms_mean: 1.93649971485
	valid_h2_kernel_norms_min: 1.93649888039
	valid_h2_max_x.max_u: 1.391e+08
	valid_h2_max_x.mean_u: 2.639e+07
	valid_h2_max_x.min_u: -3.500e+06
	valid_h2_mean_x.max_u: 5.973e+07
	valid_h2_mean_x.mean_u: -9.866e+06
	valid_h2_mean_x.min_u: -4.494e+07
	valid_h2_min_x.max_u: 9.322e+06
	valid_h2_min_x.mean_u: -7.069e+07
	valid_h2_min_x.min_u: -1.410e+08
	valid_h2_range_x.max_u: 1.527e+08
	valid_h2_range_x.mean_u: 9.708e+07
	valid_h2_range_x.min_u: 3.226e+07
	valid_objective: 1.222e+14
	valid_y_col_norms_max: 2.399e+05
	valid_y_col_norms_mean: 2.458e+04
	valid_y_col_norms_min: 1.99148595333
	valid_y_max_max_class: 0.999999821186
	valid_y_mean_max_class: 0.999999821186
	valid_y_min_max_class: 0.999999821186
	valid_y_misclass: 0.998980820179
	valid_y_nll: 1.211e+14
	valid_y_row_norms_max: 7.442e+04
	valid_y_row_norms_mean: 1.593e+04
	valid_y_row_norms_min: 1282.77770996
Time this epoch: 42.331841 seconds
Monitoring step:
	Epochs seen: 6
	Batches seen: 1134
	Examples seen: 145152
	learning_rate: 0.0500000156462
	momentum: 0.772222042084
	test_h0_kernel_norms_max: 0.900000452995
	test_h0_kernel_norms_mean: 0.900000214577
	test_h0_kernel_norms_min: 0.900000095367
	test_h0_max_x.max_u: 1.567e+07
	test_h0_max_x.mean_u: 4.923e+06
	test_h0_max_x.min_u: 8.501e+05
	test_h0_mean_x.max_u: 4.578e+06
	test_h0_mean_x.mean_u: 5.420e+05
	test_h0_mean_x.min_u: -8.016e+04
	test_h0_min_x.max_u: -3.367e+05
	test_h0_min_x.mean_u: -2.271e+06
	test_h0_min_x.min_u: -8.127e+06
	test_h0_range_x.max_u: 2.380e+07
	test_h0_range_x.mean_u: 7.194e+06
	test_h0_range_x.min_u: 1.187e+06
	test_h1_kernel_norms_max: 1.93650329113
	test_h1_kernel_norms_mean: 1.9365003109
	test_h1_kernel_norms_min: 1.93649744987
	test_h1_max_x.max_u: 1.658e+08
	test_h1_max_x.mean_u: 2.355e+07
	test_h1_max_x.min_u: -1.464e+07
	test_h1_mean_x.max_u: 1.071e+08
	test_h1_mean_x.mean_u: -1.907e+07
	test_h1_mean_x.min_u: -6.891e+07
	test_h1_min_x.max_u: 5.825e+07
	test_h1_min_x.mean_u: -5.711e+07
	test_h1_min_x.min_u: -1.192e+08
	test_h1_range_x.max_u: 1.322e+08
	test_h1_range_x.mean_u: 8.067e+07
	test_h1_range_x.min_u: 3.225e+07
	test_h2_kernel_norms_max: 1.93650126457
	test_h2_kernel_norms_mean: 1.9365003109
	test_h2_kernel_norms_min: 1.93649792671
	test_h2_max_x.max_u: 2.858e+09
	test_h2_max_x.mean_u: 1.880e+09
	test_h2_max_x.min_u: 1.499e+09
	test_h2_mean_x.max_u: 1.312e+09
	test_h2_mean_x.mean_u: 8.897e+08
	test_h2_mean_x.min_u: 7.339e+08
	test_h2_min_x.max_u: 1.852e+08
	test_h2_min_x.mean_u: 1.283e+08
	test_h2_min_x.min_u: 7.229e+07
	test_h2_range_x.max_u: 2.706e+09
	test_h2_range_x.mean_u: 1.752e+09
