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___ ___ ___ ___ _____ ___
| \_ _/ __|_ _|_ _/ __|
| |) | | (_ || | | | \__ \
|___/___\___|___| |_| |___/ 5.1-dev
----------------------------------------
executable, version, flavor /home/mayang/caffe/build/tools/caffe 1.0.0 BVLC
2017-10-11 19:43:52 [INFO ] Loaded 23 jobs.
caffe_cudnn_cifar10,caffe_stream,caffe_master
20171009-162153-6158,20171009-155942-4fb9,20171009-155621-3891
~~~~~~~~~
/home/mayang/DIGITS/digits/jobs/20171009-162153-6158/caffe_output.log
<><><><><>-----------------------------
/home/mayang/DIGITS/digits/jobs/20171009-155942-4fb9/caffe_output.log
<><><><><>-----------------------------
/home/mayang/DIGITS/digits/jobs/20171009-155621-3891/caffe_output.log
<><><><><>-----------------------------
0.083492,0.50254,0.584603,0.619683,0.658254,0.658651,0.71254,0.715397,0.715873,0.718016,0.723651,0.725714,0.726032,0.727301,0.726905,0.725952,
0.1968,0.979133,0.983799,0.984799,0.985333,0.985399,
0.0628,0.977666,0.984266,0.986,0.9862,0.9864,
16
'0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15',
0,0.1968,0.979133,0.983799,0.983799,0.984799,0.985333,0.985333,
0,0.0628,0.0628,0.0628,0.977666,0.977666,0.977666,0.977666,0.984266,0.984266,0.984266,0.986,0.986,0.986,0.986,0.9862,0.9862,0.9862,0.9862,
<><><><###############
1
------------------
<><><><><>!!!!!<><><><><>
['/usr/bin/python2', '/home/mayang/mxnet-0.11.0/example/image-classification/train_mnist.py', '--gpu=0', '--lr=0.01', u'--network=lenet', '--num-epochs=10', '--batch-size=64']
---------------
2017-10-11 19:46:26 [20171011-194625-e1fc] [INFO ] Train Mxnet Model task started.
2017-10-11 19:46:26 [20171011-194625-e1fc] [INFO ] Task subprocess args: "/usr/bin/python2 /home/mayang/mxnet-0.11.0/example/image-classification/train_mnist.py --gpu=0 --lr=0.01 --network=lenet --num-epochs=10 --batch-size=64"
2017-10-11 19:46:26 [20171011-194625-e1fc] [INFO ] args = /usr/bin/python2/home/mayang/mxnet-0.11.0/example/image-classification/train_mnist.py--gpu=0--lr=0.01--network=lenet--num-epochs=10--batch-size=64
INFO:root:start with arguments Namespace(add_stn=False, batch_size=64, disp_batches=100, dtype='float32', gpus='0', kv_store='device', load_epoch=None, lr=0.01, lr_factor=0.1, lr_step_epochs='10', model_prefix=None, mom=0.9, monitor=0, network='lenet', num_classes=10, num_epochs=10, num_examples=60000, num_layers=None, optimizer='sgd', test_io=0, top_k=0, wd=0.0001)
[19:46:32] src/operator/././cudnn_algoreg-inl.h:112: Running performance tests to find the best convolution algorithm, this can take a while... (setting env variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable)
INFO:root:Epoch[0] Batch [100] Speed: 30941.64 samples/sec accuracy=0.812809
2017-10-11 19:46:32 [20171011-194625-e1fc] [INFO ] OrderedDict()
2017-10-11 19:46:32 [20171011-194625-e1fc] [DEBUG] Training 0.0% complete.
2017-10-11 19:46:32 [20171011-194625-e1fc] [INFO ] OrderedDict()
2017-10-11 19:46:32 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0]))])
[0] Batch [100] Speed: 30941.64 samples/sec accuracy=0.812809
send progress update signl~~~ 1
<><><><><><><><><><>
0.1
<><><><><><><><><><>
2017-10-11 19:46:32 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01]))])
2017-10-11 19:46:32 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.812809])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01]))])
INFO:root:Epoch[0] Batch [200] Speed: 34737.46 samples/sec accuracy=0.940781
[0] Batch [200] Speed: 34737.46 samples/sec accuracy=0.940781
INFO:root:Epoch[0] Batch [300] Speed: 35660.16 samples/sec accuracy=0.955781
[0] Batch [300] Speed: 35660.16 samples/sec accuracy=0.955781
INFO:root:Epoch[0] Batch [400] Speed: 34704.90 samples/sec accuracy=0.957500
[0] Batch [400] Speed: 34704.90 samples/sec accuracy=0.957500
INFO:root:Epoch[0] Batch [500] Speed: 35194.26 samples/sec accuracy=0.966094
[0] Batch [500] Speed: 35194.26 samples/sec accuracy=0.966094
INFO:root:Epoch[0] Batch [600] Speed: 34870.17 samples/sec accuracy=0.969375
[0] Batch [600] Speed: 34870.17 samples/sec accuracy=0.969375
INFO:root:Epoch[0] Batch [700] Speed: 34011.98 samples/sec accuracy=0.972187
[0] Batch [700] Speed: 34011.98 samples/sec accuracy=0.972187
INFO:root:Epoch[0] Batch [800] Speed: 35047.18 samples/sec accuracy=0.973750
[0] Batch [800] Speed: 35047.18 samples/sec accuracy=0.973750
INFO:root:Epoch[0] Batch [900] Speed: 37065.56 samples/sec accuracy=0.978750
[0] Batch [900] Speed: 37065.56 samples/sec accuracy=0.978750
INFO:root:Epoch[0] Train-accuracy=0.979730
[0] Train-accuracy=0.979730
INFO:root:Epoch[0] Time cost=1.798
[0] Time cost=1.798
INFO:root:Epoch[0] Validation-accuracy=0.981290
[0] Validation-accuracy=0.981290
send progress update signl~~~ 1
2017-10-11 19:46:34 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0])), ('accuracy', NetworkOutput(kind='Accuracy', data=[0.0]))])
INFO:root:Epoch[1] Batch [100] Speed: 31884.10 samples/sec accuracy=0.977723
[1] Batch [100] Speed: 31884.10 samples/sec accuracy=0.977723
send progress update signl~~~ 2
<><><><><><><><><><>
0.2
<><><><><><><><><><>
2017-10-11 19:46:34 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.812809])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01]))])
2017-10-11 19:46:34 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.812809, 0.977723])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01]))])
INFO:root:Epoch[1] Batch [200] Speed: 33272.32 samples/sec accuracy=0.979375
[1] Batch [200] Speed: 33272.32 samples/sec accuracy=0.979375
INFO:root:Epoch[1] Batch [300] Speed: 33993.16 samples/sec accuracy=0.983594
[1] Batch [300] Speed: 33993.16 samples/sec accuracy=0.983594
INFO:root:Epoch[1] Batch [400] Speed: 34220.93 samples/sec accuracy=0.982969
[1] Batch [400] Speed: 34220.93 samples/sec accuracy=0.982969
INFO:root:Epoch[1] Batch [500] Speed: 32478.07 samples/sec accuracy=0.986406
[1] Batch [500] Speed: 32478.07 samples/sec accuracy=0.986406
INFO:root:Epoch[1] Batch [600] Speed: 35308.38 samples/sec accuracy=0.986563
[1] Batch [600] Speed: 35308.38 samples/sec accuracy=0.986563
INFO:root:Epoch[1] Batch [700] Speed: 37719.57 samples/sec accuracy=0.986094
[1] Batch [700] Speed: 37719.57 samples/sec accuracy=0.986094
INFO:root:Epoch[1] Batch [800] Speed: 37792.91 samples/sec accuracy=0.984531
[1] Batch [800] Speed: 37792.91 samples/sec accuracy=0.984531
INFO:root:Epoch[1] Batch [900] Speed: 37278.66 samples/sec accuracy=0.985781
[1] Batch [900] Speed: 37278.66 samples/sec accuracy=0.985781
INFO:root:Epoch[1] Train-accuracy=0.984375
[1] Train-accuracy=0.984375
INFO:root:Epoch[1] Time cost=1.725
[1] Time cost=1.725
INFO:root:Epoch[1] Validation-accuracy=0.985072
[1] Validation-accuracy=0.985072
send progress update signl~~~ 2
2017-10-11 19:46:36 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0])), ('accuracy', NetworkOutput(kind='Accuracy', data=[0.0, 0.98129]))])
INFO:root:Epoch[2] Batch [100] Speed: 32589.54 samples/sec accuracy=0.987314
[2] Batch [100] Speed: 32589.54 samples/sec accuracy=0.987314
send progress update signl~~~ 3
<><><><><><><><><><>
0.3
<><><><><><><><><><>
2017-10-11 19:46:36 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.812809, 0.977723])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01]))])
2017-10-11 19:46:36 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.812809, 0.977723, 0.987314])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01]))])
INFO:root:Epoch[2] Batch [200] Speed: 37260.66 samples/sec accuracy=0.988125
[2] Batch [200] Speed: 37260.66 samples/sec accuracy=0.988125
INFO:root:Epoch[2] Batch [300] Speed: 36584.60 samples/sec accuracy=0.988594
[2] Batch [300] Speed: 36584.60 samples/sec accuracy=0.988594
INFO:root:Epoch[2] Batch [400] Speed: 36895.91 samples/sec accuracy=0.990000
[2] Batch [400] Speed: 36895.91 samples/sec accuracy=0.990000
INFO:root:Epoch[2] Batch [500] Speed: 37213.65 samples/sec accuracy=0.989844
[2] Batch [500] Speed: 37213.65 samples/sec accuracy=0.989844
INFO:root:Epoch[2] Batch [600] Speed: 37564.86 samples/sec accuracy=0.990625
[2] Batch [600] Speed: 37564.86 samples/sec accuracy=0.990625
INFO:root:Epoch[2] Batch [700] Speed: 37972.70 samples/sec accuracy=0.989531
[2] Batch [700] Speed: 37972.70 samples/sec accuracy=0.989531
INFO:root:Epoch[2] Batch [800] Speed: 37600.43 samples/sec accuracy=0.990000
[2] Batch [800] Speed: 37600.43 samples/sec accuracy=0.990000
INFO:root:Epoch[2] Batch [900] Speed: 37618.71 samples/sec accuracy=0.989844
[2] Batch [900] Speed: 37618.71 samples/sec accuracy=0.989844
INFO:root:Epoch[2] Train-accuracy=0.989020
[2] Train-accuracy=0.989020
INFO:root:Epoch[2] Time cost=1.634
[2] Time cost=1.634
INFO:root:Epoch[2] Validation-accuracy=0.987361
[2] Validation-accuracy=0.987361
send progress update signl~~~ 3
2017-10-11 19:46:38 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0])), ('accuracy', NetworkOutput(kind='Accuracy', data=[0.0, 0.98129, 0.985072]))])
INFO:root:Epoch[3] Batch [100] Speed: 32293.22 samples/sec accuracy=0.990254
[3] Batch [100] Speed: 32293.22 samples/sec accuracy=0.990254
send progress update signl~~~ 4
<><><><><><><><><><>
0.4
<><><><><><><><><><>
2017-10-11 19:46:38 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.812809, 0.977723, 0.987314])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01]))])
2017-10-11 19:46:38 [20171011-194625-e1fc] [DEBUG] Training 40.0% complete.
