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full_profiling
/home/vdvinh/miniconda3/envs/ml/bin/python /home/vdvinh/projects/profile_gru/sentiment.py
2017-05-11 10:43:53,153 : INFO : LOG_FILE
2017-05-11 10:43:53,154 : INFO : _________________________________start___________________________________
2017-05-11 10:43:53,156 : INFO : name default_log
2017-05-11 10:43:53,157 : INFO : batchsize 25
2017-05-11 10:43:53,157 : INFO : epochs 10
2017-05-11 10:43:53,157 : INFO : lr 0.05
2017-05-11 10:43:53,157 : INFO : emblr 0
2017-05-11 10:43:53,157 : INFO : tag_emblr 0
2017-05-11 10:43:53,157 : INFO : rel_emblr 0
2017-05-11 10:43:53,158 : INFO : wd 0.0001
2017-05-11 10:43:53,158 : INFO : reg 0.0001
2017-05-11 10:43:53,158 : INFO : optim adagrad
2017-05-11 10:43:53,158 : INFO : input_dim 300
2017-05-11 10:43:53,158 : INFO : mem_dim 150
2017-05-11 10:43:53,158 : INFO : tag_dim 0
2017-05-11 10:43:53,159 : INFO : rel_dim 0
2017-05-11 10:43:53,159 : INFO : at_hid_dim 0
2017-05-11 10:43:53,159 : INFO : tag_glove False
2017-05-11 10:43:53,159 : INFO : rel_glove False
2017-05-11 10:43:53,165 : INFO : Namespace(at_hid_dim=0, batchsize=25, cuda=True, data='data/sst/', emblr=0, epochs=10, fine_grain=False, glove='../treelstm.pytorch/data/glove/', input_dim=300, lr=0.05, mem_dim=150, name='default_log', num_classes=3, optim='adagrad', reg=0.0001, rel_dim=0, rel_emblr=0, rel_glove=False, saved='saved_model/', seed=123, tag_dim=0, tag_emblr=0, tag_glove=False, wd=0.0001, word_dim=300)
2017-05-11 10:43:53,393 : INFO : ==> SST vocabulary size : 21701
2017-05-11 10:43:53,393 : INFO : ==> SST rel vocabulary size : 44
2017-05-11 10:43:53,393 : INFO : ==> SST tag vocabulary size : 43
2017-05-11 10:44:00,023 : INFO : optim adagrad
2017-05-11 10:44:00,023 : INFO : learning rate 0.05
2017-05-11 10:44:00,023 : INFO : embedding learning rate 0
2017-05-11 10:44:00,024 : INFO : weight decay0.0001
2017-05-11 10:44:00,024 : INFO : _param count_
2017-05-11 10:44:00,024 : INFO : torch.Size([150, 150])
2017-05-11 10:44:00,024 : INFO : torch.Size([150])
2017-05-11 10:44:00,025 : INFO : torch.Size([150, 300])
2017-05-11 10:44:00,025 : INFO : torch.Size([150])
2017-05-11 10:44:00,025 : INFO : torch.Size([150, 300])
2017-05-11 10:44:00,025 : INFO : torch.Size([150])
2017-05-11 10:44:00,026 : INFO : torch.Size([150, 300])
2017-05-11 10:44:00,026 : INFO : torch.Size([150])
2017-05-11 10:44:00,026 : INFO : torch.Size([150, 150])
2017-05-11 10:44:00,026 : INFO : torch.Size([150])
2017-05-11 10:44:00,026 : INFO : torch.Size([150, 450])
2017-05-11 10:44:00,027 : INFO : torch.Size([150])
2017-05-11 10:44:00,027 : INFO : torch.Size([150, 450])
2017-05-11 10:44:00,027 : INFO : torch.Size([150])
2017-05-11 10:44:00,027 : INFO : torch.Size([150, 450])
2017-05-11 10:44:00,027 : INFO : torch.Size([150])
2017-05-11 10:44:00,028 : INFO : torch.Size([3, 150])
2017-05-11 10:44:00,028 : INFO : torch.Size([3])
2017-05-11 10:44:00,028 : INFO : sum
2017-05-11 10:44:00,028 : INFO : 384153
2017-05-11 10:44:00,028 : INFO : ____________
Training epoch 1: 100%|██████████| 872/872 [01:43<00:00, 8.39it/s]
/home/vdvinh/projects/profile_gru/trainer.py:78: UserWarning: torch.range is deprecated in favor of torch.arange and will be removed in 0.3. Note that arange generates values in [start; end), not [start; end].
