Nameexact_genome_1542649503_170_6353_1
Workunit4099992
Created20 Nov 2018, 5:04:00 UTC
Sent20 Nov 2018, 5:12:45 UTC
Report deadline16 Dec 2018, 23:04:11 UTC
Received21 Nov 2018, 5:42:47 UTC
Server stateOver
OutcomeSuccess
Client stateDone
Exit status0 (0x0)
Computer ID78968
Run time15 hours 11 min 18 sec
CPU time15 hours 8 min 49 sec
Validate stateValid
Credit6,686.01
Device peak FLOPS2.20 GFLOPS
Application versionEXACT Batch Norm With Scaled FMP CNN Trainer v0.34
Peak working set size575.82 MB
Peak swap size595.64 MB
Peak disk usage11.16 MB

Stderr output

<core_client_version>7.8.3</core_client_version>
<![CDATA[
<stderr_txt>
   4: 5000
    class    5: 5000
    class    6: 5000
    class    7: 5000
    class    8: 5000
    class    9: 5000
calculating averages and standard deviations for images
average pixel value for channel 0: 0.491399973630905
average pixel value for channel 1: 0.482159107923508
average pixel value for channel 2: 0.446530401706696
pixel variance for channel 0: 0.0610253289341927
pixel standard deviation for channel 0: 0.247033059597015
pixel variance for channel 1: 0.0592849254608154
pixel standard deviation for channel 1: 0.24348495900631
pixel variance for channel 2: 0.0684280395507813
pixel standard deviation for channel 2: 0.261587530374527
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
image_size: 3x32x32 = 3072
read 10000 images.
    class    0: 1000
    class    1: 1000
    class    2: 1000
    class    3: 1000
    class    4: 1000
    class    5: 1000
    class    6: 1000
    class    7: 1000
    class    8: 1000
    class    9: 1000
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
image_size: 3x32x32 = 3072
read 10000 images.
    class    0: 1000
    class    1: 1000
    class    2: 1000
    class    3: 1000
    class    4: 1000
    class    5: 1000
    class    6: 1000
    class    7: 1000
    class    8: 1000
    class    9: 1000
loaded images
starting backpropagation!
arguments:
	'projects/csgrid.org_csg/exact_client_0.34_windows_x86_64.exe'
	'--training_file'
	'training_samples.bin'
	'--validation_file'
	'validation_samples.bin'
	'--testing_file'
	'testing_samples.bin'
	'--genome_file'
	'input_genome.txt'
	'--output_file'
	'output_genome.txt'
	'--checkpoint_file'
	'checkpoint.txt'
converting arguments to vector
boincified training filename: '../../projects/csgrid.org_csg/cifar_10_training.bin'
boincified validation filename: '../../projects/csgrid.org_csg/cifar_10_testing.bin'
boincified testing filename: '../../projects/csgrid.org_csg/cifar_10_testing.bin'
boincified genome filename: '../../projects/csgrid.org_csg/exact_genome_1542649503_170_6353.txt'
boincified output filename: '../../projects/csgrid.org_csg/exact_genome_1542649503_170_6353_1_r1529289343_0'
boincified checkpoint filename: 'checkpoint.txt'
loading genome
starting from checkpoint file: 'checkpoint.txt'
read CNN_Genome file with version string: 'v0.33'
read exact_id: -1
read genome_id: -1
read initial_mu: 0.458005
read mu: 0.554239
read mu_delta: 0.93565
read initial_learning_rate: 0.000275212
read learning_rate: 0.000203511
read learning_rate_delta: 0.904288
read initial_weight_decay: 0.000174326
read weight_decay: 0.000137084
read weight_decay_delta: 0.923015
read batch_size: 106
read epsilon: 1e-07
read alpha: 0.0499922
read input_dropout_probability: 0.00161003
read hidden_dropout_probability: 0.0792098
read velocity_reset: 1370
read epoch: 3
read max_epochs: 25
read reset_weights: 0
read padding: 2
read best_epoch: 1
read number_validation_images: 10000
read best_validation_predictions: 6258
read best_validation_error: 10813.5
read number_training_images: 50000
read training_predictions: 0
read training_error: 1e+07
read number_test_images: 10000
read test_predictions: 0
read test_error: 1e+07
read generation_id: 6353
read normal distribution: '1 -3.13660836219788 1.12176644802094'
generator_str: '383852661'
read generator: 383852661
read generated_by_map:
1 add_node 1
reading 110 nodes.
reading 395 edges.
number input nodes: 3
number softmax nodes: 10
order_size: 50000
parsed input file
loaded genome
loading images
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
image_size: 3x32x32 = 3072
read 50000 images.
    class    0: 5000
    class    1: 5000
    class    2: 5000
    class    3: 5000
    class    4: 5000
    class    5: 5000
    class    6: 5000
    class    7: 5000
    class    8: 5000
    class    9: 5000
calculating averages and standard deviations for images
average pixel value for channel 0: 0.491399973630905
average pixel value for channel 1: 0.482159107923508
average pixel value for channel 2: 0.446530401706696
pixel variance for channel 0: 0.0610253289341927
pixel standard deviation for channel 0: 0.247033059597015
pixel variance for channel 1: 0.0592849254608154
pixel standard deviation for channel 1: 0.24348495900631
pixel variance for channel 2: 0.0684280395507813
pixel standard deviation for channel 2: 0.261587530374527
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
image_size: 3x32x32 = 3072
read 10000 images.
    class    0: 1000
    class    1: 1000
    class    2: 1000
    class    3: 1000
    class    4: 1000
    class    5: 1000
    class    6: 1000
    class    7: 1000
    class    8: 1000
    class    9: 1000
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
image_size: 3x32x32 = 3072
read 10000 images.
    class    0: 1000
    class    1: 1000
    class    2: 1000
    class    3: 1000
    class    4: 1000
    class    5: 1000
    class    6: 1000
    class    7: 1000
    class    8: 1000
    class    9: 1000
loaded images
starting backpropagation!
arguments:
	'projects/csgrid.org_csg/exact_client_0.34_windows_x86_64.exe'
	'--training_file'
	'training_samples.bin'
	'--validation_file'
	'validation_samples.bin'
	'--testing_file'
	'testing_samples.bin'
	'--genome_file'
	'input_genome.txt'
	'--output_file'
	'output_genome.txt'
	'--checkpoint_file'
	'checkpoint.txt'
converting arguments to vector
boincified training filename: '../../projects/csgrid.org_csg/cifar_10_training.bin'
boincified validation filename: '../../projects/csgrid.org_csg/cifar_10_testing.bin'
boincified testing filename: '../../projects/csgrid.org_csg/cifar_10_testing.bin'
boincified genome filename: '../../projects/csgrid.org_csg/exact_genome_1542649503_170_6353.txt'
boincified output filename: '../../projects/csgrid.org_csg/exact_genome_1542649503_170_6353_1_r1529289343_0'
boincified checkpoint filename: 'checkpoint.txt'
loading genome
starting from checkpoint file: 'checkpoint.txt'
read CNN_Genome file with version string: 'v0.33'
read exact_id: -1
read genome_id: -1
read initial_mu: 0.458005
read mu: 0.554239
read mu_delta: 0.93565
read initial_learning_rate: 0.000275212
read learning_rate: 0.000203511
read learning_rate_delta: 0.904288
read initial_weight_decay: 0.000174326
read weight_decay: 0.000137084
read weight_decay_delta: 0.923015
read batch_size: 106
read epsilon: 1e-07
read alpha: 0.0499922
read input_dropout_probability: 0.00161003
read hidden_dropout_probability: 0.0792098
read velocity_reset: 1370
read epoch: 3
read max_epochs: 25
read reset_weights: 0
read padding: 2
read best_epoch: 1
read number_validation_images: 10000
read best_validation_predictions: 6258
read best_validation_error: 10813.5
read number_training_images: 50000
read training_predictions: 0
read training_error: 1e+07
read number_test_images: 10000
read test_predictions: 0
read test_error: 1e+07
read generation_id: 6353
read normal distribution: '1 -3.13660836219788 1.12176644802094'
generator_str: '383852661'
read generator: 383852661
read generated_by_map:
1 add_node 1
reading 110 nodes.
reading 395 edges.
number input nodes: 3
number softmax nodes: 10
order_size: 50000
parsed input file
loaded genome
loading images
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
image_size: 3x32x32 = 3072
read 50000 images.
    class    0: 5000
    class    1: 5000
    class    2: 5000
    class    3: 5000
    class    4: 5000
    class    5: 5000
    class    6: 5000
    class    7: 5000
    class    8: 5000
    class    9: 5000
calculating averages and standard deviations for images
average pixel value for channel 0: 0.491399973630905
average pixel value for channel 1: 0.482159107923508
average pixel value for channel 2: 0.446530401706696
pixel variance for channel 0: 0.0610253289341927
pixel standard deviation for channel 0: 0.247033059597015
pixel variance for channel 1: 0.0592849254608154
pixel standard deviation for channel 1: 0.24348495900631
pixel variance for channel 2: 0.0684280395507813
pixel standard deviation for channel 2: 0.261587530374527
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
image_size: 3x32x32 = 3072
read 10000 images.
    class    0: 1000
    class    1: 1000
    class    2: 1000
    class    3: 1000
    class    4: 1000
    class    5: 1000
    class    6: 1000
    class    7: 1000
    class    8: 1000
    class    9: 1000
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
image_size: 3x32x32 = 3072
read 10000 images.
    class    0: 1000
    class    1: 1000
    class    2: 1000
    class    3: 1000
    class    4: 1000
    class    5: 1000
    class    6: 1000
    class    7: 1000
    class    8: 1000
    class    9: 1000
loaded images
starting backpropagation!
epoch time: 1977.05908203125s, input_fired_time: 37.0183410644531, output_fired_time: 14.9578285217285, propagate_forward_time: 730.317077636719, propagate_backward_time: 1167.77429199219, weight_update_time: 0.534858345985413, other_time: 26.9915771484375
epoch time: 143.338073730469s, input_fired_time: 2.53440284729004, output_fired_time: 0, propagate_forward_time: 136.301513671875, propagate_backward_time: 0, weight_update_time: 0, other_time: 4.50215148925781
validation[          , genome  6353] predictions:    6342/  10000 (63.42%), best:    6342/10000 (63.42%), error:     10714.42188, best error:     10714.42188 on epoch:     3, epoch:    3/25, mu: 0.5542391539, learning_rate: 0.0002035109, weight_decay: 0.0001370844