2017-10-11 19:46:38 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.812809, 0.977723, 0.987314, 0.990254])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01]))])
INFO:root:Epoch[3] Batch [200] Speed: 36539.48 samples/sec accuracy=0.991875
[3] Batch [200] Speed: 36539.48 samples/sec accuracy=0.991875
INFO:root:Epoch[3] Batch [300] Speed: 35234.92 samples/sec accuracy=0.993437
[3] Batch [300] Speed: 35234.92 samples/sec accuracy=0.993437
INFO:root:Epoch[3] Batch [400] Speed: 34795.86 samples/sec accuracy=0.993125
[3] Batch [400] Speed: 34795.86 samples/sec accuracy=0.993125
INFO:root:Epoch[3] Batch [500] Speed: 34716.79 samples/sec accuracy=0.992656
[3] Batch [500] Speed: 34716.79 samples/sec accuracy=0.992656
INFO:root:Epoch[3] Batch [600] Speed: 35232.37 samples/sec accuracy=0.992812
[3] Batch [600] Speed: 35232.37 samples/sec accuracy=0.992812
INFO:root:Epoch[3] Batch [700] Speed: 35110.81 samples/sec accuracy=0.993125
[3] Batch [700] Speed: 35110.81 samples/sec accuracy=0.993125
INFO:root:Epoch[3] Batch [800] Speed: 35324.78 samples/sec accuracy=0.992812
[3] Batch [800] Speed: 35324.78 samples/sec accuracy=0.992812
INFO:root:Epoch[3] Batch [900] Speed: 36644.53 samples/sec accuracy=0.992812
[3] Batch [900] Speed: 36644.53 samples/sec accuracy=0.992812
INFO:root:Epoch[3] Train-accuracy=0.992821
[3] Train-accuracy=0.992821
INFO:root:Epoch[3] Time cost=1.712
[3] Time cost=1.712
INFO:root:Epoch[3] Validation-accuracy=0.988057
[3] Validation-accuracy=0.988057
send progress update signl~~~ 4
2017-10-11 19:46:40 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0])), ('accuracy', NetworkOutput(kind='Accuracy', data=[0.0, 0.98129, 0.985072, 0.987361]))])
INFO:root:Epoch[4] Batch [100] Speed: 33113.08 samples/sec accuracy=0.993193
[4] Batch [100] Speed: 33113.08 samples/sec accuracy=0.993193
send progress update signl~~~ 5
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0.5
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2017-10-11 19:46:40 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.812809, 0.977723, 0.987314, 0.990254])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01]))])
2017-10-11 19:46:40 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.812809, 0.977723, 0.987314, 0.990254, 0.993193])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01]))])
INFO:root:Epoch[4] Batch [200] Speed: 34847.94 samples/sec accuracy=0.993906
[4] Batch [200] Speed: 34847.94 samples/sec accuracy=0.993906
INFO:root:Epoch[4] Batch [300] Speed: 35842.86 samples/sec accuracy=0.994844
[4] Batch [300] Speed: 35842.86 samples/sec accuracy=0.994844
INFO:root:Epoch[4] Batch [400] Speed: 35426.64 samples/sec accuracy=0.994687
[4] Batch [400] Speed: 35426.64 samples/sec accuracy=0.994687
INFO:root:Epoch[4] Batch [500] Speed: 34066.84 samples/sec accuracy=0.994219
[4] Batch [500] Speed: 34066.84 samples/sec accuracy=0.994219
INFO:root:Epoch[4] Batch [600] Speed: 33512.63 samples/sec accuracy=0.995000
[4] Batch [600] Speed: 33512.63 samples/sec accuracy=0.995000
INFO:root:Epoch[4] Batch [700] Speed: 34144.80 samples/sec accuracy=0.995313
[4] Batch [700] Speed: 34144.80 samples/sec accuracy=0.995313
INFO:root:Epoch[4] Batch [800] Speed: 33488.75 samples/sec accuracy=0.994375
[4] Batch [800] Speed: 33488.75 samples/sec accuracy=0.994375
INFO:root:Epoch[4] Batch [900] Speed: 33162.33 samples/sec accuracy=0.994687
[4] Batch [900] Speed: 33162.33 samples/sec accuracy=0.994687
INFO:root:Epoch[4] Train-accuracy=0.994932
[4] Train-accuracy=0.994932
INFO:root:Epoch[4] Time cost=1.760
[4] Time cost=1.760
INFO:root:Epoch[4] Validation-accuracy=0.988654
[4] Validation-accuracy=0.988654
send progress update signl~~~ 5
2017-10-11 19:46:42 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0])), ('accuracy', NetworkOutput(kind='Accuracy', data=[0.0, 0.98129, 0.985072, 0.987361, 0.988057]))])
INFO:root:Epoch[5] Batch [100] Speed: 31086.84 samples/sec accuracy=0.995978
[5] Batch [100] Speed: 31086.84 samples/sec accuracy=0.995978
send progress update signl~~~ 6
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0.6
<><><><><><><><><><>
2017-10-11 19:46:42 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.812809, 0.977723, 0.987314, 0.990254, 0.993193])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01]))])
2017-10-11 19:46:42 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.812809, 0.977723, 0.987314, 0.990254, 0.993193, 0.995978])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01]))])
INFO:root:Epoch[5] Batch [200] Speed: 34447.88 samples/sec accuracy=0.995156
[5] Batch [200] Speed: 34447.88 samples/sec accuracy=0.995156
INFO:root:Epoch[5] Batch [300] Speed: 34669.00 samples/sec accuracy=0.996250
[5] Batch [300] Speed: 34669.00 samples/sec accuracy=0.996250
INFO:root:Epoch[5] Batch [400] Speed: 35095.98 samples/sec accuracy=0.996250
[5] Batch [400] Speed: 35095.98 samples/sec accuracy=0.996250
INFO:root:Epoch[5] Batch [500] Speed: 34963.50 samples/sec accuracy=0.995938
[5] Batch [500] Speed: 34963.50 samples/sec accuracy=0.995938
INFO:root:Epoch[5] Batch [600] Speed: 34338.42 samples/sec accuracy=0.997500
[5] Batch [600] Speed: 34338.42 samples/sec accuracy=0.997500
INFO:root:Epoch[5] Batch [700] Speed: 36683.39 samples/sec accuracy=0.996719
[5] Batch [700] Speed: 36683.39 samples/sec accuracy=0.996719
INFO:root:Epoch[5] Batch [800] Speed: 36912.91 samples/sec accuracy=0.995781
[5] Batch [800] Speed: 36912.91 samples/sec accuracy=0.995781
INFO:root:Epoch[5] Batch [900] Speed: 37583.16 samples/sec accuracy=0.996563
[5] Batch [900] Speed: 37583.16 samples/sec accuracy=0.996563
INFO:root:Epoch[5] Train-accuracy=0.996199
[5] Train-accuracy=0.996199
INFO:root:Epoch[5] Time cost=1.713
[5] Time cost=1.713
INFO:root:Epoch[5] Validation-accuracy=0.989650
[5] Validation-accuracy=0.989650
send progress update signl~~~ 6
2017-10-11 19:46:43 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0])), ('accuracy', NetworkOutput(kind='Accuracy', data=[0.0, 0.98129, 0.985072, 0.987361, 0.988057, 0.988654]))])
INFO:root:Epoch[6] Batch [100] Speed: 30915.77 samples/sec accuracy=0.997215
[6] Batch [100] Speed: 30915.77 samples/sec accuracy=0.997215
send progress update signl~~~ 7
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0.7
<><><><><><><><><><>
2017-10-11 19:46:44 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.812809, 0.977723, 0.987314, 0.990254, 0.993193, 0.995978])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01]))])
2017-10-11 19:46:44 [20171011-194625-e1fc] [DEBUG] Training 70.0% complete.