indices = torch.range(1,dataset.num_classes)
Testing epoch 1: 100%|██████████| 872/872 [00:42<00:00, 20.29it/s]
2017-05-11 10:46:27,200 : INFO : ==> Train loss : 0.484477
2017-05-11 10:46:27,200 : INFO : Epoch
2017-05-11 10:46:27,200 : INFO : 0
2017-05-11 10:46:27,200 : INFO : dev percentage
2017-05-11 10:46:27,200 : INFO : 0.553899082569
2017-05-11 10:46:27,686 : INFO : 22312677 function calls (21019338 primitive calls) in 147.615 seconds
2017-05-11 10:46:27,686 : INFO :
2017-05-11 10:46:27,686 : INFO : Ordered by: cumulative time
2017-05-11 10:46:27,686 : INFO :
2017-05-11 10:46:27,687 : INFO : ncalls tottime percall cumtime percall filename:lineno(function)
2017-05-11 10:46:27,687 : INFO : 1 0.475 0.475 104.154 104.154 /home/vdvinh/projects/profile_gru/trainer.py:23(train)
2017-05-11 10:46:27,687 : INFO : 455667/4360 2.857 0.000 98.667 0.023 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/modules/module.py:205(__call__)
2017-05-11 10:46:27,687 : INFO : 1744 0.011 0.000 98.269 0.056 /home/vdvinh/projects/profile_gru/model_gru.py:290(forward)
2017-05-11 10:46:27,687 : INFO : 34092/1744 1.660 0.000 98.217 0.056 /home/vdvinh/projects/profile_gru/model_gru.py:124(forward)
2017-05-11 10:46:27,687 : INFO : 52616 4.094 0.000 66.485 0.001 /home/vdvinh/projects/profile_gru/model_gru.py:60(forward)
2017-05-11 10:46:27,687 : INFO : 13824 0.688 0.000 46.913 0.003 /home/vdvinh/projects/profile_gru/model_gru.py:174(node_forward)
2017-05-11 10:46:27,687 : INFO : 872 0.010 0.000 43.109 0.049 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/variable.py:116(backward)
2017-05-11 10:46:27,687 : INFO : 872 43.079 0.049 43.079 0.049 {method 'run_backward' of 'torch._C._EngineBase' objects}
2017-05-11 10:46:27,687 : INFO : 1 0.217 0.217 42.998 42.998 /home/vdvinh/projects/profile_gru/trainer.py:72(test)
2017-05-11 10:46:27,688 : INFO : 32348 0.126 0.000 41.591 0.001 /home/vdvinh/projects/profile_gru/model_gru.py:264(forward)
2017-05-11 10:46:27,688 : INFO : 349788 6.792 0.000 34.269 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/modules/linear.py:50(forward)
2017-05-11 10:46:27,688 : INFO : 20268 0.137 0.000 26.320 0.001 /home/vdvinh/projects/profile_gru/model_gru.py:156(leaf_forward)
2017-05-11 10:46:27,688 : INFO : 349788 4.626 0.000 26.173 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/_functions/linear.py:7(forward)
2017-05-11 10:46:27,688 : INFO : 258495 0.303 0.000 11.335 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/variable.py:744(__add__)
2017-05-11 10:46:27,688 : INFO : 258495 0.266 0.000 11.032 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/variable.py:282(add)
2017-05-11 10:46:27,688 : INFO : 258495 2.953 0.000 10.767 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/variable.py:275(_add)
2017-05-11 10:46:27,688 : INFO : 208495 2.674 0.000 10.157 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/_functions/thnn/auto.py:109(forward)
2017-05-11 10:46:27,688 : INFO : 34092 0.355 0.000 8.801 0.000 /home/vdvinh/projects/profile_gru/model.py:178(forward)
2017-05-11 10:46:27,689 : INFO : 103795 1.024 0.000 7.748 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/variable.py:242(cuda)
2017-05-11 10:46:27,689 : INFO : 1013459 6.918 0.000 6.918 0.000 {method 'new' of 'torch._C.CudaFloatTensorBase' objects}
2017-05-11 10:46:27,689 : INFO : 105232 1.343 0.000 6.909 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/functional.py:441(sigmoid)
2017-05-11 10:46:27,689 : INFO : 258495 0.615 0.000 6.789 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/_functions/basic_ops.py:14(forward)
2017-05-11 10:46:27,689 : INFO : 349788 6.026 0.000 6.026 0.000 {method 'addmm_' of 'torch._C.CudaFloatTensorBase' objects}
2017-05-11 10:46:27,689 : INFO : 259107 5.977 0.000 5.977 0.000 {method 'add' of 'torch._C.CudaFloatTensorBase' objects}
2017-05-11 10:46:27,689 : INFO : 103795 0.302 0.000 5.917 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/_functions/tensor.py:154(forward)
2017-05-11 10:46:27,689 : INFO : 103795 2.595 0.000 5.578 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/_utils.py:37(_cuda)
2017-05-11 10:46:27,689 : INFO : 403276 5.080 0.000 5.080 0.000 {method 'fill_' of 'torch._C.CudaFloatTensorBase' objects}
2017-05-11 10:46:27,689 : INFO : 105232 0.167 0.000 4.201 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/variable.py:760(__mul__)
2017-05-11 10:46:27,690 : INFO : 105232 1.161 0.000 4.034 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/variable.py:301(mul)