arguments:
	'projects/csgrid.org_csg/exact_client_0.34_windows_x86_64.exe'
	'--training_file'
	'training_samples.bin'
	'--validation_file'
	'validation_samples.bin'
	'--testing_file'
	'testing_samples.bin'
	'--genome_file'
	'input_genome.txt'
	'--output_file'
	'output_genome.txt'
	'--checkpoint_file'
	'checkpoint.txt'
converting arguments to vector
boincified training filename: '../../projects/csgrid.org_csg/cifar_10_training.bin'
boincified validation filename: '../../projects/csgrid.org_csg/cifar_10_testing.bin'
boincified testing filename: '../../projects/csgrid.org_csg/cifar_10_testing.bin'
boincified genome filename: '../../projects/csgrid.org_csg/exact_genome_1542649503_170_6353.txt'
boincified output filename: '../../projects/csgrid.org_csg/exact_genome_1542649503_170_6353_1_r1529289343_0'
boincified checkpoint filename: 'checkpoint.txt'
loading genome
starting from checkpoint file: 'checkpoint.txt'
read CNN_Genome file with version string: 'v0.33'
read exact_id: -1
read genome_id: -1
read initial_mu: 0.458005
read mu: 0.58228
read mu_delta: 0.93565
read initial_learning_rate: 0.000275212
read learning_rate: 0.000184032
read learning_rate_delta: 0.904288
read initial_weight_decay: 0.000174326
read weight_decay: 0.000126531
read weight_decay_delta: 0.923015
read batch_size: 106
read epsilon: 1e-07
read alpha: 0.0499922
read input_dropout_probability: 0.00161003
read hidden_dropout_probability: 0.0792098
read velocity_reset: 1370
read epoch: 4
read max_epochs: 25
read reset_weights: 0
read padding: 2
read best_epoch: 3
read number_validation_images: 10000
read best_validation_predictions: 6342
read best_validation_error: 10714.4
read number_training_images: 50000
read training_predictions: 0
read training_error: 1e+07
read number_test_images: 10000
read test_predictions: 0
read test_error: 1e+07
read generation_id: 6353
read normal distribution: '1 -3.13660836219788 1.12176644802094'
generator_str: '2029462947'
read generator: 2029462947
read generated_by_map:
1 add_node 1
reading 110 nodes.
reading 395 edges.
number input nodes: 3
number softmax nodes: 10
order_size: 50000
parsed input file
loaded genome
loading images
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
image_size: 3x32x32 = 3072
read 50000 images.
    class    0: 5000
    class    1: 5000
    class    2: 5000
    class    3: 5000
    class    4: 5000
    class    5: 5000
    class    6: 5000
    class    7: 5000
    class    8: 5000
    class    9: 5000
calculating averages and standard deviations for images
average pixel value for channel 0: 0.491399973630905
average pixel value for channel 1: 0.482159107923508
average pixel value for channel 2: 0.446530401706696
pixel variance for channel 0: 0.0610253289341927
pixel standard deviation for channel 0: 0.247033059597015
pixel variance for channel 1: 0.0592849254608154
pixel standard deviation for channel 1: 0.24348495900631
pixel variance for channel 2: 0.0684280395507813
pixel standard deviation for channel 2: 0.261587530374527
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
image_size: 3x32x32 = 3072
read 10000 images.
    class    0: 1000
    class    1: 1000
    class    2: 1000
    class    3: 1000
    class    4: 1000
    class    5: 1000
    class    6: 1000
    class    7: 1000
    class    8: 1000
    class    9: 1000
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
image_size: 3x32x32 = 3072
read 10000 images.
    class    0: 1000
    class    1: 1000
    class    2: 1000
    class    3: 1000
    class    4: 1000
    class    5: 1000
    class    6: 1000
    class    7: 1000
    class    8: 1000
    class    9: 1000
loaded images
starting backpropagation!
arguments:
	'projects/csgrid.org_csg/exact_client_0.34_windows_x86_64.exe'
	'--training_file'
	'training_samples.bin'
	'--validation_file'
	'validation_samples.bin'
	'--testing_file'
	'testing_samples.bin'
	'--genome_file'
	'input_genome.txt'
	'--output_file'
	'output_genome.txt'
	'--checkpoint_file'
	'checkpoint.txt'
converting arguments to vector
boincified training filename: '../../projects/csgrid.org_csg/cifar_10_training.bin'
boincified validation filename: '../../projects/csgrid.org_csg/cifar_10_testing.bin'
boincified testing filename: '../../projects/csgrid.org_csg/cifar_10_testing.bin'
boincified genome filename: '../../projects/csgrid.org_csg/exact_genome_1542649503_170_6353.txt'
boincified output filename: '../../projects/csgrid.org_csg/exact_genome_1542649503_170_6353_1_r1529289343_0'
boincified checkpoint filename: 'checkpoint.txt'
loading genome
starting from checkpoint file: 'checkpoint.txt'
read CNN_Genome file with version string: 'v0.33'
read exact_id: -1
read genome_id: -1
read initial_mu: 0.458005
read mu: 0.58228
read mu_delta: 0.93565
read initial_learning_rate: 0.000275212
read learning_rate: 0.000184032
read learning_rate_delta: 0.904288
read initial_weight_decay: 0.000174326
read weight_decay: 0.000126531
read weight_decay_delta: 0.923015
read batch_size: 106
read epsilon: 1e-07
read alpha: 0.0499922
read input_dropout_probability: 0.00161003
read hidden_dropout_probability: 0.0792098
read velocity_reset: 1370
read epoch: 4
read max_epochs: 25
read reset_weights: 0
read padding: 2
read best_epoch: 3
read number_validation_images: 10000
read best_validation_predictions: 6342
read best_validation_error: 10714.4
read number_training_images: 50000
read training_predictions: 0
read training_error: 1e+07
read number_test_images: 10000
read test_predictions: 0
read test_error: 1e+07
read generation_id: 6353
read normal distribution: '1 -3.13660836219788 1.12176644802094'
generator_str: '2029462947'
read generator: 2029462947
read generated_by_map:
1 add_node 1
reading 110 nodes.
reading 395 edges.
number input nodes: 3
number softmax nodes: 10
order_size: 50000
parsed input file
loaded genome
loading images
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
image_size: 3x32x32 = 3072
read 50000 images.
    class    0: 5000
    class    1: 5000
    class    2: 5000
    class    3: 5000
    class    4: 5000
    class    5: 5000
    class    6: 5000
    class    7: 5000
    class    8: 5000
    class    9: 5000
calculating averages and standard deviations for images
average pixel value for channel 0: 0.491399973630905
average pixel value for channel 1: 0.482159107923508
average pixel value for channel 2: 0.446530401706696
pixel variance for channel 0: 0.0610253289341927
pixel standard deviation for channel 0: 0.247033059597015
pixel variance for channel 1: 0.0592849254608154
pixel standard deviation for channel 1: 0.24348495900631
pixel variance for channel 2: 0.0684280395507813
pixel standard deviation for channel 2: 0.261587530374527
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
image_size: 3x32x32 = 3072
read 10000 images.
    class    0: 1000
    class    1: 1000
    class    2: 1000
    class    3: 1000
    class    4: 1000
    class    5: 1000
    class    6: 1000
    class    7: 1000
    class    8: 1000
    class    9: 1000
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
image_size: 3x32x32 = 3072
read 10000 images.
    class    0: 1000
    class    1: 1000
    class    2: 1000
    class    3: 1000
    class    4: 1000
    class    5: 1000
    class    6: 1000
    class    7: 1000
    class    8: 1000
    class    9: 1000
loaded images
starting backpropagation!
arguments:
	'projects/csgrid.org_csg/exact_client_0.34_windows_x86_64.exe'
	'--training_file'
	'training_samples.bin'
	'--validation_file'
	'validation_samples.bin'
	'--testing_file'
	'testing_samples.bin'
	'--genome_file'
	'input_genome.txt'
	'--output_file'
	'output_genome.txt'
	'--checkpoint_file'
	'checkpoint.txt'
converting arguments to vector
boincified training filename: '../../projects/csgrid.org_csg/cifar_10_training.bin'
boincified validation filename: '../../projects/csgrid.org_csg/cifar_10_testing.bin'
boincified testing filename: '../../projects/csgrid.org_csg/cifar_10_testing.bin'
boincified genome filename: '../../projects/csgrid.org_csg/exact_genome_1542649503_170_6353.txt'
boincified output filename: '../../projects/csgrid.org_csg/exact_genome_1542649503_170_6353_1_r1529289343_0'
boincified checkpoint filename: 'checkpoint.txt'
loading genome
starting from checkpoint file: 'checkpoint.txt'
read CNN_Genome file with version string: 'v0.33'
read exact_id: -1
read genome_id: -1
read initial_mu: 0.458005
read mu: 0.58228
read mu_delta: 0.93565
read initial_learning_rate: 0.000275212
read learning_rate: 0.000184032
read learning_rate_delta: 0.904288
read initial_weight_decay: 0.000174326
read weight_decay: 0.000126531
read weight_decay_delta: 0.923015
read batch_size: 106
read epsilon: 1e-07
read alpha: 0.0499922
read input_dropout_probability: 0.00161003
read hidden_dropout_probability: 0.0792098
read velocity_reset: 1370
read epoch: 4
read max_epochs: 25
read reset_weights: 0