2017-10-11 19:46:44 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.812809, 0.977723, 0.987314, 0.990254, 0.993193, 0.995978, 0.997215])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01]))])
INFO:root:Epoch[6] Batch [200] Speed: 34620.44 samples/sec accuracy=0.995938
[6] Batch [200] Speed: 34620.44 samples/sec accuracy=0.995938
INFO:root:Epoch[6] Batch [300] Speed: 35491.70 samples/sec accuracy=0.997656
[6] Batch [300] Speed: 35491.70 samples/sec accuracy=0.997656
INFO:root:Epoch[6] Batch [400] Speed: 35451.77 samples/sec accuracy=0.997656
[6] Batch [400] Speed: 35451.77 samples/sec accuracy=0.997656
INFO:root:Epoch[6] Batch [500] Speed: 35333.75 samples/sec accuracy=0.996875
[6] Batch [500] Speed: 35333.75 samples/sec accuracy=0.996875
INFO:root:Epoch[6] Batch [600] Speed: 37740.94 samples/sec accuracy=0.998750
[6] Batch [600] Speed: 37740.94 samples/sec accuracy=0.998750
INFO:root:Epoch[6] Batch [700] Speed: 37708.71 samples/sec accuracy=0.997812
[6] Batch [700] Speed: 37708.71 samples/sec accuracy=0.997812
INFO:root:Epoch[6] Batch [800] Speed: 37566.80 samples/sec accuracy=0.997656
[6] Batch [800] Speed: 37566.80 samples/sec accuracy=0.997656
INFO:root:Epoch[6] Batch [900] Speed: 37312.34 samples/sec accuracy=0.997969
[6] Batch [900] Speed: 37312.34 samples/sec accuracy=0.997969
INFO:root:Epoch[6] Train-accuracy=0.997466
[6] Train-accuracy=0.997466
INFO:root:Epoch[6] Time cost=1.681
[6] Time cost=1.681
INFO:root:Epoch[6] Validation-accuracy=0.990147
[6] Validation-accuracy=0.990147
send progress update signl~~~ 7
2017-10-11 19:46:45 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0])), ('accuracy', NetworkOutput(kind='Accuracy', data=[0.0, 0.98129, 0.985072, 0.987361, 0.988057, 0.988654, 0.98965]))])
INFO:root:Epoch[7] Batch [100] Speed: 37805.41 samples/sec accuracy=0.997834
[7] Batch [100] Speed: 37805.41 samples/sec accuracy=0.997834
send progress update signl~~~ 8
<><><><><><><><><><>
0.8
<><><><><><><><><><>
2017-10-11 19:46:46 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.812809, 0.977723, 0.987314, 0.990254, 0.993193, 0.995978, 0.997215])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01]))])
2017-10-11 19:46:46 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.812809, 0.977723, 0.987314, 0.990254, 0.993193, 0.995978, 0.997215, 0.997834])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01]))])
INFO:root:Epoch[7] Batch [200] Speed: 36876.55 samples/sec accuracy=0.997031
[7] Batch [200] Speed: 36876.55 samples/sec accuracy=0.997031
INFO:root:Epoch[7] Batch [300] Speed: 37320.59 samples/sec accuracy=0.998594
[7] Batch [300] Speed: 37320.59 samples/sec accuracy=0.998594
INFO:root:Epoch[7] Batch [400] Speed: 37344.32 samples/sec accuracy=0.998281
[7] Batch [400] Speed: 37344.32 samples/sec accuracy=0.998281
INFO:root:Epoch[7] Batch [500] Speed: 37518.60 samples/sec accuracy=0.997812
[7] Batch [500] Speed: 37518.60 samples/sec accuracy=0.997812
INFO:root:Epoch[7] Batch [600] Speed: 37823.90 samples/sec accuracy=0.999219
[7] Batch [600] Speed: 37823.90 samples/sec accuracy=0.999219
INFO:root:Epoch[7] Batch [700] Speed: 37722.75 samples/sec accuracy=0.998594
[7] Batch [700] Speed: 37722.75 samples/sec accuracy=0.998594
INFO:root:Epoch[7] Batch [800] Speed: 37691.60 samples/sec accuracy=0.998125
[7] Batch [800] Speed: 37691.60 samples/sec accuracy=0.998125
INFO:root:Epoch[7] Batch [900] Speed: 37625.35 samples/sec accuracy=0.998750
[7] Batch [900] Speed: 37625.35 samples/sec accuracy=0.998750
INFO:root:Epoch[7] Train-accuracy=0.997889
[7] Train-accuracy=0.997889
INFO:root:Epoch[7] Time cost=1.601
[7] Time cost=1.601
INFO:root:Epoch[7] Validation-accuracy=0.989948
[7] Validation-accuracy=0.989948
send progress update signl~~~ 8
2017-10-11 19:46:47 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0])), ('accuracy', NetworkOutput(kind='Accuracy', data=[0.0, 0.98129, 0.985072, 0.987361, 0.988057, 0.988654, 0.98965, 0.990147]))])
INFO:root:Epoch[8] Batch [100] Speed: 31933.41 samples/sec accuracy=0.998608
[8] Batch [100] Speed: 31933.41 samples/sec accuracy=0.998608
send progress update signl~~~ 9
<><><><><><><><><><>
0.9
<><><><><><><><><><>
2017-10-11 19:46:47 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.812809, 0.977723, 0.987314, 0.990254, 0.993193, 0.995978, 0.997215, 0.997834])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01]))])
2017-10-11 19:46:47 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.812809, 0.977723, 0.987314, 0.990254, 0.993193, 0.995978, 0.997215, 0.997834, 0.998608])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01]))])
INFO:root:Epoch[8] Batch [200] Speed: 36262.08 samples/sec accuracy=0.997500
[8] Batch [200] Speed: 36262.08 samples/sec accuracy=0.997500
INFO:root:Epoch[8] Batch [300] Speed: 37165.89 samples/sec accuracy=0.999062
[8] Batch [300] Speed: 37165.89 samples/sec accuracy=0.999062
INFO:root:Epoch[8] Batch [400] Speed: 37782.37 samples/sec accuracy=0.998750
[8] Batch [400] Speed: 37782.37 samples/sec accuracy=0.998750
INFO:root:Epoch[8] Batch [500] Speed: 37730.97 samples/sec accuracy=0.998437
[8] Batch [500] Speed: 37730.97 samples/sec accuracy=0.998437
INFO:root:Epoch[8] Batch [600] Speed: 37933.15 samples/sec accuracy=0.999531
[8] Batch [600] Speed: 37933.15 samples/sec accuracy=0.999531
INFO:root:Epoch[8] Batch [700] Speed: 37169.95 samples/sec accuracy=0.999531
[8] Batch [700] Speed: 37169.95 samples/sec accuracy=0.999531
INFO:root:Epoch[8] Batch [800] Speed: 37082.30 samples/sec accuracy=0.998594
[8] Batch [800] Speed: 37082.30 samples/sec accuracy=0.998594
INFO:root:Epoch[8] Batch [900] Speed: 37045.41 samples/sec accuracy=0.999687
[8] Batch [900] Speed: 37045.41 samples/sec accuracy=0.999687
INFO:root:Epoch[8] Train-accuracy=0.998733
[8] Train-accuracy=0.998733
INFO:root:Epoch[8] Time cost=1.644
[8] Time cost=1.644
INFO:root:Epoch[8] Validation-accuracy=0.990346
[8] Validation-accuracy=0.990346
send progress update signl~~~ 9
2017-10-11 19:46:49 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0])), ('accuracy', NetworkOutput(kind='Accuracy', data=[0.0, 0.98129, 0.985072, 0.987361, 0.988057, 0.988654, 0.98965, 0.990147, 0.989948]))])
INFO:root:Epoch[9] Batch [100] Speed: 36111.44 samples/sec accuracy=0.998917
[9] Batch [100] Speed: 36111.44 samples/sec accuracy=0.998917
send progress update signl~~~ 10
<><><><><><><><><><>
1.0
<><><><><><><><><><>
2017-10-11 19:46:49 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.812809, 0.977723, 0.987314, 0.990254, 0.993193, 0.995978, 0.997215, 0.997834, 0.998608])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01]))])
2017-10-11 19:46:49 [20171011-194625-e1fc] [DEBUG] Training 100.0% complete.
2017-10-11 19:46:49 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.812809, 0.977723, 0.987314, 0.990254, 0.993193, 0.995978, 0.997215, 0.997834, 0.998608, 0.998917])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01]))])
INFO:root:Epoch[9] Batch [200] Speed: 33846.53 samples/sec accuracy=0.998125
[9] Batch [200] Speed: 33846.53 samples/sec accuracy=0.998125
INFO:root:Epoch[9] Batch [300] Speed: 35058.71 samples/sec accuracy=0.999062
[9] Batch [300] Speed: 35058.71 samples/sec accuracy=0.999062
INFO:root:Epoch[9] Batch [400] Speed: 34254.46 samples/sec accuracy=0.999375
[9] Batch [400] Speed: 34254.46 samples/sec accuracy=0.999375
INFO:root:Epoch[9] Batch [500] Speed: 30702.37 samples/sec accuracy=0.998750
[9] Batch [500] Speed: 30702.37 samples/sec accuracy=0.998750
INFO:root:Epoch[9] Batch [600] Speed: 31699.16 samples/sec accuracy=0.999687
[9] Batch [600] Speed: 31699.16 samples/sec accuracy=0.999687
INFO:root:Epoch[9] Batch [700] Speed: 31676.42 samples/sec accuracy=0.999531
[9] Batch [700] Speed: 31676.42 samples/sec accuracy=0.999531
INFO:root:Epoch[9] Batch [800] Speed: 34075.36 samples/sec accuracy=0.999062
[9] Batch [800] Speed: 34075.36 samples/sec accuracy=0.999062
INFO:root:Epoch[9] Batch [900] Speed: 34102.24 samples/sec accuracy=0.999687
[9] Batch [900] Speed: 34102.24 samples/sec accuracy=0.999687
INFO:root:Update[9371]: Change learning rate to 1.00000e-03
INFO:root:Epoch[9] Train-accuracy=0.999155
[9] Train-accuracy=0.999155
INFO:root:Epoch[9] Time cost=1.803
[9] Time cost=1.803
INFO:root:Epoch[9] Validation-accuracy=0.991143
[9] Validation-accuracy=0.991143
send progress update signl~~~ 10
2017-10-11 19:46:51 [20171011-194625-e1fc] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0])), ('accuracy', NetworkOutput(kind='Accuracy', data=[0.0, 0.98129, 0.985072, 0.987361, 0.988057, 0.988654, 0.98965, 0.990147, 0.989948, 0.990346]))])
2017-10-11 19:46:51 [20171011-194625-e1fc] [INFO ] Train Mxnet Model task completed.
<><><><><><><><><><>
1.0
<><><><><><><><><><>
2017-10-11 19:46:52 [20171011-194625-e1fc] [INFO ] Job complete.
2017-10-11 19:46:55 [20171011-194625-e1fc] [INFO ] Job deleted.
<><><><###############
1
------------------
<><><><><>!!!!!<><><><><>
['/usr/bin/python2', '/home/mayang/mxnet-0.11.0/example/image-classification/train_cifar10.py', '--gpu=0', '--lr=0.01', u'--network=inception_small', '--num-epochs=10', '--batch-size=120']
---------------
2017-10-11 19:48:04 [20171011-194803-6cac] [INFO ] Train Mxnet Model task started.
2017-10-11 19:48:04 [20171011-194803-6cac] [INFO ] Task subprocess args: "/usr/bin/python2 /home/mayang/mxnet-0.11.0/example/image-classification/train_cifar10.py --gpu=0 --lr=0.01 --network=inception_small --num-epochs=10 --batch-size=120"
2017-10-11 19:48:04 [20171011-194803-6cac] [INFO ] args = /usr/bin/python2/home/mayang/mxnet-0.11.0/example/image-classification/train_cifar10.py--gpu=0--lr=0.01--network=inception_small--num-epochs=10--batch-size=120
Traceback (most recent call last):
File "/home/mayang/mxnet-0.11.0/example/image-classification/train_cifar10.py", line 66, in <module>
net = import_module('symbols.'+args.network)
File "/usr/lib/python2.7/importlib/__init__.py", line 37, in import_module
__import__(name)
ImportError: No module named inception_small
2017-10-11 19:48:05 [20171011-194803-6cac] [ERROR] Train Mxnet Model task failed with error code 1
Traceback (most recent call last):
File "/home/mayang/mxnet-0.11.0/example/image-classification/train_cifar10.py", line 66, in <module>
net = import_module('symbols.'+args.network)
File "/usr/lib/python2.7/importlib/__init__.py", line 37, in import_module
__import__(name)
ImportError: No module named inception_small
<><><><###############
1
------------------
<><><><><>!!!!!<><><><><>
['/usr/bin/python2', '/home/mayang/mxnet-0.11.0/example/image-classification/train_cifar10.py', '--gpu=0', '--lr=0.01', u'--network=inception_small', '--num-epochs=10', '--batch-size=120']
---------------
2017-10-11 19:52:45 [20171011-195244-aa20] [INFO ] Train Mxnet Model task started.