2017-05-11 10:46:27,690 : INFO : 13824 0.668 0.000 3.859 0.000 /home/vdvinh/projects/profile_gru/model_gru.py:201(get_child_state)
2017-05-11 10:46:27,690 : INFO : 349788 3.779 0.000 3.779 0.000 {method 'addr_' of 'torch._C.CudaFloatTensorBase' objects}
2017-05-11 10:46:27,690 : INFO : 52616 1.152 0.000 3.493 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/variable.py:757(__rsub__)
2017-05-11 10:46:27,690 : INFO : 52616 0.686 0.000 3.442 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/functional.py:437(tanh)
2017-05-11 10:46:27,690 : INFO : 50647 0.640 0.000 3.225 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/functional.py:433(log_softmax)
2017-05-11 10:46:27,690 : INFO : 1744 0.043 0.000 3.138 0.002 /home/vdvinh/projects/profile_gru/dataset.py:135(__getitem__)
2017-05-11 10:46:27,690 : INFO : 688816/8720 0.796 0.000 3.094 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/copy.py:145(deepcopy)
2017-05-11 10:46:27,690 : INFO : 105232 0.389 0.000 2.830 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/_functions/basic_ops.py:42(forward)
2017-05-11 10:46:27,691 : INFO : 16555 0.071 0.000 2.727 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/modules/loss.py:318(forward)
2017-05-11 10:46:27,691 : INFO : 34092 0.384 0.000 2.716 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/functional.py:365(dropout)
2017-05-11 10:46:27,691 : INFO : 16555 0.059 0.000 2.610 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/functional.py:518(cross_entropy)
2017-05-11 10:46:27,691 : INFO : 64696/32348 1.528 0.000 2.599 0.000 {torch._C.cat}
2017-05-11 10:46:27,691 : INFO : 32348 0.365 0.000 2.480 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/variable.py:839(cat)
2017-05-11 10:46:27,691 : INFO : 34092/1744 0.196 0.000 2.372 0.001 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/copy.py:306(_reconstruct)
2017-05-11 10:46:27,691 : INFO : 1589806 2.368 0.000 2.368 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/modules/module.py:224(__getattr__)
2017-05-11 10:46:27,691 : INFO : 34092/1744 0.246 0.000 2.288 0.001 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/copy.py:253(_deepcopy_dict)
2017-05-11 10:46:27,691 : INFO : 105232 2.271 0.000 2.271 0.000 {method 'mul' of 'torch._C.CudaFloatTensorBase' objects}
2017-05-11 10:46:27,691 : INFO : 105232 2.219 0.000 2.219 0.000 {torch._thnn._THCUNN.CudaSigmoid_updateOutput}
2017-05-11 10:46:27,692 : INFO : 34092/1744 0.059 0.000 2.194 0.001 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/copy.py:226(_deepcopy_list)
2017-05-11 10:46:27,692 : INFO : 34092 0.327 0.000 2.150 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/_functions/dropout.py:20(forward)
2017-05-11 10:46:27,692 : INFO : 52616 0.305 0.000 2.073 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/_functions/basic_ops.py:100(forward)
2017-05-11 10:46:27,692 : INFO : 32348 0.138 0.000 1.568 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/_functions/tensor.py:308(forward)
2017-05-11 10:46:27,692 : INFO : 66440 0.626 0.000 1.527 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/variable.py:65(__getitem__)
2017-05-11 10:46:27,692 : INFO : 61740 1.519 0.000 1.519 0.000 {method 'copy_' of 'torch._C.CudaFloatTensorBase' objects}
2017-05-11 10:46:27,692 : INFO : 16555 0.374 0.000 1.451 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/functional.py:468(nll_loss)
2017-05-11 10:46:27,692 : INFO : 33220 0.314 0.000 1.396 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/variable.py:71(__setitem__)
2017-05-11 10:46:27,692 : INFO : 455667 0.983 0.000 1.381 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/collections.py:121(values)
2017-05-11 10:46:27,692 : INFO : 379295 1.196 0.000 1.196 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/function.py:142(__init__)
2017-05-11 10:46:27,693 : INFO : 414289 0.861 0.000 1.182 0.000 {getattr}
2017-05-11 10:46:27,693 : INFO : 349788 1.165 0.000 1.165 0.000 {method 't' of 'torch._C.CudaFloatTensorBase' objects}
2017-05-11 10:46:27,693 : INFO : 52616 1.120 0.000 1.120 0.000 {torch._thnn._THCUNN.CudaTanh_updateOutput}
2017-05-11 10:46:27,693 : INFO : 50647 1.008 0.000 1.008 0.000 {torch._thnn._THCUNN.CudaLogSoftMax_updateOutput}
2017-05-11 10:46:27,693 : INFO : 2 0.932 0.466 0.932 0.466 {gc.collect}
2017-05-11 10:46:27,693 : INFO : 16555 0.197 0.000 0.920 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/_functions/thnn/auto.py:31(forward)
2017-05-11 10:46:27,693 : INFO : 1610081 0.905 0.000 0.905 0.000 {method 'size' of 'torch._C.CudaFloatTensorBase' objects}
