Nameexact_genome_1542277804_167_5977_1
Workunit4090858
Created15 Nov 2018, 15:39:02 UTC
Sent15 Nov 2018, 15:43:40 UTC
Report deadline12 Dec 2018, 22:48:00 UTC
Received16 Nov 2018, 10:25:59 UTC
Server stateOver
OutcomeSuccess
Client stateDone
Exit status0 (0x0)
Computer ID60920
Run time12 hours 13 min 57 sec
CPU time12 hours 9 min 34 sec
Validate stateValid
Credit6,823.67
Device peak FLOPS3.88 GFLOPS
Application versionEXACT Batch Norm With Scaled FMP CNN Trainer v0.34
Peak working set size515.83 MB
Peak swap size514.48 MB
Peak disk usage11.64 MB

Stderr output

<core_client_version>7.12.1</core_client_version>
<![CDATA[
<stderr_txt>
delta: 0.95
read initial_weight_decay: 0.0005
read weight_decay: 0.000407253
read weight_decay_delta: 0.95
read batch_size: 50
read epsilon: 1e-07
read alpha: 0.1
read input_dropout_probability: 0
read hidden_dropout_probability: 0
read velocity_reset: 1000
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: 5152
read best_validation_error: 15324.5
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: 5977
read normal distribution: '1 0 0'
generator_str: '1505299912'
read generator: 1505299912
read generated_by_map:
1 crossover 1
reading 92 nodes.
reading 377 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_1542277804_167_5977.txt'
boincified output filename: '../../projects/csgrid.org_csg/exact_genome_1542277804_167_5977_1_r1562212892_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: 0.5
read mu: 0.590892
read mu_delta: 0.95
read initial_learning_rate: 0.0125
read learning_rate: 0.0101813
read learning_rate_delta: 0.95
read initial_weight_decay: 0.0005
read weight_decay: 0.000407253
read weight_decay_delta: 0.95
read batch_size: 50
read epsilon: 1e-07
read alpha: 0.1
read input_dropout_probability: 0
read hidden_dropout_probability: 0
read velocity_reset: 1000
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: 5152
read best_validation_error: 15324.5
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: 5977
read normal distribution: '1 0 0'
generator_str: '1505299912'
read generator: 1505299912
read generated_by_map:
1 crossover 1
reading 92 nodes.
reading 377 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_1542277804_167_5977.txt'
boincified output filename: '../../projects/csgrid.org_csg/exact_genome_1542277804_167_5977_1_r1562212892_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: 0.5
read mu: 0.590892
read mu_delta: 0.95
read initial_learning_rate: 0.0125
read learning_rate: 0.0101813
read learning_rate_delta: 0.95
read initial_weight_decay: 0.0005
read weight_decay: 0.000407253
read weight_decay_delta: 0.95
read batch_size: 50
read epsilon: 1e-07
read alpha: 0.1
read input_dropout_probability: 0
read hidden_dropout_probability: 0
read velocity_reset: 1000
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: 5152
read best_validation_error: 15324.5
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: 5977
read normal distribution: '1 0 0'
generator_str: '1505299912'
read generator: 1505299912
read generated_by_map:
1 crossover 1
reading 92 nodes.
reading 377 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_1542277804_167_5977.txt'
boincified output filename: '../../projects/csgrid.org_csg/exact_genome_1542277804_167_5977_1_r1562212892_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: 0.5
read mu: 0.590892
read mu_delta: 0.95
read initial_learning_rate: 0.0125
read learning_rate: 0.0101813
read learning_rate_delta: 0.95
read initial_weight_decay: 0.0005
read weight_decay: 0.000407253
read weight_decay_delta: 0.95
read batch_size: 50
read epsilon: 1e-07
read alpha: 0.1
read input_dropout_probability: 0
read hidden_dropout_probability: 0
read velocity_reset: 1000
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: 5152
read best_validation_error: 15324.5