	test_h2_range_x.min_u: 1.387e+09
	test_objective: 4.022e+14
	test_y_col_norms_max: 5.830e+05
	test_y_col_norms_mean: 1.264e+04
	test_y_col_norms_min: 3.1719892025
	test_y_max_max_class: 1.00000011921
	test_y_mean_max_class: 1.00000011921
	test_y_min_max_class: 1.00000011921
	test_y_misclass: 0.999023616314
	test_y_nll: 4.138e+14
	test_y_row_norms_max: 6.027e+04
	test_y_row_norms_mean: 1.818e+04
	test_y_row_norms_min: 1171.07324219
	total_seconds_last_epoch: 47.4932518005
	training_seconds_this_epoch: 42.3318443298
	valid_h0_kernel_norms_max: 0.900000274181
	valid_h0_kernel_norms_mean: 0.900000035763
	valid_h0_kernel_norms_min: 0.899999976158
	valid_h0_max_x.max_u: 1.567e+07
	valid_h0_max_x.mean_u: 4.923e+06
	valid_h0_max_x.min_u: 8.501e+05
	valid_h0_mean_x.max_u: 4.578e+06
	valid_h0_mean_x.mean_u: 5.420e+05
	valid_h0_mean_x.min_u: -8.016e+04
	valid_h0_min_x.max_u: -3.367e+05
	valid_h0_min_x.mean_u: -2.271e+06
	valid_h0_min_x.min_u: -8.127e+06
	valid_h0_range_x.max_u: 2.380e+07
	valid_h0_range_x.mean_u: 7.194e+06
	valid_h0_range_x.min_u: 1.187e+06
	valid_h1_kernel_norms_max: 1.93650245667
	valid_h1_kernel_norms_mean: 1.93649971485
	valid_h1_kernel_norms_min: 1.9364964962
	valid_h1_max_x.max_u: 1.658e+08
	valid_h1_max_x.mean_u: 2.355e+07
	valid_h1_max_x.min_u: -1.464e+07
	valid_h1_mean_x.max_u: 1.071e+08
	valid_h1_mean_x.mean_u: -1.907e+07
	valid_h1_mean_x.min_u: -6.891e+07
	valid_h1_min_x.max_u: 5.825e+07
	valid_h1_min_x.mean_u: -5.711e+07
	valid_h1_min_x.min_u: -1.192e+08
	valid_h1_range_x.max_u: 1.322e+08
	valid_h1_range_x.mean_u: 8.067e+07
	valid_h1_range_x.min_u: 3.225e+07
	valid_h2_kernel_norms_max: 1.93650186062
	valid_h2_kernel_norms_mean: 1.93649971485
	valid_h2_kernel_norms_min: 1.93649852276
	valid_h2_max_x.max_u: 2.858e+09
	valid_h2_max_x.mean_u: 1.880e+09
	valid_h2_max_x.min_u: 1.499e+09
	valid_h2_mean_x.max_u: 1.312e+09
	valid_h2_mean_x.mean_u: 8.897e+08
	valid_h2_mean_x.min_u: 7.339e+08
	valid_h2_min_x.max_u: 1.852e+08
	valid_h2_min_x.mean_u: 1.283e+08
	valid_h2_min_x.min_u: 7.229e+07
	valid_h2_range_x.max_u: 2.706e+09
	valid_h2_range_x.mean_u: 1.752e+09
	valid_h2_range_x.min_u: 1.387e+09
	valid_objective: 3.945e+14
	valid_y_col_norms_max: 5.830e+05
	valid_y_col_norms_mean: 1.264e+04
	valid_y_col_norms_min: 3.1719892025
	valid_y_max_max_class: 0.999999821186
	valid_y_mean_max_class: 0.999999821186
	valid_y_min_max_class: 0.999999821186
	valid_y_misclass: 0.99932050705
	valid_y_nll: 4.071e+14
	valid_y_row_norms_max: 6.027e+04
	valid_y_row_norms_mean: 1.818e+04
	valid_y_row_norms_min: 1171.07299805
Time this epoch: 42.346430 seconds