read padding: 2
read best_epoch: 3
read number_validation_images: 10000
read best_validation_predictions: 6342
read best_validation_error: 10714.4
read number_training_images: 50000
read training_predictions: 0
read training_error: 1e+07
read number_test_images: 10000
read test_predictions: 0
read test_error: 1e+07
read generation_id: 6353
read normal distribution: '1 -3.13660836219788 1.12176644802094'
generator_str: '2029462947'
read generator: 2029462947
read generated_by_map:
1 add_node 1
reading 110 nodes.
reading 395 edges.
number input nodes: 3
number softmax nodes: 10
order_size: 50000
parsed input file
loaded genome
loading images
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
image_size: 3x32x32 = 3072
read 50000 images.
    class    0: 5000
    class    1: 5000
    class    2: 5000
    class    3: 5000
    class    4: 5000
    class    5: 5000
    class    6: 5000
    class    7: 5000
    class    8: 5000
    class    9: 5000
calculating averages and standard deviations for images
average pixel value for channel 0: 0.491399973630905
average pixel value for channel 1: 0.482159107923508
average pixel value for channel 2: 0.446530401706696
pixel variance for channel 0: 0.0610253289341927
pixel standard deviation for channel 0: 0.247033059597015
pixel variance for channel 1: 0.0592849254608154
pixel standard deviation for channel 1: 0.24348495900631
pixel variance for channel 2: 0.0684280395507813
pixel standard deviation for channel 2: 0.261587530374527
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
image_size: 3x32x32 = 3072
read 10000 images.
    class    0: 1000
    class    1: 1000
    class    2: 1000
    class    3: 1000
    class    4: 1000
    class    5: 1000
    class    6: 1000
    class    7: 1000
    class    8: 1000
    class    9: 1000
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
image_size: 3x32x32 = 3072
read 10000 images.
    class    0: 1000
    class    1: 1000
    class    2: 1000
    class    3: 1000
    class    4: 1000
    class    5: 1000
    class    6: 1000
    class    7: 1000
    class    8: 1000
    class    9: 1000
loaded images
starting backpropagation!
arguments:
	'projects/csgrid.org_csg/exact_client_0.34_windows_x86_64.exe'
	'--training_file'
	'training_samples.bin'
	'--validation_file'
	'validation_samples.bin'
	'--testing_file'
	'testing_samples.bin'
	'--genome_file'
	'input_genome.txt'
	'--output_file'
	'output_genome.txt'
	'--checkpoint_file'
	'checkpoint.txt'
converting arguments to vector
boincified training filename: '../../projects/csgrid.org_csg/cifar_10_training.bin'
boincified validation filename: '../../projects/csgrid.org_csg/cifar_10_testing.bin'
boincified testing filename: '../../projects/csgrid.org_csg/cifar_10_testing.bin'
boincified genome filename: '../../projects/csgrid.org_csg/exact_genome_1542649503_170_6353.txt'
boincified output filename: '../../projects/csgrid.org_csg/exact_genome_1542649503_170_6353_1_r1529289343_0'
boincified checkpoint filename: 'checkpoint.txt'
loading genome
starting from checkpoint file: 'checkpoint.txt'
read CNN_Genome file with version string: 'v0.33'
read exact_id: -1
read genome_id: -1
read initial_mu: 0.458005
read mu: 0.58228
read mu_delta: 0.93565
read initial_learning_rate: 0.000275212
read learning_rate: 0.000184032
read learning_rate_delta: 0.904288
read initial_weight_decay: 0.000174326
read weight_decay: 0.000126531
read weight_decay_delta: 0.923015
read batch_size: 106
read epsilon: 1e-07
read alpha: 0.0499922
read input_dropout_probability: 0.00161003
read hidden_dropout_probability: 0.0792098
read velocity_reset: 1370
read epoch: 4
read max_epochs: 25
read reset_weights: 0
read padding: 2
read best_epoch: 3
read number_validation_images: 10000
read best_validation_predictions: 6342
read best_validation_error: 10714.4
read number_training_images: 50000
read training_predictions: 0
read training_error: 1e+07
read number_test_images: 10000
read test_predictions: 0
read test_error: 1e+07
read generation_id: 6353
read normal distribution: '1 -3.13660836219788 1.12176644802094'
generator_str: '2029462947'
read generator: 2029462947
read generated_by_map:
1 add_node 1
reading 110 nodes.
reading 395 edges.
number input nodes: 3
number softmax nodes: 10
order_size: 50000
parsed input file
loaded genome
loading images
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
image_size: 3x32x32 = 3072
read 50000 images.
    class    0: 5000
    class    1: 5000
    class    2: 5000
    class    3: 5000
    class    4: 5000
    class    5: 5000
    class    6: 5000
    class    7: 5000
    class    8: 5000
    class    9: 5000
calculating averages and standard deviations for images
average pixel value for channel 0: 0.491399973630905
average pixel value for channel 1: 0.482159107923508
average pixel value for channel 2: 0.446530401706696
pixel variance for channel 0: 0.0610253289341927
pixel standard deviation for channel 0: 0.247033059597015
pixel variance for channel 1: 0.0592849254608154
pixel standard deviation for channel 1: 0.24348495900631
pixel variance for channel 2: 0.0684280395507813
pixel standard deviation for channel 2: 0.261587530374527
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
image_size: 3x32x32 = 3072
read 10000 images.
    class    0: 1000
    class    1: 1000
    class    2: 1000
    class    3: 1000
    class    4: 1000
    class    5: 1000
    class    6: 1000
    class    7: 1000
    class    8: 1000
    class    9: 1000
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
image_size: 3x32x32 = 3072
read 10000 images.
    class    0: 1000
    class    1: 1000
    class    2: 1000
    class    3: 1000
    class    4: 1000
    class    5: 1000
    class    6: 1000
    class    7: 1000
    class    8: 1000
    class    9: 1000
loaded images
starting backpropagation!
arguments:
	'projects/csgrid.org_csg/exact_client_0.34_windows_x86_64.exe'
	'--training_file'
	'training_samples.bin'
	'--validation_file'
	'validation_samples.bin'
	'--testing_file'
	'testing_samples.bin'
	'--genome_file'
	'input_genome.txt'
	'--output_file'
	'output_genome.txt'
	'--checkpoint_file'
	'checkpoint.txt'
converting arguments to vector
boincified training filename: '../../projects/csgrid.org_csg/cifar_10_training.bin'
boincified validation filename: '../../projects/csgrid.org_csg/cifar_10_testing.bin'
boincified testing filename: '../../projects/csgrid.org_csg/cifar_10_testing.bin'
boincified genome filename: '../../projects/csgrid.org_csg/exact_genome_1542649503_170_6353.txt'
boincified output filename: '../../projects/csgrid.org_csg/exact_genome_1542649503_170_6353_1_r1529289343_0'
boincified checkpoint filename: 'checkpoint.txt'
loading genome
starting from checkpoint file: 'checkpoint.txt'
read CNN_Genome file with version string: 'v0.33'
read exact_id: -1
read genome_id: -1
read initial_mu: 0.458005
read mu: 0.58228
read mu_delta: 0.93565
read initial_learning_rate: 0.000275212
read learning_rate: 0.000184032
read learning_rate_delta: 0.904288
read initial_weight_decay: 0.000174326
read weight_decay: 0.000126531
read weight_decay_delta: 0.923015
read batch_size: 106
read epsilon: 1e-07
read alpha: 0.0499922
read input_dropout_probability: 0.00161003
read hidden_dropout_probability: 0.0792098
read velocity_reset: 1370
read epoch: 4
read max_epochs: 25
read reset_weights: 0
read padding: 2
read best_epoch: 3
read number_validation_images: 10000
read best_validation_predictions: 6342
read best_validation_error: 10714.4
read number_training_images: 50000
read training_predictions: 0
read training_error: 1e+07
read number_test_images: 10000
read test_predictions: 0
read test_error: 1e+07
read generation_id: 6353
read normal distribution: '1 -3.13660836219788 1.12176644802094'
generator_str: '2029462947'
read generator: 2029462947
read generated_by_map:
1 add_node 1
reading 110 nodes.
reading 395 edges.
number input nodes: 3
number softmax nodes: 10
order_size: 50000
parsed input file
loaded genome
loading images
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
image_size: 3x32x32 = 3072
read 50000 images.
    class    0: 5000
    class    1: 5000
    class    2: 5000
    class    3: 5000
    class    4: 5000
    class    5: 5000
    class    6: 5000
    class    7: 5000
    class    8: 5000
    class    9: 5000
calculating averages and standard deviations for images
average pixel value for channel 0: 0.491399973630905
average pixel value for channel 1: 0.482159107923508
average pixel value for channel 2: 0.446530401706696
pixel variance for channel 0: 0.0610253289341927
pixel standard deviation for channel 0: 0.247033059597015
pixel variance for channel 1: 0.0592849254608154
pixel standard deviation for channel 1: 0.24348495900631
pixel variance for channel 2: 0.0684280395507813
pixel standard deviation for channel 2: 0.261587530374527