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: 5977
read normal distribution: '1 0 0'
generator_str: '1505299912'
read generator: 1505299912
read generated_by_map:
1 crossover 1
reading 92 nodes.
reading 377 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_1542277804_167_5977.txt'
boincified output filename: '../../projects/csgrid.org_csg/exact_genome_1542277804_167_5977_1_r1562212892_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: 0.5
read mu: 0.590892
read mu_delta: 0.95
read initial_learning_rate: 0.0125
read learning_rate: 0.0101813
read learning_rate_delta: 0.95
read initial_weight_decay: 0.0005
read weight_decay: 0.000407253
read weight_decay_delta: 0.95
read batch_size: 50
read epsilon: 1e-07
read alpha: 0.1
read input_dropout_probability: 0
read hidden_dropout_probability: 0
read velocity_reset: 1000
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: 5152
read best_validation_error: 15324.5
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: 5977
read normal distribution: '1 0 0'
generator_str: '1505299912'
read generator: 1505299912
read generated_by_map:
1 crossover 1
reading 92 nodes.
reading 377 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_1542277804_167_5977.txt'
boincified output filename: '../../projects/csgrid.org_csg/exact_genome_1542277804_167_5977_1_r1562212892_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: 0.5
read mu: 0.590892
read mu_delta: 0.95
read initial_learning_rate: 0.0125
read learning_rate: 0.0101813
read learning_rate_delta: 0.95
read initial_weight_decay: 0.0005
read weight_decay: 0.000407253
read weight_decay_delta: 0.95
read batch_size: 50
read epsilon: 1e-07
read alpha: 0.1
read input_dropout_probability: 0
read hidden_dropout_probability: 0
read velocity_reset: 1000
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: 5152
read best_validation_error: 15324.5
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: 5977
read normal distribution: '1 0 0'
generator_str: '1505299912'
read generator: 1505299912
read generated_by_map:
1 crossover 1
reading 92 nodes.
reading 377 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_1542277804_167_5977.txt'
boincified output filename: '../../projects/csgrid.org_csg/exact_genome_1542277804_167_5977_1_r1562212892_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: 0.5
read mu: 0.590892
read mu_delta: 0.95
read initial_learning_rate: 0.0125
read learning_rate: 0.0101813
read learning_rate_delta: 0.95
read initial_weight_decay: 0.0005
read weight_decay: 0.000407253
read weight_decay_delta: 0.95
read batch_size: 50
read epsilon: 1e-07
read alpha: 0.1
read input_dropout_probability: 0
read hidden_dropout_probability: 0
read velocity_reset: 1000
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: 5152
read best_validation_error: 15324.5
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: 5977
read normal distribution: '1 0 0'
generator_str: '1505299912'
read generator: 1505299912
read generated_by_map:
1 crossover 1
reading 92 nodes.
reading 377 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: 1564.2333984375s, input_fired_time: 8.87519931793213, output_fired_time: 8.81001567840576, propagate_forward_time: 598.508422851563, propagate_backward_time: 935.580749511719, weight_update_time: 1.41878461837769, other_time: 12.4589233398438
epoch time: 124.178215026855s, input_fired_time: 1.10017943382263, output_fired_time: 0, propagate_forward_time: 120.957801818848, propagate_backward_time: 0, weight_update_time: 0, other_time: 2.12023162841797
validation[          , genome  5977] predictions:    5069/  10000 (50.69%), best:    5152/10000 (51.52%), error:     15491.65918, best error:     15324.51367 on epoch:     3, epoch:    4/25, mu: 0.5908919573, learning_rate: 0.0101813274, weight_decay: 0.0004072531