Monitoring step:
	Epochs seen: 7
	Batches seen: 1323
	Examples seen: 169344
	learning_rate: 0.0500000156462
	momentum: 0.826666772366
	test_h0_kernel_norms_max: 0.900000452995
	test_h0_kernel_norms_mean: 0.900000214577
	test_h0_kernel_norms_min: 0.899999499321
	test_h0_max_x.max_u: 2.775e+07
	test_h0_max_x.mean_u: 7.419e+06
	test_h0_max_x.min_u: 5.327e+05
	test_h0_mean_x.max_u: 5.297e+06
	test_h0_mean_x.mean_u: 5.323e+05
	test_h0_mean_x.min_u: -1.295e+06
	test_h0_min_x.max_u: -4.760e+05
	test_h0_min_x.mean_u: -3.821e+06
	test_h0_min_x.min_u: -1.306e+07
	test_h0_range_x.max_u: 3.382e+07
	test_h0_range_x.mean_u: 1.124e+07
	test_h0_range_x.min_u: 1.009e+06
	test_h1_kernel_norms_max: 1.93650269508
	test_h1_kernel_norms_mean: 1.9365003109
	test_h1_kernel_norms_min: 1.9364978075
	test_h1_max_x.max_u: 2.397e+08
	test_h1_max_x.mean_u: 9.978e+07
	test_h1_max_x.min_u: 2.108e+07
	test_h1_mean_x.max_u: 1.348e+08
	test_h1_mean_x.mean_u: 2.642e+07
	test_h1_mean_x.min_u: -5.949e+07
	test_h1_min_x.max_u: 1.362e+07
	test_h1_min_x.mean_u: -7.169e+07
	test_h1_min_x.min_u: -2.300e+08
	test_h1_range_x.max_u: 2.599e+08
	test_h1_range_x.mean_u: 1.715e+08
	test_h1_range_x.min_u: 6.708e+07
	test_h2_kernel_norms_max: 1.93650126457
	test_h2_kernel_norms_mean: 1.9365003109
	test_h2_kernel_norms_min: 1.93649792671
	test_h2_max_x.max_u: 2.937e+09
	test_h2_max_x.mean_u: 6.699e+08
	test_h2_max_x.min_u: -5.126e+07
	test_h2_mean_x.max_u: 1.268e+09
	test_h2_mean_x.mean_u: 1.429e+08
	test_h2_mean_x.min_u: -4.167e+08
	test_h2_min_x.max_u: 1.304e+08
	test_h2_min_x.mean_u: -3.504e+08
	test_h2_min_x.min_u: -1.094e+09
	test_h2_range_x.max_u: 2.806e+09
	test_h2_range_x.mean_u: 1.020e+09
	test_h2_range_x.min_u: 4.722e+08
	test_objective: 1.559e+16
	test_y_col_norms_max: 1.830e+06
	test_y_col_norms_mean: 8.272e+04
	test_y_col_norms_min: 418.869384766
	test_y_max_max_class: 1.00000011921
	test_y_mean_max_class: 1.00000011921
	test_y_min_max_class: 1.00000011921
	test_y_misclass: 0.999674618244
	test_y_nll: 1.471e+16
	test_y_row_norms_max: 3.764e+05
	test_y_row_norms_mean: 6.468e+04
	test_y_row_norms_min: 3372.04663086
	total_seconds_last_epoch: 47.4537658691
	training_seconds_this_epoch: 42.3464317322
	valid_h0_kernel_norms_max: 0.900000274181
	valid_h0_kernel_norms_mean: 0.900000035763
	valid_h0_kernel_norms_min: 0.899999976158
	valid_h0_max_x.max_u: 2.775e+07
	valid_h0_max_x.mean_u: 7.419e+06
	valid_h0_max_x.min_u: 5.327e+05
	valid_h0_mean_x.max_u: 5.297e+06
	valid_h0_mean_x.mean_u: 5.323e+05
	valid_h0_mean_x.min_u: -1.295e+06
	valid_h0_min_x.max_u: -4.760e+05