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
image_size: 3x32x32 = 3072
read 10000 images.
    class    0: 1000
    class    1: 1000
    class    2: 1000
    class    3: 1000
    class    4: 1000
    class    5: 1000
    class    6: 1000
    class    7: 1000
    class    8: 1000
    class    9: 1000
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
image_size: 3x32x32 = 3072
read 10000 images.
    class    0: 1000
    class    1: 1000
    class    2: 1000
    class    3: 1000
    class    4: 1000
    class    5: 1000
    class    6: 1000
    class    7: 1000
    class    8: 1000
    class    9: 1000
loaded images
starting backpropagation!
arguments:
	'projects/csgrid.org_csg/exact_client_0.34_windows_x86_64.exe'
	'--training_file'
	'training_samples.bin'
	'--validation_file'
	'validation_samples.bin'
	'--testing_file'
	'testing_samples.bin'
	'--genome_file'
	'input_genome.txt'
	'--output_file'
	'output_genome.txt'
	'--checkpoint_file'
	'checkpoint.txt'
converting arguments to vector
boincified training filename: '../../projects/csgrid.org_csg/cifar_10_training.bin'
boincified validation filename: '../../projects/csgrid.org_csg/cifar_10_testing.bin'
boincified testing filename: '../../projects/csgrid.org_csg/cifar_10_testing.bin'
boincified genome filename: '../../projects/csgrid.org_csg/exact_genome_1542649503_170_6353.txt'
boincified output filename: '../../projects/csgrid.org_csg/exact_genome_1542649503_170_6353_1_r1529289343_0'
boincified checkpoint filename: 'checkpoint.txt'
loading genome
starting from checkpoint file: 'checkpoint.txt'
read CNN_Genome file with version string: 'v0.33'
read exact_id: -1
read genome_id: -1
read initial_mu: 0.458005
read mu: 0.58228
read mu_delta: 0.93565
read initial_learning_rate: 0.000275212
read learning_rate: 0.000184032
read learning_rate_delta: 0.904288
read initial_weight_decay: 0.000174326
read weight_decay: 0.000126531
read weight_decay_delta: 0.923015
read batch_size: 106
read epsilon: 1e-07
read alpha: 0.0499922
read input_dropout_probability: 0.00161003
read hidden_dropout_probability: 0.0792098
read velocity_reset: 1370
read epoch: 4
read max_epochs: 25
read reset_weights: 0
read padding: 2
read best_epoch: 3
read number_validation_images: 10000
read best_validation_predictions: 6342
read best_validation_error: 10714.4
read number_training_images: 50000
read training_predictions: 0
read training_error: 1e+07
read number_test_images: 10000
read test_predictions: 0
read test_error: 1e+07
read generation_id: 6353
read normal distribution: '1 -3.13660836219788 1.12176644802094'
generator_str: '2029462947'
read generator: 2029462947
read generated_by_map:
1 add_node 1
reading 110 nodes.
reading 395 edges.
number input nodes: 3
number softmax nodes: 10
order_size: 50000
parsed input file
loaded genome
loading images
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
image_size: 3x32x32 = 3072
read 50000 images.
    class    0: 5000
    class    1: 5000
    class    2: 5000
    class    3: 5000
    class    4: 5000
    class    5: 5000
    class    6: 5000
    class    7: 5000
    class    8: 5000
    class    9: 5000
calculating averages and standard deviations for images
average pixel value for channel 0: 0.491399973630905
average pixel value for channel 1: 0.482159107923508
average pixel value for channel 2: 0.446530401706696
pixel variance for channel 0: 0.0610253289341927
pixel standard deviation for channel 0: 0.247033059597015
pixel variance for channel 1: 0.0592849254608154
pixel standard deviation for channel 1: 0.24348495900631
pixel variance for channel 2: 0.0684280395507813
pixel standard deviation for channel 2: 0.261587530374527
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
image_size: 3x32x32 = 3072
read 10000 images.
    class    0: 1000
    class    1: 1000
    class    2: 1000
    class    3: 1000
    class    4: 1000
    class    5: 1000
    class    6: 1000
    class    7: 1000
    class    8: 1000
    class    9: 1000
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
image_size: 3x32x32 = 3072
read 10000 images.
    class    0: 1000
    class    1: 1000
    class    2: 1000
    class    3: 1000
    class    4: 1000
    class    5: 1000
    class    6: 1000
    class    7: 1000
    class    8: 1000
    class    9: 1000
loaded images
starting backpropagation!
arguments:
	'projects/csgrid.org_csg/exact_client_0.34_windows_x86_64.exe'
	'--training_file'
	'training_samples.bin'
	'--validation_file'
	'validation_samples.bin'
	'--testing_file'
	'testing_samples.bin'
	'--genome_file'
	'input_genome.txt'
	'--output_file'
	'output_genome.txt'
	'--checkpoint_file'
	'checkpoint.txt'
converting arguments to vector
boincified training filename: '../../projects/csgrid.org_csg/cifar_10_training.bin'
boincified validation filename: '../../projects/csgrid.org_csg/cifar_10_testing.bin'
boincified testing filename: '../../projects/csgrid.org_csg/cifar_10_testing.bin'
boincified genome filename: '../../projects/csgrid.org_csg/exact_genome_1542649503_170_6353.txt'
boincified output filename: '../../projects/csgrid.org_csg/exact_genome_1542649503_170_6353_1_r1529289343_0'
boincified checkpoint filename: 'checkpoint.txt'
loading genome
starting from checkpoint file: 'checkpoint.txt'
read CNN_Genome file with version string: 'v0.33'
read exact_id: -1
read genome_id: -1
read initial_mu: 0.458005
read mu: 0.58228
read mu_delta: 0.93565
read initial_learning_rate: 0.000275212
read learning_rate: 0.000184032
read learning_rate_delta: 0.904288
read initial_weight_decay: 0.000174326
read weight_decay: 0.000126531
read weight_decay_delta: 0.923015
read batch_size: 106
read epsilon: 1e-07
read alpha: 0.0499922
read input_dropout_probability: 0.00161003
read hidden_dropout_probability: 0.0792098
read velocity_reset: 1370
read epoch: 4
read max_epochs: 25
read reset_weights: 0
read padding: 2
read best_epoch: 3
read number_validation_images: 10000
read best_validation_predictions: 6342
read best_validation_error: 10714.4
read number_training_images: 50000
read training_predictions: 0
read training_error: 1e+07
read number_test_images: 10000
read test_predictions: 0
read test_error: 1e+07
read generation_id: 6353
read normal distribution: '1 -3.13660836219788 1.12176644802094'
generator_str: '2029462947'
read generator: 2029462947
read generated_by_map:
1 add_node 1
reading 110 nodes.
reading 395 edges.
number input nodes: 3
number softmax nodes: 10
order_size: 50000
parsed input file
loaded genome
loading images
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
reading image set with 5000 images.
image_size: 3x32x32 = 3072
read 50000 images.
    class    0: 5000
    class    1: 5000
    class    2: 5000
    class    3: 5000
    class    4: 5000
    class    5: 5000
    class    6: 5000
    class    7: 5000
    class    8: 5000
    class    9: 5000
calculating averages and standard deviations for images
average pixel value for channel 0: 0.491399973630905
average pixel value for channel 1: 0.482159107923508
average pixel value for channel 2: 0.446530401706696
pixel variance for channel 0: 0.0610253289341927
pixel standard deviation for channel 0: 0.247033059597015
pixel variance for channel 1: 0.0592849254608154
pixel standard deviation for channel 1: 0.24348495900631
pixel variance for channel 2: 0.0684280395507813
pixel standard deviation for channel 2: 0.261587530374527
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
image_size: 3x32x32 = 3072
read 10000 images.
    class    0: 1000
    class    1: 1000
    class    2: 1000
    class    3: 1000
    class    4: 1000
    class    5: 1000
    class    6: 1000
    class    7: 1000
    class    8: 1000
    class    9: 1000
number_classes: 10
channels: 3
width: 32
height: 32
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
reading image set with 1000 images.
image_size: 3x32x32 = 3072
read 10000 images.
    class    0: 1000
    class    1: 1000
    class    2: 1000
    class    3: 1000
    class    4: 1000
    class    5: 1000
    class    6: 1000
    class    7: 1000
    class    8: 1000
    class    9: 1000
loaded images
starting backpropagation!
epoch time: 1896.90075683594s, input_fired_time: 35.5115661621094, output_fired_time: 14.6420698165894, propagate_forward_time: 694.607788085938, propagate_backward_time: 1125.43920898438, weight_update_time: 0.519755303859711, other_time: 26.7000732421875
epoch time: 158.312957763672s, input_fired_time: 2.78712749481201, output_fired_time: 0, propagate_forward_time: 150.598007202148, propagate_backward_time: 0, weight_update_time: 0, other_time: 4.92782592773438
validation[          , genome  6353] predictions:    6257/  10000 (62.57%), best:    6342/10000 (63.42%), error:     10921.23145, best error:     10714.42188 on epoch:     3, epoch:    4/25, mu: 0.5822803974, learning_rate: 0.0001840325, weight_decay: 0.0001265310

