ValueError: Cannot concatenate sparse features as sequence dimension does not match

[tabergma]

Rasa version: 1.7.0
Python version: 3.6

Issue:
Training with rasa train nlu using intent and responses does not work. Removing the responses from the training data, solves the issue.

https://forum.rasa.com/t/valueerror-sequence-dimensions-for-sparse-and-dense-features-dont-coincide/22844

Error (including full traceback):

Traceback (most recent call last):
  File "c:\users\saurabhd\appdata\local\programs\python\python36\lib\runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "c:\users\saurabhd\appdata\local\programs\python\python36\lib\runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "C:\Users\saurabhd\AppData\Local\Programs\Python\Python36\Scripts\rasa.exe\__main__.py", line 7, in <module>
  File "c:\users\saurabhd\appdata\local\programs\python\python36\lib\site-packages\rasa\__main__.py", line 76, in main
    cmdline_arguments.func(cmdline_arguments)
  File "c:\users\saurabhd\appdata\local\programs\python\python36\lib\site-packages\rasa\cli\train.py", line 76, in train
    kwargs=extract_additional_arguments(args),
  File "c:\users\saurabhd\appdata\local\programs\python\python36\lib\site-packages\rasa\train.py", line 46, in train
    kwargs=kwargs,
  File "c:\users\saurabhd\appdata\local\programs\python\python36\lib\asyncio\base_events.py", line 484, in run_until_complete
    return future.result()
  File "c:\users\saurabhd\appdata\local\programs\python\python36\lib\site-packages\rasa\train.py", line 97, in train_async
    kwargs,
  File "c:\users\saurabhd\appdata\local\programs\python\python36\lib\site-packages\rasa\train.py", line 184, in _train_async_internal
    kwargs=kwargs,
  File "c:\users\saurabhd\appdata\local\programs\python\python36\lib\site-packages\rasa\train.py", line 241, in _do_training
    persist_nlu_training_data=persist_nlu_training_data,
  File "c:\users\saurabhd\appdata\local\programs\python\python36\lib\site-packages\rasa\train.py", line 470, in _train_nlu_with_validated_data
    persist_nlu_training_data=persist_nlu_training_data,
  File "c:\users\saurabhd\appdata\local\programs\python\python36\lib\site-packages\rasa\nlu\train.py", line 86, in train
    interpreter = trainer.train(training_data, **kwargs)
  File "c:\users\saurabhd\appdata\local\programs\python\python36\lib\site-packages\rasa\nlu\model.py", line 191, in train
    updates = component.train(working_data, self.config, **context)
  File "c:\users\saurabhd\appdata\local\programs\python\python36\lib\site-packages\rasa\nlu\featurizers\sparse_featurizer\regex_featurizer.py", line 67, in train
    self._text_features_with_regex(example, attribute)
  File "c:\users\saurabhd\appdata\local\programs\python\python36\lib\site-packages\rasa\nlu\featurizers\sparse_featurizer\regex_featurizer.py", line 76, in _text_features_with_regex
    message, extras, feature_name=SPARSE_FEATURE_NAMES[attribute]
  File "c:\users\saurabhd\appdata\local\programs\python\python36\lib\site-packages\rasa\nlu\featurizers\featurizer.py", line 67, in _combine_with_existing_sparse_features
    f"Cannot concatenate sparse features as sequence dimension does not "
ValueError: Cannot concatenate sparse features as sequence dimension does not match: 7 != 1. Make sure to set 'return_sequence' to the same value for all your featurizers.

Command or request that led to error:

rasa train nlu