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_1542277804_167_5977.txt'
boincified output filename: '../../projects/csgrid.org_csg/exact_genome_1542277804_167_5977_1_r1562212892_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: 0.5
read mu: 0.610847
read mu_delta: 0.95
read initial_learning_rate: 0.0125
read learning_rate: 0.00967226
read learning_rate_delta: 0.95
read initial_weight_decay: 0.0005
read weight_decay: 0.00038689
read weight_decay_delta: 0.95
read batch_size: 50
read epsilon: 1e-07
read alpha: 0.1
read input_dropout_probability: 0
read hidden_dropout_probability: 0
read velocity_reset: 1000
read epoch: 5
read max_epochs: 25
read reset_weights: 0
read padding: 2
read best_epoch: 3
read number_validation_images: 10000
read best_validation_predictions: 5152
read best_validation_error: 15324.5
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: 5977
read normal distribution: '1 0 0'
generator_str: '1196905979'
read generator: 1196905979
read generated_by_map:
1 crossover 1
reading 92 nodes.
reading 377 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_1542277804_167_5977.txt'
boincified output filename: '../../projects/csgrid.org_csg/exact_genome_1542277804_167_5977_1_r1562212892_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: 0.5
read mu: 0.610847
read mu_delta: 0.95
read initial_learning_rate: 0.0125
read learning_rate: 0.00967226
read learning_rate_delta: 0.95
read initial_weight_decay: 0.0005
read weight_decay: 0.00038689
read weight_decay_delta: 0.95
read batch_size: 50
read epsilon: 1e-07
read alpha: 0.1
read input_dropout_probability: 0
read hidden_dropout_probability: 0
read velocity_reset: 1000
read epoch: 5
read max_epochs: 25
read reset_weights: 0
read padding: 2
read best_epoch: 3
read number_validation_images: 10000
read best_validation_predictions: 5152
read best_validation_error: 15324.5
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: 5977
read normal distribution: '1 0 0'
generator_str: '1196905979'
read generator: 1196905979
read generated_by_map:
1 crossover 1
reading 92 nodes.
reading 377 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_1542277804_167_5977.txt'
boincified output filename: '../../projects/csgrid.org_csg/exact_genome_1542277804_167_5977_1_r1562212892_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: 0.5
read mu: 0.610847
read mu_delta: 0.95
read initial_learning_rate: 0.0125
read learning_rate: 0.00967226
read learning_rate_delta: 0.95
read initial_weight_decay: 0.0005
read weight_decay: 0.00038689
read weight_decay_delta: 0.95
read batch_size: 50
read epsilon: 1e-07
read alpha: 0.1
read input_dropout_probability: 0
read hidden_dropout_probability: 0
read velocity_reset: 1000
read epoch: 5
read max_epochs: 25
read reset_weights: 0
read padding: 2
read best_epoch: 3
read number_validation_images: 10000
read best_validation_predictions: 5152
read best_validation_error: 15324.5
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: 5977
read normal distribution: '1 0 0'
generator_str: '1196905979'
read generator: 1196905979
read generated_by_map:
1 crossover 1
reading 92 nodes.
reading 377 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: 1542.45275878906s, input_fired_time: 8.77809715270996, output_fired_time: 8.66767501831055, propagate_forward_time: 589.754089355469, propagate_backward_time: 922.98388671875, weight_update_time: 1.39864635467529, other_time: 12.2689819335938
epoch time: 121.262542724609s, input_fired_time: 1.07381749153137, output_fired_time: 0, propagate_forward_time: 118.114028930664, propagate_backward_time: 0, weight_update_time: 0, other_time: 2.07469940185547
validation[          , genome  5977] predictions:    5247/  10000 (52.47%), best:    5247/10000 (52.47%), error:     14566.34570, best error:     14566.34570 on epoch:     5, epoch:    5/25, mu: 0.6108473539, learning_rate: 0.0096722608, weight_decay: 0.0003868904