epoch time: 1946.2554931641s, input_fired_time: 35.5776481628, output_fired_time: 14.7917451859, propagate_forward_time: 712.5440063477, propagate_backward_time: 1158.0887451172, weight_update_time: 0.5026761889, other_time: 25.2532958984
epoch time: 155.1105499268s, input_fired_time: 2.8295958042, output_fired_time: 0.0000000000, propagate_forward_time: 147.0335845947, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 5.2473754883
validation[          , genome  6353] predictions:    6253/  10000 (62.53%), best:    6342/10000 (63.42%), error:     10885.97754, best error:     10714.42188 on epoch:     3, epoch:    5/25, mu: 0.6085171700, learning_rate: 0.0001664183, weight_decay: 0.0001167900

epoch time: 1981.2885742188s, input_fired_time: 36.8637733459, output_fired_time: 15.5805511475, propagate_forward_time: 729.5739135742, propagate_backward_time: 1173.5954589844, weight_update_time: 0.5301934481, other_time: 25.6748046875
epoch time: 159.6902618408s, input_fired_time: 2.7708187103, output_fired_time: 0.0000000000, propagate_forward_time: 152.1575775146, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 4.7618713379
validation[          , genome  6353] predictions:    6140/  10000 (61.40%), best:    6342/10000 (63.42%), error:     11109.72168, best error:     10714.42188 on epoch:     3, epoch:    6/25, mu: 0.6330655813, learning_rate: 0.0001504901, weight_decay: 0.0001077989