	valid_h0_min_x.mean_u: -3.821e+06
	valid_h0_min_x.min_u: -1.306e+07
	valid_h0_range_x.max_u: 3.382e+07
	valid_h0_range_x.mean_u: 1.124e+07
	valid_h0_range_x.min_u: 1.009e+06
	valid_h1_kernel_norms_max: 1.93650197983
	valid_h1_kernel_norms_mean: 1.93649971485
	valid_h1_kernel_norms_min: 1.93649852276
	valid_h1_max_x.max_u: 2.397e+08
	valid_h1_max_x.mean_u: 9.978e+07
	valid_h1_max_x.min_u: 2.108e+07
	valid_h1_mean_x.max_u: 1.348e+08
	valid_h1_mean_x.mean_u: 2.642e+07
	valid_h1_mean_x.min_u: -5.949e+07
	valid_h1_min_x.max_u: 1.362e+07
	valid_h1_min_x.mean_u: -7.169e+07
	valid_h1_min_x.min_u: -2.300e+08
	valid_h1_range_x.max_u: 2.599e+08
	valid_h1_range_x.mean_u: 1.715e+08
	valid_h1_range_x.min_u: 6.708e+07
	valid_h2_kernel_norms_max: 1.93650186062
	valid_h2_kernel_norms_mean: 1.93649971485
	valid_h2_kernel_norms_min: 1.93649852276
	valid_h2_max_x.max_u: 2.937e+09
	valid_h2_max_x.mean_u: 6.699e+08
	valid_h2_max_x.min_u: -5.126e+07
	valid_h2_mean_x.max_u: 1.268e+09
	valid_h2_mean_x.mean_u: 1.429e+08
	valid_h2_mean_x.min_u: -4.167e+08
	valid_h2_min_x.max_u: 1.304e+08
	valid_h2_min_x.mean_u: -3.504e+08
	valid_h2_min_x.min_u: -1.094e+09
	valid_h2_range_x.max_u: 2.806e+09
	valid_h2_range_x.mean_u: 1.020e+09
	valid_h2_range_x.min_u: 4.722e+08
	valid_objective: 1.570e+16
	valid_y_col_norms_max: 1.830e+06
	valid_y_col_norms_mean: 8.272e+04
	valid_y_col_norms_min: 418.869598389
	valid_y_max_max_class: 0.999999821186
	valid_y_mean_max_class: 0.999999821186
	valid_y_min_max_class: 0.999999821186
	valid_y_misclass: 0.999660134315
	valid_y_nll: 1.470e+16
	valid_y_row_norms_max: 3.764e+05
	valid_y_row_norms_mean: 6.468e+04
	valid_y_row_norms_min: 3372.04516602
Time this epoch: 42.350535 seconds
Monitoring step:
	Epochs seen: 8
	Batches seen: 1512
	Examples seen: 193536
	learning_rate: 0.0500000156462
	momentum: 0.881110966206
	test_h0_kernel_norms_max: 0.900000452995
	test_h0_kernel_norms_mean: 0.900000214577
	test_h0_kernel_norms_min: 0.900000095367
	test_h0_max_x.max_u: 4.568e+06
	test_h0_max_x.mean_u: 1.912e+06
	test_h0_max_x.min_u: 2.465e+05
	test_h0_mean_x.max_u: 1.773e+05
	test_h0_mean_x.mean_u: -1321.26171875
	test_h0_mean_x.min_u: -1.968e+05
	test_h0_min_x.max_u: -2.356e+05
	test_h0_min_x.mean_u: -1.992e+06
	test_h0_min_x.min_u: -5.238e+06
	test_h0_range_x.max_u: 8.701e+06
	test_h0_range_x.mean_u: 3.904e+06
	test_h0_range_x.min_u: 4.821e+05
	test_h1_kernel_norms_max: 1.93650317192
	test_h1_kernel_norms_mean: 1.9365003109
	test_h1_kernel_norms_min: 1.93649744987
	test_h1_max_x.max_u: 3.285e+07
	test_h1_max_x.mean_u: 1.631e+07
	test_h1_max_x.min_u: 4.165e+06