epoch time: 1540.7271728516s, input_fired_time: 8.7741355896, output_fired_time: 8.6409425735, propagate_forward_time: 588.8331909180, propagate_backward_time: 922.1918945313, weight_update_time: 1.3931777477, other_time: 12.2869262695
epoch time: 120.9347763062s, input_fired_time: 1.0702173710, output_fired_time: 0.0000000000, propagate_forward_time: 117.7935485840, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.0710067749
validation[          , genome  5977] predictions:    4998/  10000 (49.98%), best:    5247/10000 (52.47%), error:     16561.91211, best error:     14566.34570 on epoch:     5, epoch:    6/25, mu: 0.6298049688, learning_rate: 0.0091886474, weight_decay: 0.0003675459

epoch time: 1542.0429687500s, input_fired_time: 8.7762165070, output_fired_time: 8.6311492920, propagate_forward_time: 590.3117675781, propagate_backward_time: 922.0386352539, weight_update_time: 1.4124448299, other_time: 12.2852172852
epoch time: 121.0628814697s, input_fired_time: 1.0784208775, output_fired_time: 0.0000000000, propagate_forward_time: 117.9125595093, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.0718994141
validation[          , genome  5977] predictions:    5476/  10000 (54.76%), best:    5476/10000 (54.76%), error:     13914.50781, best error:     13914.50781 on epoch:     7, epoch:    7/25, mu: 0.6478147507, learning_rate: 0.0087292148, weight_decay: 0.0003491686

epoch time: 1542.5498046875s, input_fired_time: 8.7836399078, output_fired_time: 8.6547088623, propagate_forward_time: 589.8037719727, propagate_backward_time: 923.0036621094, weight_update_time: 1.3951458931, other_time: 12.3040161133
epoch time: 121.1108703613s, input_fired_time: 1.0867760181, output_fired_time: 0.0000000000, propagate_forward_time: 117.9578781128, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.0662155151
validation[          , genome  5977] predictions:    5053/  10000 (50.53%), best:    5476/10000 (54.76%), error:     16092.66016, best error:     13914.50781 on epoch:     7, epoch:    8/25, mu: 0.6649240255, learning_rate: 0.0082927542, weight_decay: 0.0003317102

epoch time: 1542.5972900391s, input_fired_time: 8.7763128281, output_fired_time: 8.7029418945, propagate_forward_time: 589.7627563477, propagate_backward_time: 923.1030883789, weight_update_time: 1.3982653618, other_time: 12.2520751953
epoch time: 120.6616363525s, input_fired_time: 1.0961679220, output_fired_time: 0.0000000000, propagate_forward_time: 117.4882202148, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.0772476196
validation[          , genome  5977] predictions:    5139/  10000 (51.39%), best:    5476/10000 (54.76%), error:     15473.16797, best error:     13914.50781 on epoch:     7, epoch:    9/25, mu: 0.6811778545, learning_rate: 0.0078781163, weight_decay: 0.0003151247

epoch time: 1541.8385009766s, input_fired_time: 8.7911930084, output_fired_time: 8.6561079025, propagate_forward_time: 589.5320434570, propagate_backward_time: 922.5989379883, weight_update_time: 1.3922851086, other_time: 12.2602539063
epoch time: 120.9891204834s, input_fired_time: 1.0997906923, output_fired_time: 0.0000000000, propagate_forward_time: 117.8222503662, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.0670776367
validation[          , genome  5977] predictions:    5243/  10000 (52.43%), best:    5476/10000 (54.76%), error:     14922.87793, best error:     13914.50781 on epoch:     7, epoch:   10/25, mu: 0.6966189742, learning_rate: 0.0074842102, weight_decay: 0.0002993684

epoch time: 1542.1519775391s, input_fired_time: 8.8216571808, output_fired_time: 8.6473302841, propagate_forward_time: 589.9735717773, propagate_backward_time: 922.4340209961, weight_update_time: 1.3970873356, other_time: 12.2753906250
epoch time: 121.2992706299s, input_fired_time: 1.0808323622, output_fired_time: 0.0000000000, propagate_forward_time: 118.1395034790, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.0789337158
validation[          , genome  5977] predictions:    5082/  10000 (50.82%), best:    5476/10000 (54.76%), error:     15626.61230, best error:     13914.50781 on epoch:     7, epoch:   11/25, mu: 0.7112880349, learning_rate: 0.0071099997, weight_decay: 0.0002844000

