C3W2 Error running

[Joseph_Porrovecchio]

The provided function def standardize_func(sentence):“Removes a list of stopwords” does not remove all stop_words.

Runing the Unit test"unittests.test_fit_vectorizer(fit_vectorizer, standardize_func)" produces:

Error: Failed test case: Found stopwords in the vocabulary.

Any help appreciated "
…

[Alireza_Saei]

Hi @Joseph_Porrovecchio

Make sure to apply the standardize_func to all of your sentences. Also, ensure that the stopwords list and replacement action in your function are correct.

Hope it helps! Feel free to ask if you need further assistance.

[Joseph_Porrovecchio]

Thank you Alirez,

I call the ‘standardize_func’ in from vectorizer.adapt(train_sentences, standardize_func) . Also, The result for test_sentence call to standardized_sentence = standardize_func(test_sentence) does not seem correct?

[Deepti_Prasad]

@Joseph_Porrovecchio

‘standardize_func’ in from vectorizer.adapt(train_sentences, standardize_func

you are using standardize_func at the wrong place, this need to be recalled where we instantiate the tokenizer class.

See the below thread for more detail

C3W2_Assignment - fit_vectorizer

Now addressing to your code issue, I don’t know if you have referred the ungraded lab which tells you to use the same tf.keras.layers.TextVectorization as these codes were already given at the beginning of the codes. Now comes to adding other parameters to this Tokenizer class as per instruction, instruction mentions you to use vocab_size and assign tells you to use standardise_func, vocab_size and runcate the output sequences to have MAX_LENGTH length. Also not to forget emember to use the c…

Regards
DP

[Joseph_Porrovecchio]

Thank you DP!

Moved standardize_func and that solved it!