2017-10-11 19:52:45 [20171011-195244-aa20] [INFO ] Task subprocess args: "/usr/bin/python2 /home/mayang/mxnet-0.11.0/example/image-classification/train_cifar10.py --gpu=0 --lr=0.01 --network=inception_small --num-epochs=10 --batch-size=120"
2017-10-11 19:52:45 [20171011-195244-aa20] [INFO ] args = /usr/bin/python2/home/mayang/mxnet-0.11.0/example/image-classification/train_cifar10.py--gpu=0--lr=0.01--network=inception_small--num-epochs=10--batch-size=120
Traceback (most recent call last):
File "/home/mayang/mxnet-0.11.0/example/image-classification/train_cifar10.py", line 66, in <module>
net = import_module('symbols.'+args.network)
File "/usr/lib/python2.7/importlib/__init__.py", line 37, in import_module
__import__(name)
File "/home/mayang/mxnet-0.11.0/example/image-classification/symbols/inception_small.py", line 5, in <module>
import find_mxnet
ImportError: No module named find_mxnet
2017-10-11 19:52:46 [20171011-195244-aa20] [ERROR] Train Mxnet Model task failed with error code 1
Traceback (most recent call last):
File "/home/mayang/mxnet-0.11.0/example/image-classification/train_cifar10.py", line 66, in <module>
net = import_module('symbols.'+args.network)
File "/usr/lib/python2.7/importlib/__init__.py", line 37, in import_module
__import__(name)
File "/home/mayang/mxnet-0.11.0/example/image-classification/symbols/inception_small.py", line 5, in <module>
import find_mxnet
ImportError: No module named find_mxnet
<><><><###############
1
------------------
<><><><><>!!!!!<><><><><>
['/usr/bin/python2', '/home/mayang/mxnet-0.11.0/example/image-classification/train_cifar10.py', '--gpu=0', '--lr=0.01', u'--network=inception_small', '--num-epochs=10', '--batch-size=120']
---------------
2017-10-11 19:53:27 [20171011-195325-21b2] [INFO ] Train Mxnet Model task started.
2017-10-11 19:53:27 [20171011-195325-21b2] [INFO ] Task subprocess args: "/usr/bin/python2 /home/mayang/mxnet-0.11.0/example/image-classification/train_cifar10.py --gpu=0 --lr=0.01 --network=inception_small --num-epochs=10 --batch-size=120"
2017-10-11 19:53:27 [20171011-195325-21b2] [INFO ] args = /usr/bin/python2/home/mayang/mxnet-0.11.0/example/image-classification/train_cifar10.py--gpu=0--lr=0.01--network=inception_small--num-epochs=10--batch-size=120
Traceback (most recent call last):
File "/home/mayang/mxnet-0.11.0/example/image-classification/train_cifar10.py", line 67, in <module>
sym = net.get_symbol(**vars(args))
TypeError: get_symbol() got an unexpected keyword argument 'max_random_shear_ratio'
2017-10-11 19:53:28 [20171011-195325-21b2] [ERROR] Train Mxnet Model task failed with error code 1
Traceback (most recent call last):
File "/home/mayang/mxnet-0.11.0/example/image-classification/train_cifar10.py", line 67, in <module>
sym = net.get_symbol(**vars(args))
TypeError: get_symbol() got an unexpected keyword argument 'max_random_shear_ratio'
<><><><###############
1
------------------
<><><><><>!!!!!<><><><><>
['/usr/bin/python2', '/home/mayang/mxnet-0.11.0/example/image-classification/train_cifar10.py', '--gpu=0', '--lr=0.01', u'--network=inception_small', '--num-epochs=10', '--batch-size=120']
---------------
2017-10-11 19:54:08 [20171011-195407-2be4] [INFO ] Train Mxnet Model task started.
2017-10-11 19:54:08 [20171011-195407-2be4] [INFO ] Task subprocess args: "/usr/bin/python2 /home/mayang/mxnet-0.11.0/example/image-classification/train_cifar10.py --gpu=0 --lr=0.01 --network=inception_small --num-epochs=10 --batch-size=120"
2017-10-11 19:54:08 [20171011-195407-2be4] [INFO ] args = /usr/bin/python2/home/mayang/mxnet-0.11.0/example/image-classification/train_cifar10.py--gpu=0--lr=0.01--network=inception_small--num-epochs=10--batch-size=120
INFO:root:start with arguments Namespace(batch_size=120, benchmark=0, data_nthreads=4, data_train='/home/mayang/mxnet-0.11.0/example/image-classification/data/cifar10_train.rec', data_val='/home/mayang/mxnet-0.11.0/example/image-classification/data/cifar10_val.rec', disp_batches=20, dtype='float32', gpus='0', image_shape='3,28,28', kv_store='device', load_epoch=None, lr=0.01, lr_factor=0.1, lr_step_epochs='200,250', max_random_aspect_ratio=0, max_random_h=36, max_random_l=50, max_random_rotate_angle=0, max_random_s=50, max_random_scale=1, max_random_shear_ratio=0, min_random_scale=1, model_prefix=None, mom=0.9, monitor=0, network='inception_small', num_classes=10, num_epochs=10, num_examples=50000, num_layers=110, optimizer='sgd', pad_size=4, random_crop=1, random_mirror=1, rgb_mean='123.68,116.779,103.939', test_io=0, top_k=0, wd=0.0001)
[19:54:09] src/io/iter_image_recordio_2.cc:153: ImageRecordIOParser2: /home/mayang/mxnet-0.11.0/example/image-classification/data/cifar10_train.rec, use 4 threads for decoding..
[19:54:10] src/io/iter_image_recordio_2.cc:153: ImageRecordIOParser2: /home/mayang/mxnet-0.11.0/example/image-classification/data/cifar10_val.rec, use 4 threads for decoding..
[19:54:11] src/operator/././cudnn_algoreg-inl.h:112: Running performance tests to find the best convolution algorithm, this can take a while... (setting env variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable)
INFO:root:Epoch[0] Batch [20] Speed: 2892.06 samples/sec accuracy=0.181746
2017-10-11 19:54:14 [20171011-195407-2be4] [INFO ] OrderedDict()
2017-10-11 19:54:14 [20171011-195407-2be4] [DEBUG] Training 0.0% complete.
2017-10-11 19:54:14 [20171011-195407-2be4] [INFO ] OrderedDict()
2017-10-11 19:54:14 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0]))])
[0] Batch [20] Speed: 2892.06 samples/sec accuracy=0.181746
INFO:root:Epoch[0] Batch [40] Speed: 3036.99 samples/sec accuracy=0.282917
[0] Batch [40] Speed: 3036.99 samples/sec accuracy=0.282917
INFO:root:Epoch[0] Batch [60] Speed: 3043.90 samples/sec accuracy=0.305833
[0] Batch [60] Speed: 3043.90 samples/sec accuracy=0.305833
INFO:root:Epoch[0] Batch [80] Speed: 3065.68 samples/sec accuracy=0.345000
[0] Batch [80] Speed: 3065.68 samples/sec accuracy=0.345000
INFO:root:Epoch[0] Batch [100] Speed: 3087.94 samples/sec accuracy=0.369583
[0] Batch [100] Speed: 3087.94 samples/sec accuracy=0.369583
send progress update signl~~~ 1
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0.1
<><><><><><><><><><>
2017-10-11 19:54:17 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01]))])
2017-10-11 19:54:17 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.369583])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01]))])
INFO:root:Epoch[0] Batch [120] Speed: 3066.53 samples/sec accuracy=0.381250
[0] Batch [120] Speed: 3066.53 samples/sec accuracy=0.381250
INFO:root:Epoch[0] Batch [140] Speed: 3048.79 samples/sec accuracy=0.383750
[0] Batch [140] Speed: 3048.79 samples/sec accuracy=0.383750
INFO:root:Epoch[0] Batch [160] Speed: 3102.68 samples/sec accuracy=0.408750
[0] Batch [160] Speed: 3102.68 samples/sec accuracy=0.408750
INFO:root:Epoch[0] Batch [180] Speed: 3098.76 samples/sec accuracy=0.426667
[0] Batch [180] Speed: 3098.76 samples/sec accuracy=0.426667
INFO:root:Epoch[0] Batch [200] Speed: 3083.47 samples/sec accuracy=0.416667
[0] Batch [200] Speed: 3083.47 samples/sec accuracy=0.416667
INFO:root:Epoch[0] Batch [220] Speed: 3091.49 samples/sec accuracy=0.441667
[0] Batch [220] Speed: 3091.49 samples/sec accuracy=0.441667
INFO:root:Epoch[0] Batch [240] Speed: 3091.19 samples/sec accuracy=0.449167
[0] Batch [240] Speed: 3091.19 samples/sec accuracy=0.449167
INFO:root:Epoch[0] Batch [260] Speed: 3090.57 samples/sec accuracy=0.448333
[0] Batch [260] Speed: 3090.57 samples/sec accuracy=0.448333
INFO:root:Epoch[0] Batch [280] Speed: 3076.20 samples/sec accuracy=0.484583
[0] Batch [280] Speed: 3076.20 samples/sec accuracy=0.484583
INFO:root:Epoch[0] Batch [300] Speed: 3057.10 samples/sec accuracy=0.489167
[0] Batch [300] Speed: 3057.10 samples/sec accuracy=0.489167
INFO:root:Epoch[0] Batch [320] Speed: 3091.86 samples/sec accuracy=0.509583
[0] Batch [320] Speed: 3091.86 samples/sec accuracy=0.509583
INFO:root:Epoch[0] Batch [340] Speed: 3104.59 samples/sec accuracy=0.502083
[0] Batch [340] Speed: 3104.59 samples/sec accuracy=0.502083
INFO:root:Epoch[0] Batch [360] Speed: 3091.29 samples/sec accuracy=0.515417
[0] Batch [360] Speed: 3091.29 samples/sec accuracy=0.515417
INFO:root:Epoch[0] Batch [380] Speed: 3082.59 samples/sec accuracy=0.505000
[0] Batch [380] Speed: 3082.59 samples/sec accuracy=0.505000
INFO:root:Epoch[0] Batch [400] Speed: 3081.94 samples/sec accuracy=0.532917
[0] Batch [400] Speed: 3081.94 samples/sec accuracy=0.532917
INFO:root:Epoch[0] Train-accuracy=0.511458
[0] Train-accuracy=0.511458
INFO:root:Epoch[0] Time cost=16.503
[0] Time cost=16.503
INFO:root:Epoch[0] Validation-accuracy=0.566964
[0] Validation-accuracy=0.566964
send progress update signl~~~ 1
2017-10-11 19:54:30 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0])), ('accuracy', NetworkOutput(kind='Accuracy', data=[0.0]))])
INFO:root:Epoch[1] Batch [20] Speed: 3047.71 samples/sec accuracy=0.542460
[1] Batch [20] Speed: 3047.71 samples/sec accuracy=0.542460
INFO:root:Epoch[1] Batch [40] Speed: 3048.22 samples/sec accuracy=0.516250
[1] Batch [40] Speed: 3048.22 samples/sec accuracy=0.516250
INFO:root:Epoch[1] Batch [60] Speed: 3086.11 samples/sec accuracy=0.536667
[1] Batch [60] Speed: 3086.11 samples/sec accuracy=0.536667
INFO:root:Epoch[1] Batch [80] Speed: 3095.32 samples/sec accuracy=0.559583
[1] Batch [80] Speed: 3095.32 samples/sec accuracy=0.559583
INFO:root:Epoch[1] Batch [100] Speed: 3099.35 samples/sec accuracy=0.560417
[1] Batch [100] Speed: 3099.35 samples/sec accuracy=0.560417
send progress update signl~~~ 2
<><><><><><><><><><>
0.2
<><><><><><><><><><>
2017-10-11 19:54:34 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.369583])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01]))])
2017-10-11 19:54:34 [20171011-195407-2be4] [DEBUG] Training 20.0% complete.