epoch time: 1542.7027587891s, input_fired_time: 8.8029422760, output_fired_time: 8.6367206573, propagate_forward_time: 589.7637329102, propagate_backward_time: 923.2203369141, weight_update_time: 1.3946181536, other_time: 12.2789916992
epoch time: 120.9039688110s, input_fired_time: 1.0796360970, output_fired_time: 0.0000000000, propagate_forward_time: 117.7541885376, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.0701446533
validation[          , genome  5977] predictions:    5202/  10000 (52.02%), best:    5476/10000 (54.76%), error:     14528.55957, best error:     13914.50781 on epoch:     7, epoch:   12/25, mu: 0.7252236605, learning_rate: 0.0067544994, weight_decay: 0.0002701800

epoch time: 1540.2807617188s, input_fired_time: 8.8114118576, output_fired_time: 8.6507015228, propagate_forward_time: 588.9425659180, propagate_backward_time: 921.6289672852, weight_update_time: 1.3953857422, other_time: 12.2470703125
epoch time: 120.9617691040s, input_fired_time: 1.0858017206, output_fired_time: 0.0000000000, propagate_forward_time: 117.7900772095, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.0858917236
validation[          , genome  5977] predictions:    5394/  10000 (53.94%), best:    5476/10000 (54.76%), error:     14241.35840, best error:     13914.50781 on epoch:     7, epoch:   13/25, mu: 0.7384625077, learning_rate: 0.0064167744, weight_decay: 0.0002566710

epoch time: 1540.3885498047s, input_fired_time: 8.8306560516, output_fired_time: 8.6391916275, propagate_forward_time: 589.2147827148, propagate_backward_time: 921.4551391602, weight_update_time: 1.3932864666, other_time: 12.2487792969
epoch time: 120.8633880615s, input_fired_time: 1.0752042532, output_fired_time: 0.0000000000, propagate_forward_time: 117.7272720337, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.0609130859
validation[          , genome  5977] predictions:    5497/  10000 (54.97%), best:    5476/10000 (54.76%), error:     13916.04980, best error:     13914.50781 on epoch:     7, epoch:   14/25, mu: 0.7510393858, learning_rate: 0.0060959356, weight_decay: 0.0002438374

epoch time: 1541.0412597656s, input_fired_time: 8.8592300415, output_fired_time: 8.6264047623, propagate_forward_time: 589.5467529297, propagate_backward_time: 921.7665405273, weight_update_time: 1.4003293514, other_time: 12.2422485352
epoch time: 120.9655990601s, input_fired_time: 1.1040389538, output_fired_time: 0.0000000000, propagate_forward_time: 117.7976608276, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.0638961792
validation[          , genome  5977] predictions:    5351/  10000 (53.51%), best:    5476/10000 (54.76%), error:     14783.15723, best error:     13914.50781 on epoch:     7, epoch:   15/25, mu: 0.7629874349, learning_rate: 0.0057911389, weight_decay: 0.0002316456

epoch time: 1540.9482421875s, input_fired_time: 8.8508644104, output_fired_time: 8.6452960968, propagate_forward_time: 589.5537109375, propagate_backward_time: 921.6487426758, weight_update_time: 1.3953341246, other_time: 12.2496948242
epoch time: 120.9225463867s, input_fired_time: 1.0889027119, output_fired_time: 0.0000000000, propagate_forward_time: 117.7441406250, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.0895004272
validation[          , genome  5977] predictions:    5099/  10000 (50.99%), best:    5476/10000 (54.76%), error:     15326.68164, best error:     13914.50781 on epoch:     7, epoch:   16/25, mu: 0.7743380666, learning_rate: 0.0055015818, weight_decay: 0.0002200633

