nohup.out

training model for yanshao, tiedemann & nivre...
~/repos/yanshao_tagger ~/repos/chinese_orca
Encoding:  utf-8
Reading data......
Reading embeddings...
Using Radical dictionary...
Traceback (most recent call last):
  File "tagger.py", line 144, in <module>
    train_gram = toolbox.get_gram_vec(path, train_file, gram2idx)
  File "/home/rob/repos/yanshao_tagger/toolbox.py", line 735, in get_gram_vec
    for line in codecs.open(real_path, 'r', encoding='utf-8'):
  File "/usr/lib/python2.7/codecs.py", line 699, in next
    return self.reader.next()
  File "/usr/lib/python2.7/codecs.py", line 630, in next
    line = self.readline()
  File "/usr/lib/python2.7/codecs.py", line 532, in readline
    if len(self.linebuffer) == 1:
KeyboardInterrupt
training model for yanshao, tiedemann & nivre...
~/repos/yanshao_tagger ~/repos/chinese_orca
WARNING:tensorflow:From /home/rob/repos/yanshao_tagger/layers.py:300: calling reduce_max (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
Encoding:  utf-8
Reading data......
Reading embeddings...
Using Radical dictionary...
Longest sentence by character is 418. 
Longest sentence by word is 242. 
Longest word is 104. 
Number of buckets:  39
Training set: 65467 instances; Dev set: 3614 instances.
Initialization....
Bucket 1, 0.568074 seconds
Bucket 2, 0.156680 seconds
Bucket 3, 0.167799 seconds
Bucket 4, 0.162262 seconds
Bucket 5, 0.156511 seconds
Bucket 6, 0.157020 seconds
Bucket 7, 0.156586 seconds
Bucket 8, 0.493624 seconds
Bucket 9, 0.157359 seconds
Bucket 10, 0.156574 seconds
Bucket 11, 0.157094 seconds
Bucket 12, 0.157078 seconds
Bucket 13, 0.158206 seconds
Bucket 14, 0.156789 seconds
Bucket 15, 0.160855 seconds
Bucket 16, 0.198380 seconds
Bucket 17, 0.199453 seconds
Bucket 18, 0.560053 seconds
Bucket 19, 0.157503 seconds
Bucket 20, 0.157713 seconds
Bucket 21, 0.157211 seconds
Bucket 22, 0.157598 seconds
Bucket 23, 0.157249 seconds
Bucket 24, 0.157532 seconds
Bucket 25, 0.157612 seconds
Bucket 26, 0.157350 seconds
Bucket 27, 0.156245 seconds
Bucket 28, 0.156788 seconds
Bucket 29, 0.157501 seconds
Bucket 30, 0.549750 seconds
Bucket 31, 0.164121 seconds
Bucket 32, 0.162001 seconds
Bucket 33, 0.162123 seconds
Bucket 34, 0.158675 seconds
Bucket 35, 0.156947 seconds
Bucket 36, 0.158199 seconds
Bucket 37, 0.157052 seconds
Bucket 38, 0.157740 seconds
Bucket 39, 0.168390 seconds
Training preparation...
Defining loss...
Traceback (most recent call last):
  File "tagger.py", line 201, in <module>
    clipping=args.clipping)
  File "/home/rob/repos/yanshao_tagger/bucket_model.py", line 280, in config
    batch_size=self.real_batches[i])
  File "/home/rob/repos/yanshao_tagger/losses.py", line 105, in loss_wrapper
    total_loss.append(loss_function(sy, sy_, stranstion, snums_tags, batch_size))
  File "/home/rob/repos/yanshao_tagger/losses.py", line 93, in crf_loss
    total_path_score, _, _ = Forward(tag_scores, transitions, nums_tags, lengths, batch_size)()
  File "/home/rob/repos/yanshao_tagger/layers.py", line 321, in __call__
    current =  tf.reshape(self.observations[t,:, :, :], [-1, 1, self.nums_tags + 1])
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/array_ops.py", line 563, in _slice_helper
    packed_begin, packed_end, packed_strides = (stack(begin), stack(end),
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/array_ops.py", line 928, in stack
    return ops.convert_to_tensor(values, name=name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 946, in convert_to_tensor
    as_ref=False)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1036, in internal_convert_to_tensor
    ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/constant_op.py", line 235, in _constant_tensor_conversion_function
    return constant(v, dtype=dtype, name=name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/constant_op.py", line 214, in constant
    value, dtype=dtype, shape=shape, verify_shape=verify_shape))
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/tensor_util.py", line 492, in make_tensor_proto
    tensor_shape=tensor_shape.as_shape(shape).as_proto())
KeyboardInterrupt
~/repos/chinese_orca
training model for yanshao, tiedemann & nivre...
~/repos/yanshao_tagger ~/repos/chinese_orca
WARNING:tensorflow:From /home/rob/repos/yanshao_tagger/layers.py:300: calling reduce_max (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
2018-03-26 15:05:31.144496: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 AVX512F FMA
Encoding:  utf-8
Reading data......
Reading embeddings...
Using Radical dictionary...
Longest sentence by character is 418. 
Longest sentence by word is 242. 
Longest word is 104. 
Number of buckets:  39
Training set: 65467 instances; Dev set: 3614 instances.
Initialization....
Bucket 1, 0.550416 seconds
Bucket 2, 0.168652 seconds
Bucket 3, 0.161346 seconds
Bucket 4, 0.160681 seconds
Bucket 5, 0.157532 seconds
Bucket 6, 0.162069 seconds
Bucket 7, 0.158297 seconds
Bucket 8, 0.502789 seconds
Bucket 9, 0.184769 seconds
Bucket 10, 0.170335 seconds
Bucket 11, 0.170497 seconds
Bucket 12, 0.170908 seconds
Bucket 13, 0.160382 seconds
Bucket 14, 0.156919 seconds
Bucket 15, 0.165783 seconds
Bucket 16, 0.160574 seconds
Bucket 17, 0.157988 seconds
Bucket 18, 0.539743 seconds
Bucket 19, 0.161247 seconds
Bucket 20, 0.157858 seconds
Bucket 21, 0.158109 seconds
Bucket 22, 0.157653 seconds
Bucket 23, 0.162453 seconds
Bucket 24, 0.159979 seconds
Bucket 25, 0.160345 seconds
Bucket 26, 0.159107 seconds
Bucket 27, 0.157024 seconds
Bucket 28, 0.163711 seconds
Bucket 29, 0.166551 seconds
Bucket 30, 0.566433 seconds
Bucket 31, 0.170970 seconds
Bucket 32, 0.161497 seconds
Bucket 33, 0.161153 seconds
Bucket 34, 0.160404 seconds
Bucket 35, 0.158395 seconds
Bucket 36, 0.157466 seconds
Bucket 37, 0.157951 seconds
Bucket 38, 0.158092 seconds
Bucket 39, 0.161362 seconds
Training preparation...
Defining loss...
Computing gradients...
Bucket 1, 1.392454 seconds
Bucket 2, 1.747467 seconds
Bucket 3, 2.167475 seconds
Bucket 4, 2.559225 seconds
Bucket 5, 2.957130 seconds
Bucket 6, 3.779853 seconds
Bucket 7, 6.464422 seconds
Bucket 8, 4.260952 seconds
Bucket 9, 4.711302 seconds
Bucket 10, 5.025151 seconds
Bucket 11, 5.500359 seconds
Bucket 12, 5.914242 seconds
Bucket 13, 6.332796 seconds
Bucket 14, 9.682850 seconds
Bucket 15, 7.098299 seconds
Bucket 16, 7.518259 seconds
Bucket 17, 7.948305 seconds
Bucket 18, 8.351705 seconds
Bucket 19, 8.862128 seconds
Bucket 20, 13.295040 seconds
Bucket 21, 9.842445 seconds
Bucket 22, 10.198705 seconds
Bucket 23, 10.793105 seconds
Bucket 24, 11.225740 seconds
Bucket 25, 11.591411 seconds
Bucket 26, 17.541041 seconds
Bucket 27, 12.941267 seconds
Bucket 28, 12.878641 seconds
Bucket 29, 13.260415 seconds
Bucket 30, 13.689006 seconds
Bucket 31, 14.604815 seconds
Bucket 32, 23.207380 seconds
Bucket 33, 15.517427 seconds
Bucket 34, 15.755663 seconds
Bucket 35, 16.178133 seconds
Bucket 36, 16.554654 seconds
Bucket 37, 17.493666 seconds
Bucket 38, 31.131514 seconds
Bucket 39, 20.406225 seconds
Done. Time consumed: 690 seconds
epoch: 1
Segmentation F1-score: 0.946775
POS Tagging F1-score: 0.890895