2017-10-11 19:54:34 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.369583, 0.560417])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01]))])
INFO:root:Epoch[1] Batch [120] Speed: 3097.52 samples/sec accuracy=0.550000
[1] Batch [120] Speed: 3097.52 samples/sec accuracy=0.550000
INFO:root:Epoch[1] Batch [140] Speed: 3088.50 samples/sec accuracy=0.562083
[1] Batch [140] Speed: 3088.50 samples/sec accuracy=0.562083
INFO:root:Epoch[1] Batch [160] Speed: 3095.05 samples/sec accuracy=0.570000
[1] Batch [160] Speed: 3095.05 samples/sec accuracy=0.570000
INFO:root:Epoch[1] Batch [180] Speed: 3084.58 samples/sec accuracy=0.572083
[1] Batch [180] Speed: 3084.58 samples/sec accuracy=0.572083
INFO:root:Epoch[1] Batch [200] Speed: 3094.30 samples/sec accuracy=0.586667
[1] Batch [200] Speed: 3094.30 samples/sec accuracy=0.586667
INFO:root:Epoch[1] Batch [220] Speed: 3072.31 samples/sec accuracy=0.577500
[1] Batch [220] Speed: 3072.31 samples/sec accuracy=0.577500
INFO:root:Epoch[1] Batch [240] Speed: 3054.29 samples/sec accuracy=0.578333
[1] Batch [240] Speed: 3054.29 samples/sec accuracy=0.578333
INFO:root:Epoch[1] Batch [260] Speed: 3078.90 samples/sec accuracy=0.583750
[1] Batch [260] Speed: 3078.90 samples/sec accuracy=0.583750
INFO:root:Epoch[1] Batch [280] Speed: 3081.36 samples/sec accuracy=0.585833
[1] Batch [280] Speed: 3081.36 samples/sec accuracy=0.585833
INFO:root:Epoch[1] Batch [300] Speed: 3079.85 samples/sec accuracy=0.596250
[1] Batch [300] Speed: 3079.85 samples/sec accuracy=0.596250
INFO:root:Epoch[1] Batch [320] Speed: 3096.85 samples/sec accuracy=0.605417
[1] Batch [320] Speed: 3096.85 samples/sec accuracy=0.605417
INFO:root:Epoch[1] Batch [340] Speed: 3095.06 samples/sec accuracy=0.605000
[1] Batch [340] Speed: 3095.06 samples/sec accuracy=0.605000
INFO:root:Epoch[1] Batch [360] Speed: 3099.99 samples/sec accuracy=0.607917
[1] Batch [360] Speed: 3099.99 samples/sec accuracy=0.607917
INFO:root:Epoch[1] Batch [380] Speed: 3098.95 samples/sec accuracy=0.611250
[1] Batch [380] Speed: 3098.95 samples/sec accuracy=0.611250
INFO:root:Epoch[1] Batch [400] Speed: 3102.61 samples/sec accuracy=0.617500
[1] Batch [400] Speed: 3102.61 samples/sec accuracy=0.617500
INFO:root:Epoch[1] Train-accuracy=0.622917
[1] Train-accuracy=0.622917
INFO:root:Epoch[1] Time cost=16.200
[1] Time cost=16.200
INFO:root:Epoch[1] Validation-accuracy=0.652811
[1] Validation-accuracy=0.652811
send progress update signl~~~ 2
2017-10-11 19:54:47 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0])), ('accuracy', NetworkOutput(kind='Accuracy', data=[0.0, 0.566964]))])
INFO:root:Epoch[2] Batch [20] Speed: 3092.36 samples/sec accuracy=0.632143
[2] Batch [20] Speed: 3092.36 samples/sec accuracy=0.632143
INFO:root:Epoch[2] Batch [40] Speed: 3097.97 samples/sec accuracy=0.612917
[2] Batch [40] Speed: 3097.97 samples/sec accuracy=0.612917
INFO:root:Epoch[2] Batch [60] Speed: 3099.27 samples/sec accuracy=0.627083
[2] Batch [60] Speed: 3099.27 samples/sec accuracy=0.627083
INFO:root:Epoch[2] Batch [80] Speed: 3106.73 samples/sec accuracy=0.621250
[2] Batch [80] Speed: 3106.73 samples/sec accuracy=0.621250
INFO:root:Epoch[2] Batch [100] Speed: 3083.86 samples/sec accuracy=0.622917
[2] Batch [100] Speed: 3083.86 samples/sec accuracy=0.622917
send progress update signl~~~ 3
<><><><><><><><><><>
0.3
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2017-10-11 19:54:51 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.369583, 0.560417])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01]))])
2017-10-11 19:54:51 [20171011-195407-2be4] [DEBUG] Training 30.0% complete.
2017-10-11 19:54:51 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.369583, 0.560417, 0.622917])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01]))])
INFO:root:Epoch[2] Batch [120] Speed: 3061.03 samples/sec accuracy=0.628333
[2] Batch [120] Speed: 3061.03 samples/sec accuracy=0.628333
INFO:root:Epoch[2] Batch [140] Speed: 3070.42 samples/sec accuracy=0.643750
[2] Batch [140] Speed: 3070.42 samples/sec accuracy=0.643750
INFO:root:Epoch[2] Batch [160] Speed: 3108.67 samples/sec accuracy=0.647083
[2] Batch [160] Speed: 3108.67 samples/sec accuracy=0.647083
INFO:root:Epoch[2] Batch [180] Speed: 3094.82 samples/sec accuracy=0.637917
[2] Batch [180] Speed: 3094.82 samples/sec accuracy=0.637917
INFO:root:Epoch[2] Batch [200] Speed: 3087.74 samples/sec accuracy=0.642500
[2] Batch [200] Speed: 3087.74 samples/sec accuracy=0.642500
2017-10-11 19:54:56 [20171011-195325-21b2] [INFO ] Job deleted.
2017-10-11 19:54:56 [20171011-195244-aa20] [INFO ] Job deleted.
2017-10-11 19:54:56 [20171011-194803-6cac] [INFO ] Job deleted.
INFO:root:Epoch[2] Batch [220] Speed: 3055.74 samples/sec accuracy=0.648333
[2] Batch [220] Speed: 3055.74 samples/sec accuracy=0.648333
INFO:root:Epoch[2] Batch [240] Speed: 3064.97 samples/sec accuracy=0.658333
[2] Batch [240] Speed: 3064.97 samples/sec accuracy=0.658333
INFO:root:Epoch[2] Batch [260] Speed: 3096.48 samples/sec accuracy=0.636250
[2] Batch [260] Speed: 3096.48 samples/sec accuracy=0.636250
INFO:root:Epoch[2] Batch [280] Speed: 3090.10 samples/sec accuracy=0.632500
[2] Batch [280] Speed: 3090.10 samples/sec accuracy=0.632500
INFO:root:Epoch[2] Batch [300] Speed: 3112.37 samples/sec accuracy=0.639583
[2] Batch [300] Speed: 3112.37 samples/sec accuracy=0.639583
INFO:root:Epoch[2] Batch [320] Speed: 3104.46 samples/sec accuracy=0.651250
[2] Batch [320] Speed: 3104.46 samples/sec accuracy=0.651250
INFO:root:Epoch[2] Batch [340] Speed: 3113.27 samples/sec accuracy=0.660000
[2] Batch [340] Speed: 3113.27 samples/sec accuracy=0.660000
INFO:root:Epoch[2] Batch [360] Speed: 3091.31 samples/sec accuracy=0.648750
[2] Batch [360] Speed: 3091.31 samples/sec accuracy=0.648750
INFO:root:Epoch[2] Batch [380] Speed: 3096.80 samples/sec accuracy=0.678333
[2] Batch [380] Speed: 3096.80 samples/sec accuracy=0.678333
INFO:root:Epoch[2] Batch [400] Speed: 3104.65 samples/sec accuracy=0.660417
[2] Batch [400] Speed: 3104.65 samples/sec accuracy=0.660417
INFO:root:Epoch[2] Train-accuracy=0.662778
[2] Train-accuracy=0.662778
INFO:root:Epoch[2] Time cost=16.124
[2] Time cost=16.124
INFO:root:Epoch[2] Validation-accuracy=0.689859
[2] Validation-accuracy=0.689859
send progress update signl~~~ 3
2017-10-11 19:55:04 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0])), ('accuracy', NetworkOutput(kind='Accuracy', data=[0.0, 0.566964, 0.652811]))])
INFO:root:Epoch[3] Batch [20] Speed: 3107.73 samples/sec accuracy=0.678968
[3] Batch [20] Speed: 3107.73 samples/sec accuracy=0.678968
INFO:root:Epoch[3] Batch [40] Speed: 3072.37 samples/sec accuracy=0.677917
[3] Batch [40] Speed: 3072.37 samples/sec accuracy=0.677917
INFO:root:Epoch[3] Batch [60] Speed: 3069.43 samples/sec accuracy=0.664583
[3] Batch [60] Speed: 3069.43 samples/sec accuracy=0.664583
INFO:root:Epoch[3] Batch [80] Speed: 3067.18 samples/sec accuracy=0.678333
[3] Batch [80] Speed: 3067.18 samples/sec accuracy=0.678333
INFO:root:Epoch[3] Batch [100] Speed: 3085.27 samples/sec accuracy=0.678333
[3] Batch [100] Speed: 3085.27 samples/sec accuracy=0.678333
send progress update signl~~~ 4
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0.4
<><><><><><><><><><>
2017-10-11 19:55:09 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.369583, 0.560417, 0.622917])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01]))])
2017-10-11 19:55:09 [20171011-195407-2be4] [DEBUG] Training 40.0% complete.
