I have this line in globalconfig.py:20 VERSION="1.7" and I'm working with fn1.7 data.
I ran the preprocess steps.
Now I'm trying to run the training with this command: python segrnn-argid.py
I'm getting this error:
Traceback (most recent call last):
File "segrnn-argid.py", line 98, in <module>
wvs = get_wvec_map()
File "/Users/pinouchon/code/huggingface/open-sesame/src/dataio.py", line 276, in get_wvec_map
raise Exception("word vector file not found!", FILTERED_WVECS_FILE)
Exception: ('word vector file not found!', '../data/glove.6B.100d.framenet.txt')
The error goes away if I replace
FILTERED_WVECS_FILE = DATADIR + "glove.6B.100d.framenet.txt" with
FILTERED_WVECS_FILE = DATADIR + "glove.6B.100d.txt"
in globalconfig.py:85.
Now the training starts without errors (python segrnn-argid.py).
But after about 40min of training, I get this new error:
[dev epoch=0 after=2001] lprec = 0.40382 lrec = 0.14518 lf1 = 0.21358 -- savinglibc++abi.dylib: terminating with uncaught exception of type std::runtime_error: Could not write model to tmp/1.7model.sra-1527520332.05
This looks like a low-level error inside dynet. I cannot find what is causing it with google/stackoverflow.
I installed dynet with pip install dynet. I'm running OSX High Sierra and python 2.7.10 inside a virtualenv.
I ran the training twice with both times the same error (and a different tmp file name in each case)
The error doesn't look related to my fix in globalconfig.py:85.
Any pointers?
Full output of the training:
[dynet] random seed: 1594657864
[dynet] allocating memory: 512MB
[dynet] memory allocation done.
COMMAND: segrnn-argid.py
PARSER SETTINGS
_____________________
PARSING MODE: train
USING EXEMPLAR? False
USING SPAN CLIP? True
LOSS TYPE: softmaxm
COST TYPE: recall
R-O COST VALUE: 2
USING DROPOUT? True
USING WORDVECS? True
USING HIERARCHY? False
USING D-SYNTAX? False
USING C-SYNTAX? False
USING PTB-CLOSS? False
MODEL WILL BE SAVED TO tmp/1.7model.sra-1527520332.05
_____________________
reading ../data/neural/fn1.7/fn1.7.fulltext.train.syntaxnet.conll...
# examples in ../data/neural/fn1.7/fn1.7.fulltext.train.syntaxnet.conll : 19391 in 3413 sents
# examples with missing arguments : 526
reading the frame-element - frame map from ../data/fndata-1.7/frame/...
# max FEs for frame: 32 in Frame(Traversing)
reading the word vectors file from ../data/glove.6B.100d.txt...
using pretrained embeddings of dimension 100
# words in vocab: 400575
# POS tags: 45
# lexical units: 9441
# LU POS tags: 14
# frames: 1223
# FEs: 1287
# dependency relations: 1
# constituency labels: 1
clipping spans longer than 20...
longest span size: 102
longest FE span size: 89
# train examples before filter: 19391
# train examples after filter: 19391
reading ../data/neural/fn1.7/fn1.7.dev.syntaxnet.conll...
# examples in ../data/neural/fn1.7/fn1.7.dev.syntaxnet.conll : 2272 in 326 sents
# examples with missing arguments : 73
unknowns in dev
_____________________
# unseen, unlearnt test words in vocab: (45, 390570)
# unseen, unlearnt test POS tags: (0, 1)
# unseen, unlearnt test lexical units: (0, 6444)
# unseen, unlearnt test LU pos tags: (0, 3)
# unseen, unlearnt test frames: (0, 469)
# unseen, unlearnt test FEs: (0, 521)
# unseen, unlearnt test deprels: (0, 1)
# unseen, unlearnt test constit labels: (0, 1)
[lr=0.0005 clips=99 updates=100] 100 loss = 38.650128 [took 46.383 s]
[lr=0.0005 clips=100 updates=100] 200 loss = 20.779121 [took 50.716 s]
[lr=0.0005 clips=100 updates=100] 300 loss = 17.716823 [took 46.031 s]
[lr=0.0005 clips=99 updates=100] 400 loss = 18.769036 [took 41.463 s]
[lr=0.0005 clips=100 updates=100] 500 loss = 18.951144 [took 49.424 s]
[lr=0.0005 clips=100 updates=100] 600 loss = 20.763794 [took 51.008 s]
[lr=0.0005 clips=100 updates=100] 700 loss = 17.897359 [took 45.175 s]
[lr=0.0005 clips=100 updates=100] 800 loss = 17.369590 [took 42.235 s]
[lr=0.0005 clips=98 updates=100] 900 loss = 16.837128 [took 49.753 s]
[lr=0.0005 clips=100 updates=100] 1000 loss = 17.795842 [took 51.235 s]
[dev epoch=0 after=1001] wprec = 0.00000 wrec = 0.00000 wf1 = 0.00000
[dev epoch=0 after=1001] uprec = 0.00000 urec = 0.00000 uf1 = 0.00000
[dev epoch=0 after=1001] lprec = 0.00000 lrec = 0.00000 lf1 = 0.00000 [took 621.073 s]
[lr=0.0005 clips=100 updates=100] 1100 loss = 16.862659 [took 50.687 s]
[lr=0.0005 clips=100 updates=100] 1200 loss = 14.759756 [took 40.827 s]
[lr=0.0005 clips=100 updates=100] 1300 loss = 14.575772 [took 39.446 s]
[lr=0.0005 clips=100 updates=100] 1400 loss = 14.491017 [took 42.966 s]
[lr=0.0005 clips=100 updates=100] 1500 loss = 15.175744 [took 55.345 s]
[lr=0.0005 clips=100 updates=100] 1600 loss = 14.648142 [took 42.464 s]
[lr=0.0005 clips=100 updates=100] 1700 loss = 13.749653 [took 50.359 s]
[lr=0.0005 clips=100 updates=100] 1800 loss = 13.874129 [took 46.874 s]
[lr=0.0005 clips=100 updates=100] 1900 loss = 14.471691 [took 42.907 s]
[lr=0.0005 clips=100 updates=100] 2000 loss = 13.668519 [took 49.962 s]
[dev epoch=0 after=2001] wprec = 0.41848 wrec = 0.06883 wf1 = 0.11822
[dev epoch=0 after=2001] uprec = 0.55100 urec = 0.18472 uf1 = 0.27668
[dev epoch=0 after=2001] lprec = 0.40382 lrec = 0.14518 lf1 = 0.21358 -- savinglibc++abi.dylib: terminating with uncaught exception of type std::runtime_error: Could not write model to tmp/1.7model.sra-1527520332.05
[1] 54727 abort python segrnn-argid.py
I have this line in globalconfig.py:20
VERSION="1.7"
and I'm working with fn1.7 data. I ran the preprocess steps.Now I'm trying to run the training with this command:
python segrnn-argid.py
I'm getting this error:
The error goes away if I replace
FILTERED_WVECS_FILE = DATADIR + "glove.6B.100d.framenet.txt"
withFILTERED_WVECS_FILE = DATADIR + "glove.6B.100d.txt"
in globalconfig.py:85.Now the training starts without errors (
python segrnn-argid.py
).But after about 40min of training, I get this new error:
This looks like a low-level error inside dynet. I cannot find what is causing it with google/stackoverflow. I installed dynet with
pip install dynet
. I'm running OSX High Sierra and python 2.7.10 inside a virtualenv. I ran the training twice with both times the same error (and a different tmp file name in each case) The error doesn't look related to my fix in globalconfig.py:85. Any pointers?Full output of the training: