tagger icon indicating copy to clipboard operation
tagger copied to clipboard
verified publisher icon glample

IOError "No such file or directory: './evaluation/temp/eval.1181043.scores "

Open Daisy-123 opened this issue 7 years ago • 3 comments

Hi I tried this code " time /tools/anaconda2/bin/python train.py --train dataset/train1400.iob --dev dataset/dev300.iob --test dataset/test284.iob --tag_scheme iob > test-output0611 " , but I got the error message " IOError: [Errno 2] No such file or directory: './evaluation/temp/eval.1181043.scores "

How can I solve this problem ?

Daisy-123 avatar Jun 13 '18 02:06 Daisy-123

What does the full log file contain? Could you check this is not a problem with permissions and that the script is allowed to create this scores file in the temp directory? (Also, does the temp directory exist?)

glample avatar Jun 13 '18 07:06 glample

  • Full log : WARNING (theano.tensor.blas): Using NumPy C-API based implementation for BLAS functions. Traceback (most recent call last): File "train.py", line 222, in test_data, id_to_tag, dico_tags) File "/mnt/Storage01/blue90211/tagger-master/utils.py", line 277, in evaluate eval_lines = [l.rstrip() for l in codecs.open(scores_path, 'r', 'utf8')] File "/tools/anaconda2/lib/python2.7/codecs.py", line 896, in open file = builtin.open(filename, mode, buffering) IOError: [Errno 2] No such file or directory: './evaluation/temp/eval.1181043.scores'
  • Temp directory is generated by script (not exited before).
  • I got eval.1181043.output file in temp directory ,but I can't find eval.1181043.scores.
  • The process seems on going ... as below (stopped in epoch 0) : " .............. 27900, cost average: 0.028285 27950, cost average: 0.456446 processed 1307517 tokens with 3937 phrases; found: 324 phrases; correct: 192. accuracy: 99.30%; precision: 59.26%; recall: 4.88%; FB1: 9.01 Claim: precision: 59.26%; recall: 15.79%; FB1: 24.94 324 PriorArt: precision: 0.00%; recall: 0.00%; FB1: 0.00 0 ID NE Total OI-ClaimB-PriorArtI-PriorArtB-Claim Percent 0 O12952511294615 583 0 0 53 99.951 1I-Claim 6480 2950 3530 0 0 0 54.475 2B-PriorArt 2721 2655 65 0 0 1 0.000 3I-PriorArt 1849 1839 10 0 0 0 0.000 4B-Claim 1216 922 24 0 0 270 22.204 1298415/1307517 (99.30387%) processed 1133259 tokens with 4170 phrases; found: 302 phrases; correct: 171. accuracy: 99.20%; precision: 56.62%; recall: 4.10%; FB1: 7.65 Claim: precision: 56.90%; recall: 14.07%; FB1: 22.56 297 PriorArt: precision: 40.00%; recall: 0.07%; FB1: 0.13 5 ID NE Total OI-ClaimB-PriorArtI-PriorArtB-Claim Percent 0 O11213951120900 443 2 0 50 99.956 1I-Claim 5686 2610 3074 0 0 2 54.063 2B-PriorArt 2969 2906 58 2 0 3 0.067 3I-PriorArt 2008 1981 24 1 0 2 0.000 4B-Claim 1201 926 40 0 0 235 19.567 1124211/1133259 (99.20159%) Score on dev: 9.01000 Score on test: 7.65000 New best score on dev. Saving model to disk... New best score on test. 28000, cost average: 0.016292 28050, cost average: 0.545872 28100, cost average: 0.665584 28150, cost average: 0.817216 28200, cost average: 0.029983 28250, cost average: 0.342566 28300, cost average: 0.429246 28350, cost average: 0.035073 28400, cost average: 0.009134 28450, cost average: 0.274903 28500, cost average: 0.448717 28550, cost average: 0.014378 28600, cost average: 0.342188 28650, cost average: 0.033076 28700, cost average: 0.010674 28750, cost average: 0.009748 28800, cost average: 0.018098 28850, cost average: 0.020268 28900, cost average: 0.022872 28950, cost average: 0.271496 processed 1307517 tokens with 3937 phrases; found: 534 phrases; correct: 30. accuracy: 99.24%; precision: 5.62%; recall: 0.76%; FB1: 1.34 Claim: precision: 5.62%; recall: 2.47%; FB1: 3.43 534 PriorArt: precision: 0.00%; recall: 0.00%; FB1: 0.00 0 ID NE Total OI-ClaimB-PriorArtI-PriorArtB-Claim Percent 0 O12952511292716 2424 0 0 111 99.804 1I-Claim 6480 1968 4509 0 0 3 69.583 2B-PriorArt 2721 2324 370 0 0 27 0.000 3I-PriorArt 1849 1702 137 0 0 10 0.000 4B-Claim 1216 749 88 0 0 379 31.168 1297604/1307517 (99.24185%) .................... "