	test_h1_mean_x.max_u: 7.954e+06
	test_h1_mean_x.mean_u: 2.687e+06
	test_h1_mean_x.min_u: -5.522e+05
	test_h1_min_x.max_u: -5.373e+05
	test_h1_min_x.mean_u: -3.747e+06
	test_h1_min_x.min_u: -7.108e+06
	test_h1_range_x.max_u: 3.514e+07
	test_h1_range_x.mean_u: 2.006e+07
	test_h1_range_x.min_u: 9.676e+06
	test_h2_kernel_norms_max: 1.93650126457
	test_h2_kernel_norms_mean: 1.9365003109
	test_h2_kernel_norms_min: 1.93649792671
	test_h2_max_x.max_u: 3.863e+08
	test_h2_max_x.mean_u: 1.755e+08
	test_h2_max_x.min_u: 1.072e+07
	test_h2_mean_x.max_u: 1.219e+08
	test_h2_mean_x.mean_u: 4.366e+07
	test_h2_mean_x.min_u: -3.361e+07
	test_h2_min_x.max_u: 1.804e+07
	test_h2_min_x.mean_u: -4.967e+07
	test_h2_min_x.min_u: -2.115e+08
	test_h2_range_x.max_u: 3.840e+08
	test_h2_range_x.mean_u: 2.251e+08
	test_h2_range_x.min_u: 8.961e+07
	test_objective: 4.762e+12
	test_y_col_norms_max: 2.928e+04
	test_y_col_norms_mean: 1871.82702637
	test_y_col_norms_min: 39.0379905701
	test_y_max_max_class: 1.00000011921
	test_y_mean_max_class: 1.00000011921
	test_y_min_max_class: 1.00000011921
	test_y_misclass: 0.999023616314
	test_y_nll: 4.159e+12
	test_y_row_norms_max: 4949.11083984
	test_y_row_norms_mean: 1152.45812988
	test_y_row_norms_min: 97.2359542847
	total_seconds_last_epoch: 47.4625778198
	training_seconds_this_epoch: 42.3505477905
	valid_h0_kernel_norms_max: 0.900000274181
	valid_h0_kernel_norms_mean: 0.900000035763
	valid_h0_kernel_norms_min: 0.899999976158
	valid_h0_max_x.max_u: 4.568e+06
	valid_h0_max_x.mean_u: 1.912e+06
	valid_h0_max_x.min_u: 2.465e+05
	valid_h0_mean_x.max_u: 1.773e+05
	valid_h0_mean_x.mean_u: -1321.25866699
	valid_h0_mean_x.min_u: -1.968e+05
	valid_h0_min_x.max_u: -2.356e+05
	valid_h0_min_x.mean_u: -1.992e+06
	valid_h0_min_x.min_u: -5.238e+06
	valid_h0_range_x.max_u: 8.701e+06
	valid_h0_range_x.mean_u: 3.904e+06
	valid_h0_range_x.min_u: 4.821e+05
	valid_h1_kernel_norms_max: 1.93650245667
	valid_h1_kernel_norms_mean: 1.93649971485
	valid_h1_kernel_norms_min: 1.93649661541
	valid_h1_max_x.max_u: 3.285e+07
	valid_h1_max_x.mean_u: 1.631e+07
	valid_h1_max_x.min_u: 4.165e+06
	valid_h1_mean_x.max_u: 7.954e+06
	valid_h1_mean_x.mean_u: 2.687e+06
	valid_h1_mean_x.min_u: -5.522e+05
	valid_h1_min_x.max_u: -5.373e+05
	valid_h1_min_x.mean_u: -3.747e+06
	valid_h1_min_x.min_u: -7.108e+06
	valid_h1_range_x.max_u: 3.514e+07
	valid_h1_range_x.mean_u: 2.006e+07
	valid_h1_range_x.min_u: 9.676e+06
	valid_h2_kernel_norms_max: 1.93650174141
	valid_h2_kernel_norms_mean: 1.93649971485
	valid_h2_kernel_norms_min: 1.93649852276
	valid_h2_max_x.max_u: 3.863e+08
	valid_h2_max_x.mean_u: 1.755e+08