epoch time: 1919.8050537109s, input_fired_time: 35.5872688293, output_fired_time: 14.6977748871, propagate_forward_time: 707.0128173828, propagate_backward_time: 1137.8364257813, weight_update_time: 0.5063173175, other_time: 24.6707763672
epoch time: 137.8362731934s, input_fired_time: 2.4086565971, output_fired_time: 0.0000000000, propagate_forward_time: 131.3947296143, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 4.0328826904
validation[          , genome  6353] predictions:    6253/  10000 (62.53%), best:    6342/10000 (63.42%), error:     11006.92188, best error:     10714.42188 on epoch:     3, epoch:    7/25, mu: 0.6560342908, learning_rate: 0.0001360864, weight_decay: 0.0000995000

epoch time: 1831.7924804688s, input_fired_time: 34.8251953125, output_fired_time: 13.9859333038, propagate_forward_time: 670.6224975586, propagate_backward_time: 1088.6265869141, weight_update_time: 0.4840624928, other_time: 23.7322998047
epoch time: 145.2932281494s, input_fired_time: 2.5035417080, output_fired_time: 0.0000000000, propagate_forward_time: 138.3908386230, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 4.3988494873
validation[          , genome  6353] predictions:    6315/  10000 (63.15%), best:    6342/10000 (63.42%), error:     10809.79102, best error:     10714.42188 on epoch:     3, epoch:    8/25, mu: 0.6775249839, learning_rate: 0.0001230613, weight_decay: 0.0000918400