epoch time: 1547.1401367188s, input_fired_time: 8.8740615845, output_fired_time: 8.6602191925, propagate_forward_time: 591.7297363281, propagate_backward_time: 925.5683593750, weight_update_time: 1.3978523016, other_time: 12.3077392578
epoch time: 120.8572006226s, input_fired_time: 1.1040213108, output_fired_time: 0.0000000000, propagate_forward_time: 117.6622161865, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.0909652710
validation[          , genome  5977] predictions:    5491/  10000 (54.91%), best:    5491/10000 (54.91%), error:     13702.81641, best error:     13702.81641 on epoch:    17, epoch:   17/25, mu: 0.7851211429, learning_rate: 0.0052265027, weight_decay: 0.0002090601

epoch time: 1541.7153320313s, input_fired_time: 8.8478775024, output_fired_time: 8.6324024200, propagate_forward_time: 589.5297241211, propagate_backward_time: 922.4669189453, weight_update_time: 1.3954918385, other_time: 12.2383422852
epoch time: 121.2870788574s, input_fired_time: 1.1031095982, output_fired_time: 0.0000000000, propagate_forward_time: 118.1269531250, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.0570144653
validation[          , genome  5977] predictions:    5326/  10000 (53.26%), best:    5491/10000 (54.91%), error:     15313.52148, best error:     13702.81641 on epoch:    17, epoch:   18/25, mu: 0.7953650951, learning_rate: 0.0049651773, weight_decay: 0.0001986071

epoch time: 1541.2471923828s, input_fired_time: 8.8746042252, output_fired_time: 8.6442832947, propagate_forward_time: 589.6229248047, propagate_backward_time: 921.7992553711, weight_update_time: 1.4188338518, other_time: 12.3060913086
epoch time: 121.0312881470s, input_fired_time: 1.0994250774, output_fired_time: 0.0000000000, propagate_forward_time: 117.8762207031, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.0556411743
validation[          , genome  5977] predictions:    5587/  10000 (55.87%), best:    5587/10000 (55.87%), error:     13456.53418, best error:     13456.53418 on epoch:    19, epoch:   19/25, mu: 0.8050968647, learning_rate: 0.0047169183, weight_decay: 0.0001886768

epoch time: 1544.1488037109s, input_fired_time: 8.9057235718, output_fired_time: 8.6525535583, propagate_forward_time: 589.9888916016, propagate_backward_time: 924.3616333008, weight_update_time: 1.3895434141, other_time: 12.2399291992
epoch time: 121.1515731812s, input_fired_time: 1.1077686548, output_fired_time: 0.0000000000, propagate_forward_time: 117.9671478271, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.0766601563
validation[          , genome  5977] predictions:    5537/  10000 (55.37%), best:    5587/10000 (55.87%), error:     13937.05957, best error:     13456.53418 on epoch:    19, epoch:   20/25, mu: 0.8143420219, learning_rate: 0.0044810725, weight_decay: 0.0001792429

epoch time: 1540.9356689453s, input_fired_time: 8.8985271454, output_fired_time: 8.6510906219, propagate_forward_time: 589.2587890625, propagate_backward_time: 921.8403930664, weight_update_time: 1.3990755081, other_time: 12.2868041992
epoch time: 121.1773910522s, input_fired_time: 1.1027170420, output_fired_time: 0.0000000000, propagate_forward_time: 117.9901504517, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.0845260620
validation[          , genome  5977] predictions:    5576/  10000 (55.76%), best:    5587/10000 (55.87%), error:     13465.64844, best error:     13456.53418 on epoch:    19, epoch:   21/25, mu: 0.8231249452, learning_rate: 0.0042570187, weight_decay: 0.0001702808