	valid_h2_max_x.min_u: 1.072e+07
	valid_h2_mean_x.max_u: 1.219e+08
	valid_h2_mean_x.mean_u: 4.366e+07
	valid_h2_mean_x.min_u: -3.361e+07
	valid_h2_min_x.max_u: 1.804e+07
	valid_h2_min_x.mean_u: -4.967e+07
	valid_h2_min_x.min_u: -2.115e+08
	valid_h2_range_x.max_u: 3.840e+08
	valid_h2_range_x.mean_u: 2.251e+08
	valid_h2_range_x.min_u: 8.961e+07
	valid_objective: 4.795e+12
	valid_y_col_norms_max: 2.928e+04
	valid_y_col_norms_mean: 1871.82702637
	valid_y_col_norms_min: 39.0379829407
	valid_y_max_max_class: 0.999999821186
	valid_y_mean_max_class: 0.999999821186
	valid_y_min_max_class: 0.999999821186
	valid_y_misclass: 0.998980820179
	valid_y_nll: 4.201e+12
	valid_y_row_norms_max: 4949.11132812
	valid_y_row_norms_mean: 1152.45788574
	valid_y_row_norms_min: 97.2359771729
Time this epoch: 42.355780 seconds
Monitoring step:
	Epochs seen: 9
	Batches seen: 1701
	Examples seen: 217728
	learning_rate: 0.0500000156462
	momentum: 0.935555815697
	test_h0_kernel_norms_max: 0.900000452995
	test_h0_kernel_norms_mean: 0.900000214577
	test_h0_kernel_norms_min: 0.900000095367
	test_h0_max_x.max_u: 3.969e+06
	test_h0_max_x.mean_u: 1.217e+06
	test_h0_max_x.min_u: 2.372e+05
	test_h0_mean_x.max_u: 2.018e+05
	test_h0_mean_x.mean_u: -7.563e+04
	test_h0_mean_x.min_u: -4.003e+05
	test_h0_min_x.max_u: -2.041e+05
	test_h0_min_x.mean_u: -1.521e+06
	test_h0_min_x.min_u: -4.723e+06
	test_h0_range_x.max_u: 7.100e+06
	test_h0_range_x.mean_u: 2.739e+06
	test_h0_range_x.min_u: 4.413e+05
	test_h1_kernel_norms_max: 1.93650317192
	test_h1_kernel_norms_mean: 1.9365003109
	test_h1_kernel_norms_min: 1.93649756908
	test_h1_max_x.max_u: 5.036e+07
	test_h1_max_x.mean_u: 1.805e+07
	test_h1_max_x.min_u: 1.436e+06
	test_h1_mean_x.max_u: 1.965e+07
	test_h1_mean_x.mean_u: 6.122e+06
	test_h1_mean_x.min_u: -6.168e+06
	test_h1_min_x.max_u: 6.460e+06
	test_h1_min_x.mean_u: -4.637e+06
	test_h1_min_x.min_u: -2.076e+07
	test_h1_range_x.max_u: 4.674e+07
	test_h1_range_x.mean_u: 2.269e+07
	test_h1_range_x.min_u: 1.371e+07
	test_h2_kernel_norms_max: 1.93650126457
	test_h2_kernel_norms_mean: 1.9365003109
	test_h2_kernel_norms_min: 1.93649792671
	test_h2_max_x.max_u: 3.834e+08
	test_h2_max_x.mean_u: 1.050e+08
	test_h2_max_x.min_u: -5.334e+06
	test_h2_mean_x.max_u: 1.839e+08
	test_h2_mean_x.mean_u: 3.863e+07
	test_h2_mean_x.min_u: -7.629e+07
	test_h2_min_x.max_u: 2.217e+07
	test_h2_min_x.mean_u: -2.280e+07
	test_h2_min_x.min_u: -2.451e+08
	test_h2_range_x.max_u: 3.612e+08
	test_h2_range_x.mean_u: 1.278e+08
	test_h2_range_x.min_u: 3.363e+07
	test_objective: 8.766e+13
	test_y_col_norms_max: 1.291e+05
	test_y_col_norms_mean: 2.791e+04
	test_y_col_norms_min: 1640.64343262
	test_y_max_max_class: 1.00000011921
	test_y_mean_max_class: 1.00000011921
	test_y_min_max_class: 1.00000011921
	test_y_misclass: 0.936849117279
	test_y_nll: 8.193e+13
	test_y_row_norms_max: 2.961e+04
	test_y_row_norms_mean: 1.109e+04
	test_y_row_norms_min: 1250.84155273
	total_seconds_last_epoch: 47.4680099487
	training_seconds_this_epoch: 42.3557777405
	valid_h0_kernel_norms_max: 0.900000274181
	valid_h0_kernel_norms_mean: 0.900000035763
	valid_h0_kernel_norms_min: 0.900000035763
	valid_h0_max_x.max_u: 3.969e+06
	valid_h0_max_x.mean_u: 1.217e+06
	valid_h0_max_x.min_u: 2.372e+05
	valid_h0_mean_x.max_u: 2.018e+05
	valid_h0_mean_x.mean_u: -7.563e+04
	valid_h0_mean_x.min_u: -4.003e+05
	valid_h0_min_x.max_u: -2.041e+05
	valid_h0_min_x.mean_u: -1.521e+06
	valid_h0_min_x.min_u: -4.723e+06
	valid_h0_range_x.max_u: 7.100e+06
	valid_h0_range_x.mean_u: 2.739e+06
	valid_h0_range_x.min_u: 4.413e+05
	valid_h1_kernel_norms_max: 1.93650245667
	valid_h1_kernel_norms_mean: 1.93649971485
	valid_h1_kernel_norms_min: 1.93649697304
	valid_h1_max_x.max_u: 5.036e+07
	valid_h1_max_x.mean_u: 1.805e+07
	valid_h1_max_x.min_u: 1.436e+06
	valid_h1_mean_x.max_u: 1.965e+07
	valid_h1_mean_x.mean_u: 6.122e+06
	valid_h1_mean_x.min_u: -6.168e+06
	valid_h1_min_x.max_u: 6.460e+06
	valid_h1_min_x.mean_u: -4.637e+06
	valid_h1_min_x.min_u: -2.076e+07
	valid_h1_range_x.max_u: 4.674e+07
	valid_h1_range_x.mean_u: 2.269e+07
	valid_h1_range_x.min_u: 1.371e+07
	valid_h2_kernel_norms_max: 1.93650174141
	valid_h2_kernel_norms_mean: 1.93649971485
	valid_h2_kernel_norms_min: 1.93649888039
	valid_h2_max_x.max_u: 3.834e+08
	valid_h2_max_x.mean_u: 1.050e+08
	valid_h2_max_x.min_u: -5.334e+06
	valid_h2_mean_x.max_u: 1.839e+08
	valid_h2_mean_x.mean_u: 3.863e+07
	valid_h2_mean_x.min_u: -7.629e+07
	valid_h2_min_x.max_u: 2.217e+07
	valid_h2_min_x.mean_u: -2.280e+07
	valid_h2_min_x.min_u: -2.451e+08
	valid_h2_range_x.max_u: 3.612e+08
	valid_h2_range_x.mean_u: 1.278e+08
	valid_h2_range_x.min_u: 3.363e+07
	valid_objective: 8.745e+13
	valid_y_col_norms_max: 1.291e+05
	valid_y_col_norms_mean: 2.791e+04
	valid_y_col_norms_min: 1640.64331055
	valid_y_max_max_class: 0.999999821186
	valid_y_mean_max_class: 0.999999821186
	valid_y_min_max_class: 0.999999821186
	valid_y_misclass: 0.934442818165
	valid_y_nll: 8.185e+13
	valid_y_row_norms_max: 2.961e+04
	valid_y_row_norms_mean: 1.109e+04
	valid_y_row_norms_min: 1250.84130859

Modifying Options

Some notes here on how options should be modified in the run_settings and to sub into YAML files.