2017-05-11 10:46:27,693 : INFO : 33220 0.109 0.000 0.893 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/_functions/tensor.py:33(forward)
2017-05-11 10:46:27,693 : INFO : 34092 0.858 0.000 0.858 0.000 {method 'clone' of 'torch._C.CudaFloatTensorBase' objects}
2017-05-11 10:46:27,694 : INFO : 103795 0.808 0.000 0.808 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/_functions/tensor.py:149(__init__)
2017-05-11 10:46:27,694 : INFO : 34092 0.759 0.000 0.760 0.000 {method '__reduce_ex__' of 'object' objects}
2017-05-11 10:46:27,694 : INFO : 208495 0.751 0.000 0.751 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/_functions/thnn/auto.py:93(__init__)
2017-05-11 10:46:27,694 : INFO : 33220 0.738 0.000 0.738 0.000 {method '_set_index' of 'torch._C.CudaFloatTensorBase' objects}
2017-05-11 10:46:27,694 : INFO : 66440 0.213 0.000 0.654 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/_functions/tensor.py:14(forward)
2017-05-11 10:46:27,694 : INFO : 21787 0.632 0.000 0.632 0.000 {method 'copy_' of 'torch._C.CudaLongTensorBase' objects}
2017-05-11 10:46:27,694 : INFO : 1063153 0.621 0.000 0.621 0.000 {isinstance}
2017-05-11 10:46:27,694 : INFO : 52616 0.598 0.000 0.598 0.000 {method 'sub_' of 'torch._C.CudaFloatTensorBase' objects}
2017-05-11 10:46:27,694 : INFO : 32348 0.547 0.000 0.547 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/_functions/tensor.py:304(__init__)
2017-05-11 10:46:27,694 : INFO : 47917 0.530 0.000 0.530 0.000 {torch._C.zeros}
2017-05-11 10:46:27,695 : INFO : 61741 0.524 0.000 0.524 0.000 {method 'size' of 'torch._C.FloatTensorBase' objects}
2017-05-11 10:46:27,695 : INFO : 226794 0.303 0.000 0.413 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/_thnn/__init__.py:14(__getitem__)
2017-05-11 10:46:27,695 : INFO : 682686 0.399 0.000 0.399 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/function.py:46(save_for_backward)
2017-05-11 10:46:27,695 : INFO : 456092 0.398 0.000 0.398 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/collections.py:90(__iter__)
2017-05-11 10:46:27,695 : INFO : 351532 0.300 0.000 0.389 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/backends/backend.py:7(__getattr__)
2017-05-11 10:46:27,695 : INFO : 208495 0.368 0.000 0.368 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/_functions/thnn/auto.py:100(_initialize_buffers)
2017-05-11 10:46:27,695 : INFO : 66440 0.346 0.000 0.346 0.000 {method 'index' of 'torch._C.CudaFloatTensorBase' objects}
2017-05-11 10:46:27,695 : INFO : 16555 0.332 0.000 0.332 0.000 {torch._thnn._THCUNN.CudaClassNLLCriterion_updateOutput}
2017-05-11 10:46:27,695 : INFO : 225050 0.250 0.000 0.321 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/_thnn/utils.py:19(__getattr__)
2017-05-11 10:46:27,695 : INFO : 1529910 0.315 0.000 0.315 0.000 {method 'get' of 'dict' objects}
2017-05-11 10:46:27,696 : INFO : 34092 0.189 0.000 0.289 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/copy.py:234(_deepcopy_tuple)
2017-05-11 10:46:27,696 : INFO : 70534 0.280 0.000 0.280 0.000 {method 'resize_as_' of 'torch._C.CudaFloatTensorBase' objects}
2017-05-11 10:46:27,696 : INFO : 52616 0.158 0.000 0.267 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/_functions/basic_ops.py:95(__init__)
2017-05-11 10:46:27,696 : INFO : 256420 0.248 0.000 0.248 0.000 {range}
2017-05-11 10:46:27,696 : INFO : 17046 0.241 0.000 0.241 0.000 {method 'mul_' of 'torch._C.CudaFloatTensorBase' objects}
2017-05-11 10:46:27,696 : INFO : 1744 0.019 0.000 0.234 0.000 /home/vdvinh/projects/profile_gru/embedding_model.py:27(forward)
2017-05-11 10:46:27,696 : INFO : 872 0.002 0.000 0.234 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/variable.py:784(__div__)
2017-05-11 10:46:27,696 : INFO : 213672 0.177 0.000 0.233 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/copy.py:267(_keep_alive)
2017-05-11 10:46:27,696 : INFO : 872 0.015 0.000 0.232 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/variable.py:313(div)
2017-05-11 10:46:27,697 : INFO : 17046 0.229 0.000 0.229 0.000 {method 'bernoulli_' of 'torch._C.CudaFloatTensorBase' objects}
2017-05-11 10:46:27,697 : INFO : 773513/773495 0.212 0.000 0.212 0.000 {len}
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Training epoch 2: 100%|██████████| 872/872 [01:46<00:00, 10.09it/s]
Testing epoch 2: 100%|██████████| 872/872 [00:44<00:00, 19.63it/s]
2017-05-11 10:48:59,318 : INFO : ==> Train loss : 0.310500
2017-05-11 10:48:59,318 : INFO : Epoch