2017-10-11 19:55:09 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.369583, 0.560417, 0.622917, 0.678333])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01]))])
INFO:root:Epoch[3] Batch [120] Speed: 3075.41 samples/sec accuracy=0.677500
[3] Batch [120] Speed: 3075.41 samples/sec accuracy=0.677500
INFO:root:Epoch[3] Batch [140] Speed: 3094.17 samples/sec accuracy=0.692500
[3] Batch [140] Speed: 3094.17 samples/sec accuracy=0.692500
INFO:root:Epoch[3] Batch [160] Speed: 3076.05 samples/sec accuracy=0.669167
[3] Batch [160] Speed: 3076.05 samples/sec accuracy=0.669167
INFO:root:Epoch[3] Batch [180] Speed: 3059.37 samples/sec accuracy=0.685000
[3] Batch [180] Speed: 3059.37 samples/sec accuracy=0.685000
INFO:root:Epoch[3] Batch [200] Speed: 3066.27 samples/sec accuracy=0.682917
[3] Batch [200] Speed: 3066.27 samples/sec accuracy=0.682917
INFO:root:Epoch[3] Batch [220] Speed: 3009.29 samples/sec accuracy=0.692917
[3] Batch [220] Speed: 3009.29 samples/sec accuracy=0.692917
INFO:root:Epoch[3] Batch [240] Speed: 3069.46 samples/sec accuracy=0.679167
[3] Batch [240] Speed: 3069.46 samples/sec accuracy=0.679167
INFO:root:Epoch[3] Batch [260] Speed: 3071.00 samples/sec accuracy=0.690833
[3] Batch [260] Speed: 3071.00 samples/sec accuracy=0.690833
INFO:root:Epoch[3] Batch [280] Speed: 3078.81 samples/sec accuracy=0.694583
[3] Batch [280] Speed: 3078.81 samples/sec accuracy=0.694583
INFO:root:Epoch[3] Batch [300] Speed: 3065.29 samples/sec accuracy=0.680833
[3] Batch [300] Speed: 3065.29 samples/sec accuracy=0.680833
INFO:root:Epoch[3] Batch [320] Speed: 3074.36 samples/sec accuracy=0.693750
[3] Batch [320] Speed: 3074.36 samples/sec accuracy=0.693750
INFO:root:Epoch[3] Batch [340] Speed: 3087.99 samples/sec accuracy=0.714583
[3] Batch [340] Speed: 3087.99 samples/sec accuracy=0.714583
INFO:root:Epoch[3] Batch [360] Speed: 3094.50 samples/sec accuracy=0.695417
[3] Batch [360] Speed: 3094.50 samples/sec accuracy=0.695417
INFO:root:Epoch[3] Batch [380] Speed: 3085.73 samples/sec accuracy=0.697500
[3] Batch [380] Speed: 3085.73 samples/sec accuracy=0.697500
INFO:root:Epoch[3] Batch [400] Speed: 3089.13 samples/sec accuracy=0.685000
[3] Batch [400] Speed: 3089.13 samples/sec accuracy=0.685000
INFO:root:Epoch[3] Train-accuracy=0.697396
[3] Train-accuracy=0.697396
INFO:root:Epoch[3] Time cost=16.405
[3] Time cost=16.405
INFO:root:Epoch[3] Validation-accuracy=0.740079
[3] Validation-accuracy=0.740079
send progress update signl~~~ 4
2017-10-11 19:55:22 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0])), ('accuracy', NetworkOutput(kind='Accuracy', data=[0.0, 0.566964, 0.652811, 0.689859]))])
INFO:root:Epoch[4] Batch [20] Speed: 3095.58 samples/sec accuracy=0.686905
[4] Batch [20] Speed: 3095.58 samples/sec accuracy=0.686905
INFO:root:Epoch[4] Batch [40] Speed: 3110.42 samples/sec accuracy=0.726667
[4] Batch [40] Speed: 3110.42 samples/sec accuracy=0.726667
INFO:root:Epoch[4] Batch [60] Speed: 3104.44 samples/sec accuracy=0.702917
[4] Batch [60] Speed: 3104.44 samples/sec accuracy=0.702917
INFO:root:Epoch[4] Batch [80] Speed: 3101.43 samples/sec accuracy=0.710833
[4] Batch [80] Speed: 3101.43 samples/sec accuracy=0.710833
INFO:root:Epoch[4] Batch [100] Speed: 3117.41 samples/sec accuracy=0.713750
[4] Batch [100] Speed: 3117.41 samples/sec accuracy=0.713750
send progress update signl~~~ 5
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0.5
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2017-10-11 19:55:26 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.369583, 0.560417, 0.622917, 0.678333])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01]))])
2017-10-11 19:55:26 [20171011-195407-2be4] [DEBUG] Training 50.0% complete.
2017-10-11 19:55:26 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.369583, 0.560417, 0.622917, 0.678333, 0.71375])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01]))])
INFO:root:Epoch[4] Batch [120] Speed: 3081.81 samples/sec accuracy=0.709167
[4] Batch [120] Speed: 3081.81 samples/sec accuracy=0.709167
INFO:root:Epoch[4] Batch [140] Speed: 3054.55 samples/sec accuracy=0.717083
[4] Batch [140] Speed: 3054.55 samples/sec accuracy=0.717083
INFO:root:Epoch[4] Batch [160] Speed: 3073.83 samples/sec accuracy=0.713333
[4] Batch [160] Speed: 3073.83 samples/sec accuracy=0.713333
INFO:root:Epoch[4] Batch [180] Speed: 3059.84 samples/sec accuracy=0.717500
[4] Batch [180] Speed: 3059.84 samples/sec accuracy=0.717500
INFO:root:Epoch[4] Batch [200] Speed: 3078.71 samples/sec accuracy=0.710000
[4] Batch [200] Speed: 3078.71 samples/sec accuracy=0.710000
INFO:root:Epoch[4] Batch [220] Speed: 3115.03 samples/sec accuracy=0.722917
[4] Batch [220] Speed: 3115.03 samples/sec accuracy=0.722917
INFO:root:Epoch[4] Batch [240] Speed: 3105.83 samples/sec accuracy=0.730000
[4] Batch [240] Speed: 3105.83 samples/sec accuracy=0.730000
INFO:root:Epoch[4] Batch [260] Speed: 3115.67 samples/sec accuracy=0.732500
[4] Batch [260] Speed: 3115.67 samples/sec accuracy=0.732500
INFO:root:Epoch[4] Batch [280] Speed: 3073.30 samples/sec accuracy=0.707917
[4] Batch [280] Speed: 3073.30 samples/sec accuracy=0.707917
INFO:root:Epoch[4] Batch [300] Speed: 3105.78 samples/sec accuracy=0.716250
[4] Batch [300] Speed: 3105.78 samples/sec accuracy=0.716250
INFO:root:Epoch[4] Batch [320] Speed: 3068.15 samples/sec accuracy=0.740417
[4] Batch [320] Speed: 3068.15 samples/sec accuracy=0.740417
INFO:root:Epoch[4] Batch [340] Speed: 3071.75 samples/sec accuracy=0.719583
[4] Batch [340] Speed: 3071.75 samples/sec accuracy=0.719583
INFO:root:Epoch[4] Batch [360] Speed: 3063.90 samples/sec accuracy=0.733750
[4] Batch [360] Speed: 3063.90 samples/sec accuracy=0.733750
INFO:root:Epoch[4] Batch [380] Speed: 3094.21 samples/sec accuracy=0.723333
[4] Batch [380] Speed: 3094.21 samples/sec accuracy=0.723333
INFO:root:Epoch[4] Batch [400] Speed: 3077.16 samples/sec accuracy=0.732083
[4] Batch [400] Speed: 3077.16 samples/sec accuracy=0.732083
INFO:root:Epoch[4] Train-accuracy=0.727604
[4] Train-accuracy=0.727604
INFO:root:Epoch[4] Time cost=16.185
[4] Time cost=16.185
INFO:root:Epoch[4] Validation-accuracy=0.746486
[4] Validation-accuracy=0.746486
send progress update signl~~~ 5
2017-10-11 19:55:39 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0])), ('accuracy', NetworkOutput(kind='Accuracy', data=[0.0, 0.566964, 0.652811, 0.689859, 0.740079]))])
INFO:root:Epoch[5] Batch [20] Speed: 3088.24 samples/sec accuracy=0.739683
[5] Batch [20] Speed: 3088.24 samples/sec accuracy=0.739683
INFO:root:Epoch[5] Batch [40] Speed: 3079.75 samples/sec accuracy=0.737500
[5] Batch [40] Speed: 3079.75 samples/sec accuracy=0.737500
INFO:root:Epoch[5] Batch [60] Speed: 3101.02 samples/sec accuracy=0.723750
[5] Batch [60] Speed: 3101.02 samples/sec accuracy=0.723750
INFO:root:Epoch[5] Batch [80] Speed: 3093.34 samples/sec accuracy=0.731250
[5] Batch [80] Speed: 3093.34 samples/sec accuracy=0.731250
INFO:root:Epoch[5] Batch [100] Speed: 3095.65 samples/sec accuracy=0.736250
[5] Batch [100] Speed: 3095.65 samples/sec accuracy=0.736250
send progress update signl~~~ 6
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0.6
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2017-10-11 19:55:43 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.369583, 0.560417, 0.622917, 0.678333, 0.71375])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01]))])
2017-10-11 19:55:43 [20171011-195407-2be4] [DEBUG] Training 60.0% complete.
