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textsum:AssertionError: Empty filelist. #370
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I have tried the same on $ lsb_release -a
No LSB modules are available.
Distributor ID: Ubuntu
Description: Ubuntu 14.04.4 LTS
Release: 14.04
Codename: trusty My dir structure is ubuntu@ip-10-169-182-86:~/tensorflow/lyrics$ ls -R
.:
bazel-bin bazel-genfiles bazel-lyrics bazel-out bazel-testlogs data textsum WORKSPACE
./data:
data vocab
./textsum:
batch_reader.py beam_search.py BUILD data.py README.md seq2seq_attention_decode.pyc seq2seq_attention_model.pyc seq2seq_lib.py
batch_reader.pyc beam_search.pyc data data.pyc seq2seq_attention_decode.py seq2seq_attention_model.py seq2seq_attention.py seq2seq_lib.pyc
./textsum/data:
data vocab I do not have any
So I assume that was the source of this issue. Command was $ bazel-bin/textsum/seq2seq_attention --mode=train --article_key=article --abstract_key=abstract --data_path=data/training-* --vocab_path=data/vocab --log_root=textsum/log_root --train_dir=textsum/log_root/train |
@loretoparisi you need to give it the correct path to your data. You're telling it to look for data/training-* but you don't have anything that matches that. It looks like you need to use |
Yes thanks @jamcar23, the issue is the toy data provided is data/data. We don't provide the full training data in the repo. |
@peterjliu ok thanks, where we get the training data then? |
@panyx0718 @peterjliu considering the fact that this data is not free and apparently there's no other data in this format, would it make sense to use the command below in order to train?
What are other tricks to get data in the data folder? |
Please let us know which model this issue is about (specify the top-level directory)
textsum
I get this error while doing the training
I have my
data
andvocab
and theWORKSPACE
in the same dir:(tensorflow) admin@macbookproloreto:~/Developmemt/ParisiLabs/ML/models/data$ ls -l total 320 -rw-r--r-- 1 admin staff 33582 30 Ago 17:45 data -rw-r--r-- 1 admin staff 124934 30 Ago 17:45 vocab
The command launched was
$ bazel-bin/textsum/seq2seq_attention --mode=train --article_key=article --abstract_key=abstract --data_path=data/training-* --vocab_path=data/vocab --log_root=textsum/log_root --train_dir=textsum/log_root/train
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