2017-05-11 10:48:59,318 : INFO : 1
2017-05-11 10:48:59,319 : INFO : dev percentage
2017-05-11 10:48:59,319 : INFO : 0.709862385321
2017-05-11 10:48:59,816 : INFO : 22309839 function calls (21016590 primitive calls) in 152.064 seconds
2017-05-11 10:48:59,817 : INFO :
2017-05-11 10:48:59,817 : INFO : Ordered by: cumulative time
2017-05-11 10:48:59,817 : INFO :
2017-05-11 10:48:59,817 : INFO : ncalls tottime percall cumtime percall filename:lineno(function)
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2017-05-11 10:48:59,821 : INFO : 688816/8720 0.803 0.000 2.942 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/copy.py:145(deepcopy)
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2017-05-11 10:48:59,821 : INFO : 34092/1744 0.243 0.000 2.278 0.001 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/copy.py:253(_deepcopy_dict)
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Training epoch 3: 100%|██████████| 872/872 [01:57<00:00, 5.55it/s]
Testing epoch 3: 100%|██████████| 872/872 [00:44<00:00, 19.56it/s]
2017-05-11 10:51:42,331 : INFO : ==> Train loss : 0.263661
2017-05-11 10:51:42,332 : INFO : Epoch
2017-05-11 10:51:42,332 : INFO : 2
2017-05-11 10:51:42,332 : INFO : dev percentage
2017-05-11 10:51:42,332 : INFO : 0.621559633028
2017-05-11 10:51:42,858 : INFO : 22311036 function calls (21017787 primitive calls) in 162.977 seconds
2017-05-11 10:51:42,858 : INFO :
2017-05-11 10:51:42,858 : INFO : Ordered by: cumulative time
2017-05-11 10:51:42,858 : INFO :
2017-05-11 10:51:42,858 : INFO : ncalls tottime percall cumtime percall filename:lineno(function)
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2017-05-11 10:51:42,862 : INFO : 688816/8720 0.811 0.000 3.016 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/copy.py:145(deepcopy)
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2017-05-11 10:51:42,863 : INFO : 34092/1744 0.200 0.000 2.392 0.001 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/copy.py:306(_reconstruct)
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Training epoch 4: 100%|██████████| 872/872 [02:05<00:00, 6.80it/s]
Testing epoch 4: 100%|██████████| 872/872 [00:43<00:00, 19.93it/s]
2017-05-11 10:54:32,646 : INFO : ==> Train loss : 0.232740
2017-05-11 10:54:32,646 : INFO : Epoch
2017-05-11 10:54:32,647 : INFO : 3
2017-05-11 10:54:32,647 : INFO : dev percentage
2017-05-11 10:54:32,647 : INFO : 0.807339449541
2017-05-11 10:54:33,184 : INFO : 22312378 function calls (21019129 primitive calls) in 170.251 seconds
2017-05-11 10:54:33,184 : INFO :
2017-05-11 10:54:33,185 : INFO : Ordered by: cumulative time
2017-05-11 10:54:33,185 : INFO :
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Training epoch 5: 100%|██████████| 872/872 [02:06<00:00, 6.29it/s]
Testing epoch 5: 100%|██████████| 872/872 [00:42<00:00, 20.50it/s]
2017-05-11 10:57:22,933 : INFO : ==> Train loss : 0.211310
2017-05-11 10:57:22,933 : INFO : Epoch
2017-05-11 10:57:22,933 : INFO : 4
2017-05-11 10:57:22,934 : INFO : dev percentage
2017-05-11 10:57:22,934 : INFO : 0.84747706422
2017-05-11 10:57:23,478 : INFO : 22312469 function calls (21019220 primitive calls) in 170.230 seconds
2017-05-11 10:57:23,478 : INFO :
2017-05-11 10:57:23,478 : INFO : Ordered by: cumulative time
2017-05-11 10:57:23,478 : INFO :
2017-05-11 10:57:23,479 : INFO : ncalls tottime percall cumtime percall filename:lineno(function)
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2017-05-11 10:57:23,479 : INFO : 34092/1744 1.532 0.000 94.506 0.054 /home/vdvinh/projects/profile_gru/model_gru.py:124(forward)
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2017-05-11 10:57:23,481 : INFO : 103795 0.983 0.000 6.238 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/variable.py:242(cuda)
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2017-05-11 10:57:23,482 : INFO : 13824 0.547 0.000 2.862 0.000 /home/vdvinh/projects/profile_gru/model_gru.py:201(get_child_state)
2017-05-11 10:57:23,482 : INFO : 688816/8720 0.768 0.000 2.836 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/copy.py:145(deepcopy)
2017-05-11 10:57:23,482 : INFO : 379295 2.823 0.000 2.823 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/function.py:142(__init__)
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2017-05-11 10:57:23,483 : INFO : 34092 0.368 0.000 2.571 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/functional.py:365(dropout)
2017-05-11 10:57:23,483 : INFO : 16555 0.057 0.000 2.485 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/functional.py:518(cross_entropy)
