Error during decoding

[neubig]

Hi,

I ran a super-small experiment training on the dev set from the example Japanese data (see xnmt-small.yaml in mcds-exp.zip) and got the following error. It looks like this might be because search_strategy is outputting NumPy arrays instead of integers at each timestep. Is anyone else getting this problem?

[dynet] random seed: 852191151
[dynet] allocating memory: 512MB
[dynet] memory allocation done.
=> Running ja_check
   > Training   
   Start training in minibatch mode...   
   Epoch 1.0000: train_ppl=372.9873 (words=5057, time=0-00:00:01)   
   Epoch 1.0000: test_ppl=220.3990 (words=5057, time=0-00:00:02)   
   Epoch 1.0000: best dev loss, writing model to xnmtmodel/dev.mod   
   > Evaluating   
   Traceback (most recent call last):
     File "/home/gneubig/work/xnmt/xnmt/xnmt_run_experiments.py", line 123, in <module>
          xnmt_trainer.input_reader.vocab, xnmt_trainer.output_reader.vocab, xnmt_trainer.translator))
     File "/usr0/home/gneubig/work/xnmt/xnmt/xnmt_decode.py", line 52, in xnmt_decode
          target_sentence = output_generator.process(token_string)[0]
     File "/usr0/home/gneubig/work/xnmt/xnmt/output.py", line 32, in process
          self.token_string.append(self.vocab[token])
     File "/usr0/home/gneubig/work/xnmt/xnmt/vocab.py", line 35, in __getitem__
          return self.i2w[i]
   TypeError   :    only integer scalar arrays can be converted to a scalar index   

[psjanani]

Hello sir,
I re-ran with the configurations provided by you on Python 2 and got the following output.

Training
Start training in minibatch mode...
Epoch 1.0000: train_ppl=370.9497 (words=5057, time=0-00:00:01)
Epoch 1.0000: test_ppl=249.1718 (words=5057, time=0-00:00:01)
Epoch 1.0000: best dev loss, writing model to /tmp/dev.mod
Evaluating
bleu: 0.0883409765451
wer: 0.903624733475
Epoch 2.0000: train_ppl=213.6305 (words=5057, time=0-00:00:05)
Epoch 2.0000: test_ppl=208.2777 (words=5057, time=0-00:00:05)
Epoch 2.0000: best dev loss, writing model to /tmp/dev.mod"

[psjanani]

The current idea is the following:
search_strategy returns the entire list of words (translated sentence) for a source sentence, which is sent to output for processing as a batch (array of array). The token iterator accesses the token ids in the batch. As you pointed out, the above error indicates the case of another dimension being added. But I am unable to reproduce it. Which version of Python is it? I haven't tested the pipeline on Python 3 yet. This was run on the current master branch.

[psjanani]

Hi,
This might be due to the change in a recent version of Numpy.
It apparently treats a single-element array as a scalar for the purposes of indexing. That would work against the above idea.
stack overflow
Can you please provide the version of Numpy you are using?

[neubig]

Thanks for looking at this so quickly! Here is my info, it's the standard one I got from Anaconda, although the version of anaconda may be old...

(python2) gneubig@lor:~$ python
Python 2.7.13 |Continuum Analytics, Inc.| (default, Dec 19 2016, 13:46:45) 
[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
Anaconda is brought to you by Continuum Analytics.
Please check out: http://continuum.io/thanks and https://anaconda.org
>>> import numpy as np
>>> print np.__version__
1.12.1

[psjanani]

@neubig, The error was being caused due to a change in output dimensions returned by concatenate function of the latest dynet. The latest version adds another dimension to the output. We reshape the output now.