Daisy-123 avatar Jun 13 '18 08:06 Daisy-123

  • Full log : WARNING (theano.tensor.blas): Using NumPy C-API based implementation for BLAS functions. Traceback (most recent call last): File "train.py", line 222, in test_data, id_to_tag, dico_tags) File "/mnt/Storage01/blue90211/tagger-master/utils.py", line 277, in evaluate eval_lines = [l.rstrip() for l in codecs.open(scores_path, 'r', 'utf8')] File "/tools/anaconda2/lib/python2.7/codecs.py", line 896, in open file = builtin.open(filename, mode, buffering) IOError: [Errno 2] No such file or directory: './evaluation/temp/eval.1181043.scores'
  • Temp directory is generated by script (not exited before).
  • I got eval.1181043.output file in temp directory ,but I can't find eval.1181043.scores.
  • The process seems on going ... as below (stopped in epoch 0) : " .............. 27900, cost average: 0.028285 27950, cost average: 0.456446 processed 1307517 tokens with 3937 phrases; found: 324 phrases; correct: 192. accuracy: 99.30%; precision: 59.26%; recall: 4.88%; FB1: 9.01 Claim: precision: 59.26%; recall: 15.79%; FB1: 24.94 324 PriorArt: precision: 0.00%; recall: 0.00%; FB1: 0.00 0 ID NE Total OI-ClaimB-PriorArtI-PriorArtB-Claim Percent 0 O12952511294615 583 0 0 53 99.951 1I-Claim 6480 2950 3530 0 0 0 54.475 2B-PriorArt 2721 2655 65 0 0 1 0.000 3I-PriorArt 1849 1839 10 0 0 0 0.000 4B-Claim 1216 922 24 0 0 270 22.204 1298415/1307517 (99.30387%) processed 1133259 tokens with 4170 phrases; found: 302 phrases; correct: 171. accuracy: 99.20%; precision: 56.62%; recall: 4.10%; FB1: 7.65 Claim: precision: 56.90%; recall: 14.07%; FB1: 22.56 297 PriorArt: precision: 40.00%; recall: 0.07%; FB1: 0.13 5 ID NE Total OI-ClaimB-PriorArtI-PriorArtB-Claim Percent 0 O11213951120900 443 2 0 50 99.956 1I-Claim 5686 2610 3074 0 0 2 54.063 2B-PriorArt 2969 2906 58 2 0 3 0.067 3I-PriorArt 2008 1981 24 1 0 2 0.000 4B-Claim 1201 926 40 0 0 235 19.567 1124211/1133259 (99.20159%) Score on dev: 9.01000 Score on test: 7.65000 New best score on dev. Saving model to disk... New best score on test. 28000, cost average: 0.016292 28050, cost average: 0.545872 28100, cost average: 0.665584 28150, cost average: 0.817216 28200, cost average: 0.029983 28250, cost average: 0.342566 28300, cost average: 0.429246 28350, cost average: 0.035073 28400, cost average: 0.009134 28450, cost average: 0.274903 28500, cost average: 0.448717 28550, cost average: 0.014378 28600, cost average: 0.342188 28650, cost average: 0.033076 28700, cost average: 0.010674 28750, cost average: 0.009748 28800, cost average: 0.018098 28850, cost average: 0.020268 28900, cost average: 0.022872 28950, cost average: 0.271496 processed 1307517 tokens with 3937 phrases; found: 534 phrases; correct: 30. accuracy: 99.24%; precision: 5.62%; recall: 0.76%; FB1: 1.34 Claim: precision: 5.62%; recall: 2.47%; FB1: 3.43 534 PriorArt: precision: 0.00%; recall: 0.00%; FB1: 0.00 0 ID NE Total OI-ClaimB-PriorArtI-PriorArtB-Claim Percent 0 O12952511292716 2424 0 0 111 99.804 1I-Claim 6480 1968 4509 0 0 3 69.583 2B-PriorArt 2721 2324 370 0 0 27 0.000 3I-PriorArt 1849 1702 137 0 0 10 0.000 4B-Claim 1216 749 88 0 0 379 31.168 1297604/1307517 (99.24185%) .................... "

Hi, I have the same bug. Have you solved it? How did you solve it? Thanks~

junchenzhi avatar Jun 18 '21 09:06 junchenzhi