2017-05-11 10:57:23,483 : INFO : 1589806 2.278 0.000 2.278 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/modules/module.py:224(__getattr__)
2017-05-11 10:57:23,483 : INFO : 34092/1744 0.186 0.000 2.256 0.001 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/copy.py:306(_reconstruct)
2017-05-11 10:57:23,483 : INFO : 34092/1744 0.231 0.000 2.174 0.001 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/copy.py:253(_deepcopy_dict)
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2017-05-11 10:57:23,483 : INFO : 105232 2.133 0.000 2.133 0.000 {torch._thnn._THCUNN.CudaSigmoid_updateOutput}
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2017-05-11 10:57:23,484 : INFO : 32348 0.342 0.000 2.053 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/variable.py:839(cat)
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2017-05-11 10:57:23,484 : INFO : 66440 0.580 0.000 1.436 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/variable.py:65(__getitem__)
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2017-05-11 10:57:23,485 : INFO : 2 0.978 0.489 0.978 0.489 {gc.collect}
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Training epoch 6: 100%|██████████| 872/872 [02:15<00:00, 5.51it/s]
Testing epoch 6: 100%|██████████| 872/872 [00:42<00:00, 20.58it/s]
2017-05-11 11:00:21,691 : INFO : ==> Train loss : 0.190099
2017-05-11 11:00:21,691 : INFO : Epoch
2017-05-11 11:00:21,691 : INFO : 5
2017-05-11 11:00:21,691 : INFO : dev percentage
2017-05-11 11:00:21,691 : INFO : 0.869266055046
2017-05-11 11:00:22,246 : INFO : 22313546 function calls (21020297 primitive calls) in 178.706 seconds
2017-05-11 11:00:22,247 : INFO :
2017-05-11 11:00:22,247 : INFO : Ordered by: cumulative time
2017-05-11 11:00:22,247 : INFO :
2017-05-11 11:00:22,247 : INFO : ncalls tottime percall cumtime percall filename:lineno(function)
2017-05-11 11:00:22,247 : INFO : 1 0.439 0.439 135.785 135.785 /home/vdvinh/projects/profile_gru/trainer.py:23(train)
2017-05-11 11:00:22,247 : INFO : 455667/4360 2.718 0.000 94.743 0.022 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/modules/module.py:205(__call__)
2017-05-11 11:00:22,247 : INFO : 1744 0.011 0.000 94.360 0.054 /home/vdvinh/projects/profile_gru/model_gru.py:290(forward)
2017-05-11 11:00:22,247 : INFO : 34092/1744 1.532 0.000 94.311 0.054 /home/vdvinh/projects/profile_gru/model_gru.py:124(forward)
2017-05-11 11:00:22,248 : INFO : 872 0.010 0.000 78.426 0.090 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/variable.py:116(backward)
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2017-05-11 11:00:22,248 : INFO : 52616 3.844 0.000 64.977 0.001 /home/vdvinh/projects/profile_gru/model_gru.py:60(forward)
2017-05-11 11:00:22,248 : INFO : 13824 0.653 0.000 44.926 0.003 /home/vdvinh/projects/profile_gru/model_gru.py:174(node_forward)
2017-05-11 11:00:22,248 : INFO : 1 0.207 0.207 42.388 42.388 /home/vdvinh/projects/profile_gru/trainer.py:72(test)
2017-05-11 11:00:22,248 : INFO : 32348 0.112 0.000 40.170 0.001 /home/vdvinh/projects/profile_gru/model_gru.py:264(forward)
2017-05-11 11:00:22,248 : INFO : 349788 7.083 0.000 32.810 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/modules/linear.py:50(forward)
2017-05-11 11:00:22,248 : INFO : 20268 0.131 0.000 26.159 0.001 /home/vdvinh/projects/profile_gru/model_gru.py:156(leaf_forward)
2017-05-11 11:00:22,249 : INFO : 349788 4.464 0.000 24.494 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/_functions/linear.py:7(forward)
2017-05-11 11:00:22,249 : INFO : 258495 0.287 0.000 11.968 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/variable.py:744(__add__)
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Training epoch 7: 100%|██████████| 872/872 [02:24<00:00, 5.37it/s]
Testing epoch 7: 100%|██████████| 872/872 [00:43<00:00, 20.21it/s]
2017-05-11 11:03:30,584 : INFO : ==> Train loss : 0.174449
2017-05-11 11:03:30,584 : INFO : Epoch
2017-05-11 11:03:30,584 : INFO : 6
2017-05-11 11:03:30,584 : INFO : dev percentage
2017-05-11 11:03:30,584 : INFO : 0.893348623853
2017-05-11 11:03:31,169 : INFO : 22314855 function calls (21021606 primitive calls) in 188.859 seconds
2017-05-11 11:03:31,169 : INFO :
2017-05-11 11:03:31,169 : INFO : Ordered by: cumulative time
2017-05-11 11:03:31,170 : INFO :
2017-05-11 11:03:31,170 : INFO : ncalls tottime percall cumtime percall filename:lineno(function)
2017-05-11 11:03:31,170 : INFO : 1 0.435 0.435 145.134 145.134 /home/vdvinh/projects/profile_gru/trainer.py:23(train)