2017-10-11 19:55:43 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.369583, 0.560417, 0.622917, 0.678333, 0.71375, 0.73625])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01]))])
INFO:root:Epoch[5] Batch [120] Speed: 3092.32 samples/sec accuracy=0.739583
[5] Batch [120] Speed: 3092.32 samples/sec accuracy=0.739583
INFO:root:Epoch[5] Batch [140] Speed: 3103.56 samples/sec accuracy=0.745417
[5] Batch [140] Speed: 3103.56 samples/sec accuracy=0.745417
INFO:root:Epoch[5] Batch [160] Speed: 3104.56 samples/sec accuracy=0.735833
[5] Batch [160] Speed: 3104.56 samples/sec accuracy=0.735833
INFO:root:Epoch[5] Batch [180] Speed: 3112.79 samples/sec accuracy=0.742500
[5] Batch [180] Speed: 3112.79 samples/sec accuracy=0.742500
INFO:root:Epoch[5] Batch [200] Speed: 3108.63 samples/sec accuracy=0.735417
[5] Batch [200] Speed: 3108.63 samples/sec accuracy=0.735417
INFO:root:Epoch[5] Batch [220] Speed: 3094.26 samples/sec accuracy=0.740000
[5] Batch [220] Speed: 3094.26 samples/sec accuracy=0.740000
INFO:root:Epoch[5] Batch [240] Speed: 3087.83 samples/sec accuracy=0.730833
[5] Batch [240] Speed: 3087.83 samples/sec accuracy=0.730833
INFO:root:Epoch[5] Batch [260] Speed: 3096.97 samples/sec accuracy=0.733750
[5] Batch [260] Speed: 3096.97 samples/sec accuracy=0.733750
INFO:root:Epoch[5] Batch [280] Speed: 3096.00 samples/sec accuracy=0.735000
[5] Batch [280] Speed: 3096.00 samples/sec accuracy=0.735000
INFO:root:Epoch[5] Batch [300] Speed: 3070.36 samples/sec accuracy=0.728333
[5] Batch [300] Speed: 3070.36 samples/sec accuracy=0.728333
INFO:root:Epoch[5] Batch [320] Speed: 3066.93 samples/sec accuracy=0.752083
[5] Batch [320] Speed: 3066.93 samples/sec accuracy=0.752083
INFO:root:Epoch[5] Batch [340] Speed: 3097.58 samples/sec accuracy=0.738750
[5] Batch [340] Speed: 3097.58 samples/sec accuracy=0.738750
INFO:root:Epoch[5] Batch [360] Speed: 3080.70 samples/sec accuracy=0.738333
[5] Batch [360] Speed: 3080.70 samples/sec accuracy=0.738333
INFO:root:Epoch[5] Batch [380] Speed: 3089.09 samples/sec accuracy=0.758333
[5] Batch [380] Speed: 3089.09 samples/sec accuracy=0.758333
INFO:root:Epoch[5] Batch [400] Speed: 3095.26 samples/sec accuracy=0.757083
[5] Batch [400] Speed: 3095.26 samples/sec accuracy=0.757083
INFO:root:Epoch[5] Train-accuracy=0.744444
[5] Train-accuracy=0.744444
INFO:root:Epoch[5] Time cost=16.123
[5] Time cost=16.123
INFO:root:Epoch[5] Validation-accuracy=0.741064
[5] Validation-accuracy=0.741064
send progress update signl~~~ 6
2017-10-11 19:55:56 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0])), ('accuracy', NetworkOutput(kind='Accuracy', data=[0.0, 0.566964, 0.652811, 0.689859, 0.740079, 0.746486]))])
INFO:root:Epoch[6] Batch [20] Speed: 3059.25 samples/sec accuracy=0.744841
[6] Batch [20] Speed: 3059.25 samples/sec accuracy=0.744841
INFO:root:Epoch[6] Batch [40] Speed: 3103.86 samples/sec accuracy=0.759583
[6] Batch [40] Speed: 3103.86 samples/sec accuracy=0.759583
INFO:root:Epoch[6] Batch [60] Speed: 3109.88 samples/sec accuracy=0.742500
[6] Batch [60] Speed: 3109.88 samples/sec accuracy=0.742500
INFO:root:Epoch[6] Batch [80] Speed: 3081.43 samples/sec accuracy=0.735417
[6] Batch [80] Speed: 3081.43 samples/sec accuracy=0.735417
INFO:root:Epoch[6] Batch [100] Speed: 3037.71 samples/sec accuracy=0.742083
[6] Batch [100] Speed: 3037.71 samples/sec accuracy=0.742083
send progress update signl~~~ 7
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0.7
<><><><><><><><><><>
2017-10-11 19:56:00 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.369583, 0.560417, 0.622917, 0.678333, 0.71375, 0.73625])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01]))])
2017-10-11 19:56:00 [20171011-195407-2be4] [DEBUG] Training 70.0% complete.
2017-10-11 19:56:00 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.369583, 0.560417, 0.622917, 0.678333, 0.71375, 0.73625, 0.742083])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01]))])
INFO:root:Epoch[6] Batch [120] Speed: 3046.97 samples/sec accuracy=0.757500
[6] Batch [120] Speed: 3046.97 samples/sec accuracy=0.757500
INFO:root:Epoch[6] Batch [140] Speed: 3089.80 samples/sec accuracy=0.755833
[6] Batch [140] Speed: 3089.80 samples/sec accuracy=0.755833
INFO:root:Epoch[6] Batch [160] Speed: 3107.15 samples/sec accuracy=0.742500
[6] Batch [160] Speed: 3107.15 samples/sec accuracy=0.742500
INFO:root:Epoch[6] Batch [180] Speed: 3076.86 samples/sec accuracy=0.755000
[6] Batch [180] Speed: 3076.86 samples/sec accuracy=0.755000
INFO:root:Epoch[6] Batch [200] Speed: 3061.06 samples/sec accuracy=0.744583
[6] Batch [200] Speed: 3061.06 samples/sec accuracy=0.744583
INFO:root:Epoch[6] Batch [220] Speed: 3077.82 samples/sec accuracy=0.738333
[6] Batch [220] Speed: 3077.82 samples/sec accuracy=0.738333
INFO:root:Epoch[6] Batch [240] Speed: 3096.72 samples/sec accuracy=0.768333
[6] Batch [240] Speed: 3096.72 samples/sec accuracy=0.768333
INFO:root:Epoch[6] Batch [260] Speed: 3092.85 samples/sec accuracy=0.755417
[6] Batch [260] Speed: 3092.85 samples/sec accuracy=0.755417
INFO:root:Epoch[6] Batch [280] Speed: 3088.76 samples/sec accuracy=0.762917
[6] Batch [280] Speed: 3088.76 samples/sec accuracy=0.762917
INFO:root:Epoch[6] Batch [300] Speed: 3115.38 samples/sec accuracy=0.754583
[6] Batch [300] Speed: 3115.38 samples/sec accuracy=0.754583
INFO:root:Epoch[6] Batch [320] Speed: 3099.15 samples/sec accuracy=0.762083
[6] Batch [320] Speed: 3099.15 samples/sec accuracy=0.762083
INFO:root:Epoch[6] Batch [340] Speed: 3109.70 samples/sec accuracy=0.766250
[6] Batch [340] Speed: 3109.70 samples/sec accuracy=0.766250
INFO:root:Epoch[6] Batch [360] Speed: 3059.62 samples/sec accuracy=0.757083
[6] Batch [360] Speed: 3059.62 samples/sec accuracy=0.757083
INFO:root:Epoch[6] Batch [380] Speed: 3071.88 samples/sec accuracy=0.763333
[6] Batch [380] Speed: 3071.88 samples/sec accuracy=0.763333
INFO:root:Epoch[6] Batch [400] Speed: 3072.64 samples/sec accuracy=0.767500
[6] Batch [400] Speed: 3072.64 samples/sec accuracy=0.767500
INFO:root:Epoch[6] Train-accuracy=0.753646
[6] Train-accuracy=0.753646
INFO:root:Epoch[6] Time cost=16.361
[6] Time cost=16.361
INFO:root:Epoch[6] Validation-accuracy=0.774802
[6] Validation-accuracy=0.774802
send progress update signl~~~ 7
2017-10-11 19:56:14 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0])), ('accuracy', NetworkOutput(kind='Accuracy', data=[0.0, 0.566964, 0.652811, 0.689859, 0.740079, 0.746486, 0.741064]))])
INFO:root:Epoch[7] Batch [20] Speed: 3033.25 samples/sec accuracy=0.767460
[7] Batch [20] Speed: 3033.25 samples/sec accuracy=0.767460
INFO:root:Epoch[7] Batch [40] Speed: 3072.03 samples/sec accuracy=0.759583
[7] Batch [40] Speed: 3072.03 samples/sec accuracy=0.759583
INFO:root:Epoch[7] Batch [60] Speed: 3068.36 samples/sec accuracy=0.760833
[7] Batch [60] Speed: 3068.36 samples/sec accuracy=0.760833
INFO:root:Epoch[7] Batch [80] Speed: 3099.77 samples/sec accuracy=0.772500
[7] Batch [80] Speed: 3099.77 samples/sec accuracy=0.772500
INFO:root:Epoch[7] Batch [100] Speed: 3056.89 samples/sec accuracy=0.776250
[7] Batch [100] Speed: 3056.89 samples/sec accuracy=0.776250
send progress update signl~~~ 8
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0.8
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2017-10-11 19:56:18 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.369583, 0.560417, 0.622917, 0.678333, 0.71375, 0.73625, 0.742083])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01]))])
2017-10-11 19:56:18 [20171011-195407-2be4] [DEBUG] Training 80.0% complete.
