Warning for stopwordremover
hiiamsid opened this issue · 6 comments
I was trying to remove stopword for the nlu data. And followed pipeline mentioned on the docs. But got following warning.
UserWarning: You have provided an invalid key `path` for component `rasa_nlu_examples.meta.StopWordRemover` in your pipeline. Valid options for `rasa_nlu_examples.meta.StopWordRemover` are:
- alias
And going through documentation i found that rasa_nlu_examples.meta.Printer has alias component and rasa_nlu_examples.meta.StopWordRemover has path component. Can you please check this?
Could you share your config.yml file as well? Without it, it's fairly hard to debug.
I would want to warn you though, this repo is currently being transitioned to Rasa 3.0.
I did just make an update to https://github.com/RasaHQ/rasa-nlu-examples/blob/main/rasa_nlu_examples/meta/stopwordremover.py. I just added path
as a default.
# Configuration for Rasa NLU.
# https://rasa.com/docs/rasa/nlu/components/
language: hi
pipeline:
# # No configuration for the NLU pipeline was provided. The following default pipeline was used to train your model.
# # If you'd like to customize it, uncomment and adjust the pipeline.
# # See https://rasa.com/docs/rasa/tuning-your-model for more information.
- name: rasa_nlu_examples.meta.StopWordRemover
path: /content/drive/MyDrive/small_chatbot/embed/stopword.txt
- name: WhitespaceTokenizer
- name: RegexFeaturizer
number_additional_patterns: 10
- name: LexicalSyntacticFeaturizer
- name: rasa_nlu_examples.featurizers.dense.GensimFeaturizer
cache_dir: /content/drive/MyDrive/small_chatbot/embed
file: small_dataset_word2vec
- name: CountVectorsFeaturizer
- name: CountVectorsFeaturizer
analyzer: char_wb
min_ngram: 1
max_ngram: 5
- name: CountVectorsFeaturizer
analyzer: char_wb
min_ngram: 1
max_ngram: 3
- name: rasa_nlu_examples.featurizers.dense.FastTextFeaturizer
cache_dir: /content/drive/MyDrive/small_chatbot/embed
file: small_fasttext.bin
- name: DIETClassifier
random_seed: 42
epochs: 1000
embedding_dimension: 30
batch_size: 64
drop_rate: 0.25
learning_rate: 0.0001
# - name: EntitySynonymMapper
# - name: ResponseSelector
# epochs: 100
# - name: FallbackClassifier
# threshold: 0.3
# ambiguity_threshold: 0.1
# Configuration for Rasa Core.
# https://rasa.com/docs/rasa/core/policies/
policies:
# # No configuration for policies was provided. The following default policies were used to train your model.
# # If you'd like to customize them, uncomment and adjust the policies.
# # See https://rasa.com/docs/rasa/policies for more information.
- name: MemoizationPolicy
- name: TEDPolicy
max_history: 5
epochs: 100
- name: RulePolicy
@hiiamsid can you confirm that you've installed the latest version from GitHub? Also, could you share the full traceback?
Closing due to radio silence.