2017-05-11 11:03:31,170 : INFO : 455667/4360 2.735 0.000 95.436 0.022 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/modules/module.py:205(__call__)
2017-05-11 11:03:31,170 : INFO : 1744 0.011 0.000 95.047 0.054 /home/vdvinh/projects/profile_gru/model_gru.py:290(forward)
2017-05-11 11:03:31,170 : INFO : 34092/1744 1.528 0.000 94.998 0.054 /home/vdvinh/projects/profile_gru/model_gru.py:124(forward)
2017-05-11 11:03:31,170 : INFO : 872 0.010 0.000 87.853 0.101 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/variable.py:116(backward)
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2017-05-11 11:03:31,171 : INFO : 13824 0.660 0.000 45.870 0.003 /home/vdvinh/projects/profile_gru/model_gru.py:174(node_forward)
2017-05-11 11:03:31,171 : INFO : 1 0.202 0.202 43.161 43.161 /home/vdvinh/projects/profile_gru/trainer.py:72(test)
2017-05-11 11:03:31,171 : INFO : 32348 0.116 0.000 40.537 0.001 /home/vdvinh/projects/profile_gru/model_gru.py:264(forward)
2017-05-11 11:03:31,171 : INFO : 349788 7.164 0.000 32.011 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/modules/linear.py:50(forward)
2017-05-11 11:03:31,171 : INFO : 20268 0.134 0.000 26.940 0.001 /home/vdvinh/projects/profile_gru/model_gru.py:156(leaf_forward)
2017-05-11 11:03:31,171 : INFO : 349788 3.924 0.000 23.601 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/_functions/linear.py:7(forward)
2017-05-11 11:03:31,171 : INFO : 258495 0.298 0.000 10.947 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/autograd/variable.py:744(__add__)
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2017-05-11 11:03:31,171 : INFO : 208495 2.622 0.000 10.449 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/_functions/thnn/auto.py:109(forward)
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2017-05-11 11:03:31,172 : INFO : 105232 1.294 0.000 6.741 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/functional.py:441(sigmoid)
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2017-05-11 11:03:31,173 : INFO : 103795 1.534 0.000 4.811 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/_utils.py:37(_cuda)
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2017-05-11 11:03:31,173 : INFO : 52616 1.217 0.000 4.464 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/functional.py:437(tanh)
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Training epoch 8: 100%|██████████| 872/872 [02:35<00:00, 6.21it/s]
Testing epoch 8: 100%|██████████| 872/872 [00:42<00:00, 20.51it/s]
2017-05-11 11:06:50,071 : INFO : ==> Train loss : 0.152867
2017-05-11 11:06:50,071 : INFO : Epoch
2017-05-11 11:06:50,071 : INFO : 7
2017-05-11 11:06:50,072 : INFO : dev percentage
2017-05-11 11:06:50,072 : INFO : 0.860091743119
2017-05-11 11:06:50,692 : INFO : 22315610 function calls (21022361 primitive calls) in 199.461 seconds
2017-05-11 11:06:50,692 : INFO :
2017-05-11 11:06:50,692 : INFO : Ordered by: cumulative time
2017-05-11 11:06:50,692 : INFO :
2017-05-11 11:06:50,692 : INFO : ncalls tottime percall cumtime percall filename:lineno(function)
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2017-05-11 11:06:50,693 : INFO : 34092/1744 1.535 0.000 94.316 0.054 /home/vdvinh/projects/profile_gru/model_gru.py:124(forward)
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2017-05-11 11:06:50,696 : INFO : 688816/8720 0.765 0.000 2.842 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/copy.py:145(deepcopy)
2017-05-11 11:06:50,696 : INFO : 13824 0.564 0.000 2.779 0.000 /home/vdvinh/projects/profile_gru/model_gru.py:201(get_child_state)
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2017-05-11 11:06:50,697 : INFO : 34092/1744 0.232 0.000 2.188 0.001 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/copy.py:253(_deepcopy_dict)
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Training epoch 9: 100%|██████████| 872/872 [02:40<00:00, 5.80it/s]
Testing epoch 9: 100%|██████████| 872/872 [00:41<00:00, 21.23it/s]
2017-05-11 11:10:12,821 : INFO : ==> Train loss : 0.148605
2017-05-11 11:10:12,821 : INFO : Epoch
2017-05-11 11:10:12,821 : INFO : 8
2017-05-11 11:10:12,821 : INFO : dev percentage
2017-05-11 11:10:12,821 : INFO : 0.935779816514
2017-05-11 11:10:13,413 : INFO : 22315932 function calls (21022683 primitive calls) in 202.660 seconds
2017-05-11 11:10:13,413 : INFO :
2017-05-11 11:10:13,413 : INFO : Ordered by: cumulative time
2017-05-11 11:10:13,414 : INFO :
2017-05-11 11:10:13,414 : INFO : ncalls tottime percall cumtime percall filename:lineno(function)
