I tried “word” and “char”, it works. But when I tried semantic word hashing with:
analyzer=char_wb
It always reports the following error:
File “/rasa/nlu/classifiers/embedding_intent_classifier.py”, line 565, in train
self._train_tf(X, Y, intents_for_X, loss, is_training, train_op)
File “/rasa/nlu/classifiers/embedding_intent_classifier.py”, line 458, in _train_tf
is_training: True,
File “/lib/python3.7/site-packages/tensorflow/python/client/session.py”, line 929, in run
run_metadata_ptr)
File “/lib/python3.7/site-packages/tensorflow/python/client/session.py”, line 1128, in _run
str(subfeed_t.get_shape())))
ValueError: Cannot feed value of shape (64,) for Tensor ‘a:0’, which has shape ‘(?, 15449)’
@twittmin I am assuming you are on the master branch currently. Looks like the some of the data points didn’t get featurized correctly by countVectorizer. Line 242 on file count_vectors_featurizer.py basically computes the text_features for all data points of your training which are consumed by EmbeddingIntentClassifier. Could you check the length of the second dimension of X and see if it’s consistent for all datapoints. If not, there is something wrong with the text of those data points.