epoch time: 1542.0545654297s, input_fired_time: 8.8962059021, output_fired_time: 8.6192417145, propagate_forward_time: 589.9047241211, propagate_backward_time: 922.3293457031, weight_update_time: 1.3920675516, other_time: 12.3049926758
epoch time: 121.3664016724s, input_fired_time: 1.0848280191, output_fired_time: 0.0000000000, propagate_forward_time: 118.2216110229, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.0599594116
validation[          , genome  5977] predictions:    5117/  10000 (51.17%), best:    5587/10000 (55.87%), error:     15448.95996, best error:     13456.53418 on epoch:    19, epoch:   22/25, mu: 0.8314687014, learning_rate: 0.0040441677, weight_decay: 0.0001617667

epoch time: 1541.4705810547s, input_fired_time: 8.9284133911, output_fired_time: 8.6258296967, propagate_forward_time: 589.7782592773, propagate_backward_time: 921.8369750977, weight_update_time: 1.3998486996, other_time: 12.3010253906
epoch time: 121.0159149170s, input_fired_time: 1.1091927290, output_fired_time: 0.0000000000, propagate_forward_time: 117.8277435303, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.0789794922
validation[          , genome  5977] predictions:    5543/  10000 (55.43%), best:    5587/10000 (55.87%), error:     14002.03809, best error:     13456.53418 on epoch:    19, epoch:   23/25, mu: 0.8393952847, learning_rate: 0.0038419592, weight_decay: 0.0001536784

epoch time: 1540.7648925781s, input_fired_time: 8.9133901596, output_fired_time: 8.6434650421, propagate_forward_time: 588.8414306641, propagate_backward_time: 922.1187744141, weight_update_time: 1.3933352232, other_time: 12.2479248047
epoch time: 121.1407318115s, input_fired_time: 1.1169573069, output_fired_time: 0.0000000000, propagate_forward_time: 117.8659057617, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.1578674316
validation[          , genome  5977] predictions:    5544/  10000 (55.44%), best:    5587/10000 (55.87%), error:     14044.76172, best error:     13456.53418 on epoch:    19, epoch:   24/25, mu: 0.8469254971, learning_rate: 0.0036498611, weight_decay: 0.0001459945

epoch time: 1541.1835937500s, input_fired_time: 8.9414768219, output_fired_time: 8.6583557129, propagate_forward_time: 589.3680419922, propagate_backward_time: 921.9446411133, weight_update_time: 1.4006662369, other_time: 12.2710571289
epoch time: 120.8466796875s, input_fired_time: 1.1205582619, output_fired_time: 0.0000000000, propagate_forward_time: 117.6569595337, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.0691604614
validation[          , genome  5977] predictions:    5778/  10000 (57.78%), best:    5778/10000 (57.78%), error:     12819.10840, best error:     12819.10840 on epoch:    25, epoch:   25/25, mu: 0.8540792465, learning_rate: 0.0034673680, weight_decay: 0.0001386948

evaluating best weights on full training data.
evaluting training set with running mean/variance:
epoch time: 605.4756469727s, input_fired_time: 5.5978870392, output_fired_time: 0.0000000000, propagate_forward_time: 589.4852294922, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 10.3925170898
best training[          , genome  5977] predictions:   32628/  50000 (65.26%), best:    5778/10000 (57.78%), error:     50918.52344, best error:     12819.10840 on epoch:    25, epoch:   26/25, mu: 0.8608753085, learning_rate: 0.0032939995, weight_decay: 0.0001317600
evaluating best weights on test data.
evaluting test set with running mean/variance:
epoch time: 121.1264266968s, input_fired_time: 1.1164821386, output_fired_time: 0.0000000000, propagate_forward_time: 117.9528350830, propagate_backward_time: 0.0000000000, weight_update_time: 0.0000000000, other_time: 2.0571060181
   testing[          , genome  5977] predictions:    5778/  10000 (57.78%), best:    5778/10000 (57.78%), error:     12819.10840, best error:     12819.10840 on epoch:    25, epoch:   26/25, mu: 0.8608753085, learning_rate: 0.0032939995, weight_decay: 0.0001317600
backpropagation finished successfully!
04:01:41 (18544): called boinc_finish(0)

</stderr_txt>
]]>