Time consumed: 3331 seconds
epoch: 2
Segmentation F1-score: 0.954062
POS Tagging F1-score: 0.903157

Time consumed: 2517 seconds
epoch: 3
Segmentation F1-score: 0.953157
POS Tagging F1-score: 0.903702

Time consumed: 2828 seconds
epoch: 4
Segmentation F1-score: 0.952779
POS Tagging F1-score: 0.902025

Time consumed: 2560 seconds
epoch: 5
Segmentation F1-score: 0.953005
POS Tagging F1-score: 0.901854

Time consumed: 2564 seconds
epoch: 6
Segmentation F1-score: 0.953154
POS Tagging F1-score: 0.902916

Time consumed: 2577 seconds
epoch: 7
Segmentation F1-score: 0.952056
POS Tagging F1-score: 0.900956

Time consumed: 2702 seconds
epoch: 8
Segmentation F1-score: 0.952503
POS Tagging F1-score: 0.900880

Time consumed: 2648 seconds
epoch: 9
Segmentation F1-score: 0.952822
POS Tagging F1-score: 0.901481

Time consumed: 2571 seconds
epoch: 10
Segmentation F1-score: 0.953109
POS Tagging F1-score: 0.901661

Time consumed: 2652 seconds
epoch: 11
Segmentation F1-score: 0.953096
POS Tagging F1-score: 0.902533

Time consumed: 2566 seconds
epoch: 12
Segmentation F1-score: 0.953250
POS Tagging F1-score: 0.902063

Time consumed: 2567 seconds
epoch: 13
Segmentation F1-score: 0.953606
POS Tagging F1-score: 0.901709

Time consumed: 2566 seconds
epoch: 14
Segmentation F1-score: 0.953180
POS Tagging F1-score: 0.902263

Time consumed: 2572 seconds
epoch: 15
Segmentation F1-score: 0.953232
POS Tagging F1-score: 0.902191

Time consumed: 2567 seconds
epoch: 16
Segmentation F1-score: 0.953600
POS Tagging F1-score: 0.902703

Time consumed: 2568 seconds
epoch: 17
Segmentation F1-score: 0.953683
POS Tagging F1-score: 0.902042

Time consumed: 2567 seconds
epoch: 18
Segmentation F1-score: 0.953847
POS Tagging F1-score: 0.902572

Time consumed: 2561 seconds
epoch: 19
Segmentation F1-score: 0.954067
POS Tagging F1-score: 0.902715

Time consumed: 2574 seconds
epoch: 20
Segmentation F1-score: 0.953508
POS Tagging F1-score: 0.902519

Time consumed: 2575 seconds
epoch: 21
Segmentation F1-score: 0.953929
POS Tagging F1-score: 0.902564

Time consumed: 2575 seconds
epoch: 22
Segmentation F1-score: 0.953955
POS Tagging F1-score: 0.902651

Time consumed: 2571 seconds
epoch: 23
Segmentation F1-score: 0.953802
POS Tagging F1-score: 0.902159

Time consumed: 2569 seconds
epoch: 24
Segmentation F1-score: 0.953588
POS Tagging F1-score: 0.902498

Time consumed: 2430 seconds
epoch: 25
Segmentation F1-score: 0.953646
POS Tagging F1-score: 0.902635

Time consumed: 2426 seconds
epoch: 26
Segmentation F1-score: 0.953572
POS Tagging F1-score: 0.902192

Time consumed: 2428 seconds
epoch: 27
Segmentation F1-score: 0.953659
POS Tagging F1-score: 0.902185

Time consumed: 2420 seconds
epoch: 28
Segmentation F1-score: 0.953399
POS Tagging F1-score: 0.901987

Time consumed: 2427 seconds
epoch: 29
Segmentation F1-score: 0.953807
POS Tagging F1-score: 0.902405

Time consumed: 2410 seconds
epoch: 30
Segmentation F1-score: 0.953448
POS Tagging F1-score: 0.902083

Time consumed: 2384 seconds
Training is finished!
Best segmentation F1-score: 0.954067
Best POS Tagging F1-score: 0.902715
Best epoch: 19

Done. Time consumed: 77286 seconds
~/repos/chinese_orca