epoch time: 1879.8754882813s, input_fired_time: 35.0260887146, output_fired_time: 14.1702442169, propagate_forward_time: 692.2597656250, propagate_backward_time: 1114.1854248047, weight_update_time: 0.5101881623, other_time: 24.2338867188
epoch time: 136.8232879639s, input_fired_time: 2.3887326717, output_fired_time: 0.0000000000, propagate_forward_time: 130.4008636475, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 4.0336914063
validation[          , genome  6353] predictions:    6199/  10000 (61.99%), best:    6342/10000 (63.42%), error:     11003.12891, best error:     10714.42188 on epoch:     3, epoch:    9/25, mu: 0.6976327300, learning_rate: 0.0001112829, weight_decay: 0.0000847698

epoch time: 1761.4365234375s, input_fired_time: 34.0578422546, output_fired_time: 13.4848680496, propagate_forward_time: 644.9503784180, propagate_backward_time: 1045.9771728516, weight_update_time: 0.4663901031, other_time: 22.9661865234
epoch time: 147.1092987061s, input_fired_time: 2.5719578266, output_fired_time: 0.0000000000, propagate_forward_time: 140.3579711914, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 4.1793670654
validation[          , genome  6353] predictions:    6187/  10000 (61.87%), best:    6342/10000 (63.42%), error:     11232.05859, best error:     10714.42188 on epoch:     3, epoch:   10/25, mu: 0.7164465785, learning_rate: 0.0001006317, weight_decay: 0.0000782438

epoch time: 1919.8295898438s, input_fired_time: 35.5343132019, output_fired_time: 14.7079944611, propagate_forward_time: 707.2507324219, propagate_backward_time: 1137.3997802734, weight_update_time: 0.5075132251, other_time: 24.9367675781
epoch time: 149.4561920166s, input_fired_time: 2.5866336823, output_fired_time: 0.0000000000, propagate_forward_time: 142.3557281494, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 4.5138244629
validation[          , genome  6353] predictions:    6270/  10000 (62.70%), best:    6342/10000 (63.42%), error:     10909.05859, best error:     10714.42188 on epoch:     3, epoch:   11/25, mu: 0.7340497375, learning_rate: 0.0000910001, weight_decay: 0.0000722202

epoch time: 1884.4927978516s, input_fired_time: 35.0083618164, output_fired_time: 14.2731952667, propagate_forward_time: 696.0880126953, propagate_backward_time: 1115.1347656250, weight_update_time: 0.5049972534, other_time: 23.9884033203
epoch time: 130.0769958496s, input_fired_time: 2.3239245415, output_fired_time: 0.0000000000, propagate_forward_time: 123.9984359741, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 3.7546386719
validation[          , genome  6353] predictions:    6252/  10000 (62.52%), best:    6342/10000 (63.42%), error:     10945.77246, best error:     10714.42188 on epoch:     3, epoch:   12/25, mu: 0.7505201101, learning_rate: 0.0000822903, weight_decay: 0.0000666603

epoch time: 1754.8496093750s, input_fired_time: 33.7753944397, output_fired_time: 13.4372816086, propagate_forward_time: 640.9717407227, propagate_backward_time: 1044.7188720703, weight_update_time: 0.4489079118, other_time: 21.9464111328
epoch time: 144.1797027588s, input_fired_time: 2.5231645107, output_fired_time: 0.0000000000, propagate_forward_time: 137.4922790527, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 4.1642608643
validation[          , genome  6353] predictions:    6270/  10000 (62.70%), best:    6342/10000 (63.42%), error:     10861.78711, best error:     10714.42188 on epoch:     3, epoch:   13/25, mu: 0.7659306526, learning_rate: 0.0000744141, weight_decay: 0.0000615285

epoch time: 1829.7169189453s, input_fired_time: 34.4742240906, output_fired_time: 14.0260286331, propagate_forward_time: 668.6225585938, propagate_backward_time: 1089.4548339844, weight_update_time: 0.4792495370, other_time: 23.1392822266
epoch time: 150.6997070313s, input_fired_time: 2.6102099419, output_fired_time: 0.0000000000, propagate_forward_time: 143.7531433105, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 4.3363494873
validation[          , genome  6353] predictions:    6249/  10000 (62.49%), best:    6342/10000 (63.42%), error:     10889.74902, best error:     10714.42188 on epoch:     3, epoch:   14/25, mu: 0.7803494930, learning_rate: 0.0000672918, weight_decay: 0.0000567917

epoch time: 1954.2403564453s, input_fired_time: 35.5383224487, output_fired_time: 14.7406454086, propagate_forward_time: 721.8557128906, propagate_backward_time: 1157.0832519531, weight_update_time: 0.5128002167, other_time: 25.0224609375
epoch time: 161.8289642334s, input_fired_time: 2.7108454704, output_fired_time: 0.0000000000, propagate_forward_time: 154.5755920410, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 4.5425262451
validation[          , genome  6353] predictions:    6243/  10000 (62.43%), best:    6342/10000 (63.42%), error:     10824.09180, best error:     10714.42188 on epoch:     3, epoch:   15/25, mu: 0.7938405275, learning_rate: 0.0000608512, weight_decay: 0.0000524196

epoch time: 1868.1363525391s, input_fired_time: 34.3815460205, output_fired_time: 14.1528549194, propagate_forward_time: 689.1436767578, propagate_backward_time: 1106.5565185547, weight_update_time: 0.5131641626, other_time: 23.9017333984
epoch time: 143.2714080811s, input_fired_time: 2.4908158779, output_fired_time: 0.0000000000, propagate_forward_time: 136.6876373291, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 4.0929565430
validation[          , genome  6353] predictions:    6221/  10000 (62.21%), best:    6342/10000 (63.42%), error:     10924.79492, best error:     10714.42188 on epoch:     3, epoch:   16/25, mu: 0.8064634204, learning_rate: 0.0000550270, weight_decay: 0.0000483841

epoch time: 1840.3029785156s, input_fired_time: 34.0996818542, output_fired_time: 13.8692245483, propagate_forward_time: 675.1328735352, propagate_backward_time: 1094.1518554688, weight_update_time: 0.4896276295, other_time: 23.0493164063
epoch time: 138.3411407471s, input_fired_time: 2.4637825489, output_fired_time: 0.0000000000, propagate_forward_time: 131.9786987305, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 3.8986663818
validation[          , genome  6353] predictions:    6179/  10000 (61.79%), best:    6342/10000 (63.42%), error:     10923.49219, best error:     10714.42188 on epoch:     3, epoch:   17/25, mu: 0.8182740211, learning_rate: 0.0000497602, weight_decay: 0.0000446593