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2017-05-11 11:10:13,418 : INFO : 34092 0.359 0.000 2.519 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/functional.py:365(dropout)
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2017-05-11 11:10:13,418 : INFO : 34092/1744 0.183 0.000 2.192 0.001 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/copy.py:306(_reconstruct)
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2017-05-11 11:10:13,418 : INFO : 34092/1744 0.227 0.000 2.111 0.001 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/copy.py:253(_deepcopy_dict)
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Training epoch 10: 100%|██████████| 872/872 [02:51<00:00, 5.05it/s]
Testing epoch 10: 100%|██████████| 872/872 [00:41<00:00, 21.16it/s]
2017-05-11 11:13:46,408 : INFO : ==> Train loss : 0.129256
2017-05-11 11:13:46,408 : INFO : Epoch
2017-05-11 11:13:46,409 : INFO : 9
2017-05-11 11:13:46,409 : INFO : dev percentage
2017-05-11 11:13:46,409 : INFO : 0.938073394495
2017-05-11 11:13:47,020 : INFO : 22316118 function calls (21022869 primitive calls) in 213.546 seconds
2017-05-11 11:13:47,020 : INFO :
2017-05-11 11:13:47,020 : INFO : Ordered by: cumulative time
2017-05-11 11:13:47,020 : INFO :
2017-05-11 11:13:47,020 : INFO : ncalls tottime percall cumtime percall filename:lineno(function)
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2017-05-11 11:13:47,057 : INFO : 2 0.000 0.000 0.000 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/_weakrefset.py:67(__len__)
2017-05-11 11:13:47,057 : INFO : 2 0.000 0.000 0.000 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/threading.py:300(_is_owned)
2017-05-11 11:13:47,057 : INFO : 2 0.000 0.000 0.000 0.000 {method 'startswith' of 'str' objects}
2017-05-11 11:13:47,057 : INFO : 2 0.000 0.000 0.000 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/threading.py:294(_release_save)
2017-05-11 11:13:47,057 : INFO : 5 0.000 0.000 0.000 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/multiprocessing/process.py:161(name)
2017-05-11 11:13:47,057 : INFO : 9 0.000 0.000 0.000 0.000 {iter}
2017-05-11 11:13:47,057 : INFO : 5 0.000 0.000 0.000 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/multiprocessing/process.py:59(current_process)
2017-05-11 11:13:47,057 : INFO : 2 0.000 0.000 0.000 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/threading.py:999(daemon)
2017-05-11 11:13:47,057 : INFO : 6 0.000 0.000 0.000 0.000 {thread.allocate_lock}
2017-05-11 11:13:47,058 : INFO : 20 0.000 0.000 0.000 0.000 {method 'size' of 'torch._C.CudaFloatStorageBase' objects}
2017-05-11 11:13:47,058 : INFO : 2 0.000 0.000 0.000 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/tqdm/_tqdm.py:780(__eq__)
2017-05-11 11:13:47,058 : INFO : 2 0.000 0.000 0.000 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/torch/nn/backends/thnn.py:6(__reduce__)
2017-05-11 11:13:47,058 : INFO : 3 0.000 0.000 0.000 0.000 {method 'endswith' of 'str' objects}
2017-05-11 11:13:47,058 : INFO : 5 0.000 0.000 0.000 0.000 {posix.getpid}
2017-05-11 11:13:47,058 : INFO : 2 0.000 0.000 0.000 0.000 {method 'keys' of 'dict' objects}
2017-05-11 11:13:47,058 : INFO : 10 0.000 0.000 0.000 0.000 {method 'end' of '_sre.SRE_Match' objects}
2017-05-11 11:13:47,058 : INFO : 2 0.000 0.000 0.000 0.000 {sys.setcheckinterval}
2017-05-11 11:13:47,058 : INFO : 2 0.000 0.000 0.000 0.000 {method '__enter__' of 'thread.lock' objects}
2017-05-11 11:13:47,058 : INFO : 2 0.000 0.000 0.000 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/site-packages/tqdm/_tqdm.py:117(report)
2017-05-11 11:13:47,059 : INFO : 4 0.000 0.000 0.000 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/threading.py:570(isSet)
2017-05-11 11:13:47,059 : INFO : 2 0.000 0.000 0.000 0.000 {method '__exit__' of 'thread.lock' objects}
2017-05-11 11:13:47,059 : INFO : 5 0.000 0.000 0.000 0.000 /home/vdvinh/miniconda3/envs/ml/lib/python2.7/posixpath.py:44(normcase)
2017-05-11 11:13:47,059 : INFO : 1 0.000 0.000 0.000 0.000 {method 'disable' of '_lsprof.Profiler' objects}
2017-05-11 11:13:47,059 : INFO : epoch 9 dev score of 0.938073394495
2017-05-11 11:13:47,059 : INFO : eva on test set
Testing epoch 0: 100%|██████████| 1821/1821 [01:20<00:00, 22.62it/s]
2017-05-11 11:15:07,927 : INFO : Epoch
2017-05-11 11:15:07,927 : INFO : 9
2017-05-11 11:15:07,927 : INFO : test percentage
2017-05-11 11:15:07,928 : INFO : 0.784184514003
Process finished with exit code 0
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