2017-10-11 19:56:18 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.369583, 0.560417, 0.622917, 0.678333, 0.71375, 0.73625, 0.742083, 0.77625])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01]))])
INFO:root:Epoch[7] Batch [120] Speed: 3034.72 samples/sec accuracy=0.774167
[7] Batch [120] Speed: 3034.72 samples/sec accuracy=0.774167
INFO:root:Epoch[7] Batch [140] Speed: 3077.45 samples/sec accuracy=0.779167
[7] Batch [140] Speed: 3077.45 samples/sec accuracy=0.779167
INFO:root:Epoch[7] Batch [160] Speed: 3118.19 samples/sec accuracy=0.765417
[7] Batch [160] Speed: 3118.19 samples/sec accuracy=0.765417
INFO:root:Epoch[7] Batch [180] Speed: 3077.67 samples/sec accuracy=0.764167
[7] Batch [180] Speed: 3077.67 samples/sec accuracy=0.764167
INFO:root:Epoch[7] Batch [200] Speed: 3065.11 samples/sec accuracy=0.759167
[7] Batch [200] Speed: 3065.11 samples/sec accuracy=0.759167
INFO:root:Epoch[7] Batch [220] Speed: 3093.61 samples/sec accuracy=0.769167
[7] Batch [220] Speed: 3093.61 samples/sec accuracy=0.769167
INFO:root:Epoch[7] Batch [240] Speed: 3089.71 samples/sec accuracy=0.777083
[7] Batch [240] Speed: 3089.71 samples/sec accuracy=0.777083
INFO:root:Epoch[7] Batch [260] Speed: 3083.59 samples/sec accuracy=0.770417
[7] Batch [260] Speed: 3083.59 samples/sec accuracy=0.770417
INFO:root:Epoch[7] Batch [280] Speed: 3058.07 samples/sec accuracy=0.762500
[7] Batch [280] Speed: 3058.07 samples/sec accuracy=0.762500
INFO:root:Epoch[7] Batch [300] Speed: 3070.22 samples/sec accuracy=0.769167
[7] Batch [300] Speed: 3070.22 samples/sec accuracy=0.769167
INFO:root:Epoch[7] Batch [320] Speed: 3047.93 samples/sec accuracy=0.767917
[7] Batch [320] Speed: 3047.93 samples/sec accuracy=0.767917
INFO:root:Epoch[7] Batch [340] Speed: 3096.24 samples/sec accuracy=0.768750
[7] Batch [340] Speed: 3096.24 samples/sec accuracy=0.768750
INFO:root:Epoch[7] Batch [360] Speed: 3106.08 samples/sec accuracy=0.767917
[7] Batch [360] Speed: 3106.08 samples/sec accuracy=0.767917
INFO:root:Epoch[7] Batch [380] Speed: 3030.76 samples/sec accuracy=0.777083
[7] Batch [380] Speed: 3030.76 samples/sec accuracy=0.777083
INFO:root:Epoch[7] Batch [400] Speed: 3030.98 samples/sec accuracy=0.765000
[7] Batch [400] Speed: 3030.98 samples/sec accuracy=0.765000
INFO:root:Epoch[7] Train-accuracy=0.769271
[7] Train-accuracy=0.769271
INFO:root:Epoch[7] Time cost=16.279
[7] Time cost=16.279
INFO:root:Epoch[7] Validation-accuracy=0.779016
[7] Validation-accuracy=0.779016
send progress update signl~~~ 8
2017-10-11 19:56:31 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0])), ('accuracy', NetworkOutput(kind='Accuracy', data=[0.0, 0.566964, 0.652811, 0.689859, 0.740079, 0.746486, 0.741064, 0.774802]))])
INFO:root:Epoch[8] Batch [20] Speed: 3117.59 samples/sec accuracy=0.781746
[8] Batch [20] Speed: 3117.59 samples/sec accuracy=0.781746
INFO:root:Epoch[8] Batch [40] Speed: 3070.70 samples/sec accuracy=0.787083
[8] Batch [40] Speed: 3070.70 samples/sec accuracy=0.787083
INFO:root:Epoch[8] Batch [60] Speed: 3072.51 samples/sec accuracy=0.783750
[8] Batch [60] Speed: 3072.51 samples/sec accuracy=0.783750
INFO:root:Epoch[8] Batch [80] Speed: 3085.28 samples/sec accuracy=0.776667
[8] Batch [80] Speed: 3085.28 samples/sec accuracy=0.776667
INFO:root:Epoch[8] Batch [100] Speed: 3092.74 samples/sec accuracy=0.776250
[8] Batch [100] Speed: 3092.74 samples/sec accuracy=0.776250
send progress update signl~~~ 9
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0.9
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2017-10-11 19:56:35 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.369583, 0.560417, 0.622917, 0.678333, 0.71375, 0.73625, 0.742083, 0.77625])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01]))])
2017-10-11 19:56:35 [20171011-195407-2be4] [DEBUG] Training 90.0% complete.
2017-10-11 19:56:35 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.369583, 0.560417, 0.622917, 0.678333, 0.71375, 0.73625, 0.742083, 0.77625, 0.77625])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01]))])
INFO:root:Epoch[8] Batch [120] Speed: 3088.20 samples/sec accuracy=0.799583
[8] Batch [120] Speed: 3088.20 samples/sec accuracy=0.799583
INFO:root:Epoch[8] Batch [140] Speed: 3091.68 samples/sec accuracy=0.788333
[8] Batch [140] Speed: 3091.68 samples/sec accuracy=0.788333
INFO:root:Epoch[8] Batch [160] Speed: 3063.10 samples/sec accuracy=0.788333
[8] Batch [160] Speed: 3063.10 samples/sec accuracy=0.788333
INFO:root:Epoch[8] Batch [180] Speed: 3056.23 samples/sec accuracy=0.770000
[8] Batch [180] Speed: 3056.23 samples/sec accuracy=0.770000
INFO:root:Epoch[8] Batch [200] Speed: 3089.38 samples/sec accuracy=0.778750
[8] Batch [200] Speed: 3089.38 samples/sec accuracy=0.778750
INFO:root:Epoch[8] Batch [220] Speed: 3104.14 samples/sec accuracy=0.783333
[8] Batch [220] Speed: 3104.14 samples/sec accuracy=0.783333
INFO:root:Epoch[8] Batch [240] Speed: 3104.46 samples/sec accuracy=0.779583
[8] Batch [240] Speed: 3104.46 samples/sec accuracy=0.779583
INFO:root:Epoch[8] Batch [260] Speed: 3106.06 samples/sec accuracy=0.785833
[8] Batch [260] Speed: 3106.06 samples/sec accuracy=0.785833
INFO:root:Epoch[8] Batch [280] Speed: 3101.58 samples/sec accuracy=0.773750
[8] Batch [280] Speed: 3101.58 samples/sec accuracy=0.773750
INFO:root:Epoch[8] Batch [300] Speed: 3108.11 samples/sec accuracy=0.795833
[8] Batch [300] Speed: 3108.11 samples/sec accuracy=0.795833
INFO:root:Epoch[8] Batch [320] Speed: 3075.08 samples/sec accuracy=0.790000
[8] Batch [320] Speed: 3075.08 samples/sec accuracy=0.790000
INFO:root:Epoch[8] Batch [340] Speed: 3086.35 samples/sec accuracy=0.784167
[8] Batch [340] Speed: 3086.35 samples/sec accuracy=0.784167
INFO:root:Epoch[8] Batch [360] Speed: 3088.57 samples/sec accuracy=0.790833
[8] Batch [360] Speed: 3088.57 samples/sec accuracy=0.790833
INFO:root:Epoch[8] Batch [380] Speed: 3085.53 samples/sec accuracy=0.787500
[8] Batch [380] Speed: 3085.53 samples/sec accuracy=0.787500
INFO:root:Epoch[8] Batch [400] Speed: 3069.71 samples/sec accuracy=0.787917
[8] Batch [400] Speed: 3069.71 samples/sec accuracy=0.787917
INFO:root:Epoch[8] Train-accuracy=0.786667
[8] Train-accuracy=0.786667
INFO:root:Epoch[8] Time cost=16.152
[8] Time cost=16.152
INFO:root:Epoch[8] Validation-accuracy=0.797390
[8] Validation-accuracy=0.797390
send progress update signl~~~ 9
2017-10-11 19:56:48 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0])), ('accuracy', NetworkOutput(kind='Accuracy', data=[0.0, 0.566964, 0.652811, 0.689859, 0.740079, 0.746486, 0.741064, 0.774802, 0.779016]))])
INFO:root:Epoch[9] Batch [20] Speed: 3108.87 samples/sec accuracy=0.792063
[9] Batch [20] Speed: 3108.87 samples/sec accuracy=0.792063
INFO:root:Epoch[9] Batch [40] Speed: 3093.64 samples/sec accuracy=0.792500
[9] Batch [40] Speed: 3093.64 samples/sec accuracy=0.792500
INFO:root:Epoch[9] Batch [60] Speed: 3095.07 samples/sec accuracy=0.798750
[9] Batch [60] Speed: 3095.07 samples/sec accuracy=0.798750
INFO:root:Epoch[9] Batch [80] Speed: 3109.13 samples/sec accuracy=0.798333
[9] Batch [80] Speed: 3109.13 samples/sec accuracy=0.798333
INFO:root:Epoch[9] Batch [100] Speed: 3097.82 samples/sec accuracy=0.790000
[9] Batch [100] Speed: 3097.82 samples/sec accuracy=0.790000
send progress update signl~~~ 10
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1.0
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2017-10-11 19:56:52 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.369583, 0.560417, 0.622917, 0.678333, 0.71375, 0.73625, 0.742083, 0.77625, 0.77625])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01]))])
2017-10-11 19:56:52 [20171011-195407-2be4] [DEBUG] Training 100.0% complete.
2017-10-11 19:56:52 [20171011-195407-2be4] [INFO ] OrderedDict([('epoch', NetworkOutput(kind='Epoch', data=[0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0])), ('TrainAcc', NetworkOutput(kind='Accuracy', data=[0.0, 0.369583, 0.560417, 0.622917, 0.678333, 0.71375, 0.73625, 0.742083, 0.77625, 0.77625, 0.79])), ('learning_rate', NetworkOutput(kind='LearningRate', data=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01]))])
INFO:root:Epoch[9] Batch [120] Speed: 3101.05 samples/sec accuracy=0.785417
[9] Batch [120] Speed: 3101.05 samples/sec accuracy=0.785417
INFO:root:Epoch[9] Batch [140] Speed: 3104.50 samples/sec accuracy=0.780000
[9] Batch [140] Speed: 3104.50 samples/sec accuracy=0.780000
INFO:root:Epoch[9] Batch [160] Speed: 3102.13 samples/sec accuracy=0.802500
[9] Batch [160] Speed: 3102.13 samples/sec accuracy=0.802500
INFO:root:Epoch[9] Batch [180] Speed: 3086.40 samples/sec accuracy=0.794583
[9] Batch [180] Speed: 3086.40 samples/sec accuracy=0.794583
INFO:root:Epoch[9] Batch [200] Speed: 3067.78 samples/sec accuracy=0.778333
[9] Batch [200] Speed: 3067.78 samples/sec accuracy=0.778333
INFO:root:Epoch[9] Batch [220] Speed: 3071.40 samples/sec accuracy=0.790833
[9] Batch [220] Speed: 3071.40 samples/sec accuracy=0.790833
INFO:root:Epoch[9] Batch [240] Speed: 3068.75 samples/sec accuracy=0.803333
[9] Batch [240] Speed: 3068.75 samples/sec accuracy=0.803333
INFO:root:Epoch[9] Batch [260] Speed: 3107.54 samples/sec accuracy=0.795417
[9] Batch [260] Speed: 3107.54 samples/sec accuracy=0.795417
INFO:root:Epoch[9] Batch [280] Speed: 3082.21 samples/sec accuracy=0.798333
[9] Batch [280] Speed: 3082.21 samples/sec accuracy=0.798333
INFO:root:Epoch[9] Batch [300] Speed: 3109.64 samples/sec accuracy=0.777917
[9] Batch [300] Speed: 3109.64 samples/sec accuracy=0.777917
INFO:root:Epoch[9] Batch [320] Speed: 3116.07 samples/sec accuracy=0.807083
[9] Batch [320] Speed: 3116.07 samples/sec accuracy=0.807083
INFO:root:Epoch[9] Batch [340] Speed: 3117.20 samples/sec accuracy=0.797500
[9] Batch [340] Speed: 3117.20 samples/sec accuracy=0.797500
INFO:root:Epoch[9] Batch [360] Speed: 3090.58 samples/sec accuracy=0.793333