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meijieru / crnn.pytorch

Convolutional recurrent network in pytorch
MIT License
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Segmentation fault (core dumped) #180

Open lijian-1994 opened 5 years ago

lijian-1994 commented 5 years ago

Ubuntu 17.04
no gpu python 3.6 cs316@xxxx:~/lijian/crnn.pytorch-master$ python train.py -- trainRoot ./data/train --valRoot ./data/val --random_sample --workers 1 Namespace(adadelta=False, adam=False, alphabet='0123456789abcdefghijklmnopqrstuv wxyz/', batchSize=64, beta1=0.5, cuda=False, displayInterval=500, expr_dir='expr ', imgH=32, imgW=100, keep_ratio=False, lr=0.01, manualSeed=1234, n_test_disp=10 , nepoch=25, ngpu=0, nh=256, pretrained='', random_sample=True, saveInterval=500 , trainRoot='./data/train', valInterval=500, valRoot='./data/val', workers=1) CRNN( (cnn): Sequential( (conv0): Conv2d(1, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (relu0): ReLU(inplace) (pooling0): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_m ode=False) (conv1): Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (relu1): ReLU(inplace) (pooling1): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_m ode=False) (conv2): Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (batchnorm2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_r unning_stats=True) (relu2): ReLU(inplace) (conv3): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (relu3): ReLU(inplace) (pooling2): MaxPool2d(kernel_size=(2, 2), stride=(2, 1), padding=(0, 1), dil ation=1, ceil_mode=False) (conv4): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (batchnorm4): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_r unning_stats=True) (relu4): ReLU(inplace) (conv5): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (relu5): ReLU(inplace) (pooling3): MaxPool2d(kernel_size=(2, 2), stride=(2, 1), padding=(0, 1), dil ation=1, ceil_mode=False) (conv6): Conv2d(512, 512, kernel_size=(2, 2), stride=(1, 1)) (batchnorm6): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_r unning_stats=True) (relu6): ReLU(inplace) ) (rnn): Sequential( (0): BidirectionalLSTM( (rnn): LSTM(512, 256, bidirectional=True) (embedding): Linear(in_features=512, out_features=256, bias=True) ) (1): BidirectionalLSTM( (rnn): LSTM(256, 256, bidirectional=True) (embedding): Linear(in_features=512, out_features=38, bias=True) ) ) ) Segmentation fault (core dumped)

when i run,it occur error 'Segmentation fault (core dumped)' and don't have other error message. who can help me?

Xassassinator commented 5 years ago

@lijian-1994 I have met the same issue, did you solved this problem? could you tell me about the details, thank you !

gzhcv commented 5 years ago

I got the same issue, have you sloved it?

zhengjiawen commented 5 years ago

Hi, how did you slove the problem? Can you please share? Thaks.

Marchbruno09 commented 5 years ago

Hi, have u solved this problem?

keevinzha commented 5 years ago

I got the same problem, have someone solved it now?

yunchangxiaoguan commented 4 years ago

wtf！too much problem in this code

apple2333cream commented 3 years ago

I got the same issue, have you sloved it?