snakeztc / NeuralDialog-CVAE

Hi,

What modifications in the code are needed to train on a dataset without dialogue acts, metadata, and features?

Ok so I found out that I need to change:

in corpus.py:

dialog = [(bod_utt, 0, None)] + [(utt, int(caller=="B"), feat) for caller, utt, feat in lower_utts]
to:
dialog = [(bod_utt, 0, None)] + [(utt, int(caller=="B"), None) for caller, utt, feat in lower_utts]

And in config_utils.py:
use_hcf = False

But I'm getting this error:

Traceback (most recent call last):
  File "kgcvae_swda.py", line 165, in <module>
    main()
  File "kgcvae_swda.py", line 68, in main
    model = KgRnnCVAE(sess, config, api, log_dir=None if FLAGS.forward_only else log_dir, forward=False, scope=scope)
  File "/Users/ruby/Downloads/NeuralDialog-CVAE-master/models/cvae.py", line 301, in __init__
    loop_func = decoder_fn_lib.context_decoder_fn_train(dec_init_state, selected_attribute_embedding)
UnboundLocalError: local variable 'selected_attribute_embedding' referenced before assignment

As the error says, the variable selected_attribute_embedding has no value since it seems like only when use_hcf = True you initialize it.

NeuralDialog-CVAE/models/cvae.py

Line 301 in 9d1b63e

    
           loop_func = decoder_fn_lib.context_decoder_fn_train(dec_init_state, selected_attribute_embedding)

Can you please specify what code changes needs to be?

Also, if there need to be other code changes (maybe in testing/decoding), what are they?

Thanks. We will be looking into this.

Can you please help me with this?
I really want to try your model, but I couldn't solve this on my own.

@dimeldo thanks for the interest. Currently, we are in a very busy month. We will look the issue after this.

Okay, so I was able to train successfully without dialogue acts. But I think still some other metadata was included like topics. In the code above I replaced selected_attribute_embedding with None, I figured it's related to dialogue acts embedding. I also commented all the parts related to da.

And it seems to work well, but I will still prefer an official implementation from you. It will be great if you can implement the option so it will work using the flag use_hcf and/or maybe additional flags indicating the un/use of other types of metadata, so we could try the CVAE model on other types of data.

@dimeldo Thanks! I just fixed the bug of selected_attribute_embedding is undefined

What modifications needed to train dataset without dialogue acts, metadata and features and floor?