epoch time: 1922.3737792969s, input_fired_time: 35.3506889343, output_fired_time: 14.7186374664, propagate_forward_time: 707.8182983398, propagate_backward_time: 1139.9342041016, weight_update_time: 0.5079349875, other_time: 24.5518798828
epoch time: 153.7649078369s, input_fired_time: 2.7129130363, output_fired_time: 0.0000000000, propagate_forward_time: 146.5809173584, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 4.4710845947
validation[          , genome  6353] predictions:    6365/  10000 (63.65%), best:    6342/10000 (63.42%), error:     10758.97461, best error:     10714.42188 on epoch:     3, epoch:   18/25, mu: 0.8293246031, learning_rate: 0.0000449976, weight_decay: 0.0000412212

epoch time: 1837.2153320313s, input_fired_time: 35.1097145081, output_fired_time: 14.2415904999, propagate_forward_time: 678.2127685547, propagate_backward_time: 1085.7941894531, weight_update_time: 0.4968416095, other_time: 23.8570556641
epoch time: 140.3305969238s, input_fired_time: 2.4647998810, output_fired_time: 0.0000000000, propagate_forward_time: 133.7880554199, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 4.0777435303
validation[          , genome  6353] predictions:    6352/  10000 (63.52%), best:    6342/10000 (63.42%), error:     10758.31348, best error:     10714.42188 on epoch:     3, epoch:   19/25, mu: 0.8396640420, learning_rate: 0.0000406908, weight_decay: 0.0000380478

epoch time: 1853.4708251953s, input_fired_time: 34.9716682434, output_fired_time: 14.0380973816, propagate_forward_time: 680.9718627930, propagate_backward_time: 1099.7145996094, weight_update_time: 0.4862540066, other_time: 23.7746582031
epoch time: 147.8843383789s, input_fired_time: 2.6104335785, output_fired_time: 0.0000000000, propagate_forward_time: 140.9047088623, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 4.3692016602
validation[          , genome  6353] predictions:    6252/  10000 (62.52%), best:    6342/10000 (63.42%), error:     10941.67871, best error:     10714.42188 on epoch:     3, epoch:   20/25, mu: 0.8493381739, learning_rate: 0.0000367962, weight_decay: 0.0000351187

epoch time: 2030.9407958984s, input_fired_time: 37.3829231262, output_fired_time: 15.3640546799, propagate_forward_time: 750.1655883789, propagate_backward_time: 1201.9724121094, weight_update_time: 0.5257153511, other_time: 26.0559082031
epoch time: 160.8038330078s, input_fired_time: 2.7497811317, output_fired_time: 0.0000000000, propagate_forward_time: 153.3379364014, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 4.7161102295
validation[          , genome  6353] predictions:    6254/  10000 (62.54%), best:    6342/10000 (63.42%), error:     10848.51758, best error:     10714.42188 on epoch:     3, epoch:   21/25, mu: 0.8583897352, learning_rate: 0.0000332743, weight_decay: 0.0000324151

epoch time: 1987.6713867188s, input_fired_time: 36.2072753906, output_fired_time: 15.5470714569, propagate_forward_time: 734.9349365234, propagate_backward_time: 1175.3424072266, weight_update_time: 0.5344176888, other_time: 25.6396484375
epoch time: 147.4304199219s, input_fired_time: 2.6096022129, output_fired_time: 0.0000000000, propagate_forward_time: 140.5315704346, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 4.2892456055
validation[          , genome  6353] predictions:    6382/  10000 (63.82%), best:    6382/10000 (63.82%), error:     10557.99121, best error:     10557.99121 on epoch:    22, epoch:   22/25, mu: 0.8668588400, learning_rate: 0.0000300896, weight_decay: 0.0000299196

epoch time: 1957.2219238281s, input_fired_time: 36.0080375671, output_fired_time: 15.1415414810, propagate_forward_time: 724.2111816406, propagate_backward_time: 1156.8063964844, weight_update_time: 0.5121497512, other_time: 25.0546875000
epoch time: 163.3548431396s, input_fired_time: 2.7955513000, output_fired_time: 0.0000000000, propagate_forward_time: 155.8833160400, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 4.6759796143
validation[          , genome  6353] predictions:    6381/  10000 (63.81%), best:    6382/10000 (63.82%), error:     10586.22363, best error:     10557.99121 on epoch:    22, epoch:   23/25, mu: 0.8747829795, learning_rate: 0.0000272097, weight_decay: 0.0000276162

epoch time: 2011.7851562500s, input_fired_time: 36.8493919373, output_fired_time: 15.2002258301, propagate_forward_time: 742.3053588867, propagate_backward_time: 1191.3530273438, weight_update_time: 0.5355559587, other_time: 26.0771484375
epoch time: 156.9236145020s, input_fired_time: 2.7724432945, output_fired_time: 0.0000000000, propagate_forward_time: 149.6489257813, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 4.5022430420
validation[          , genome  6353] predictions:    6405/  10000 (64.05%), best:    6382/10000 (63.82%), error:     10617.82910, best error:     10557.99121 on epoch:    22, epoch:   24/25, mu: 0.8821972013, learning_rate: 0.0000246054, weight_decay: 0.0000254902

epoch time: 1950.7453613281s, input_fired_time: 36.4192237854, output_fired_time: 14.8977642059, propagate_forward_time: 720.4502563477, propagate_backward_time: 1154.2584228516, weight_update_time: 0.5080387592, other_time: 24.7198486328
epoch time: 146.6762542725s, input_fired_time: 2.5911047459, output_fired_time: 0.0000000000, propagate_forward_time: 139.8246154785, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 4.2605285645
validation[          , genome  6353] predictions:    6347/  10000 (63.47%), best:    6347/10000 (63.47%), error:     10540.26367, best error:     10540.26367 on epoch:    25, epoch:   25/25, mu: 0.8891342878, learning_rate: 0.0000222503, weight_decay: 0.0000235278

evaluating best weights on full training data.
evaluting training set with running mean/variance:
epoch time: 726.1590576172s, input_fired_time: 12.8790073395, output_fired_time: 0.0000000000, propagate_forward_time: 692.0456542969, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 21.2343750000
best training[          , genome  6353] predictions:   34535/  50000 (69.07%), best:    6347/10000 (63.47%), error:     47347.05859, best error:     10540.26367 on epoch:    25, epoch:   26/25, mu: 0.8956249952, learning_rate: 0.0000201207, weight_decay: 0.0000217165
evaluating best weights on test data.
evaluting test set with running mean/variance:
epoch time: 140.7425994873s, input_fired_time: 2.4873807430, output_fired_time: 0.0000000000, propagate_forward_time: 133.9063873291, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 4.3488311768
   testing[          , genome  6353] predictions:    6347/  10000 (63.47%), best:    6347/10000 (63.47%), error:     10540.26367, best error:     10540.26367 on epoch:    25, epoch:   26/25, mu: 0.8956249952, learning_rate: 0.0000201207, weight_decay: 0.0000217165
backpropagation finished successfully!
21:42:30 (9164): called boinc_finish(0)

</stderr_txt>
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