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AIPHES / emnlp19-moverscore

MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance
MIT License
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argument 'tensors' (position 1) must be tuple of Tensors, not str #23

Open Crista23 opened 2 years ago

Crista23 commented 2 years ago

How to fix the error below? Thank you!

$ python3 example.py Traceback (most recent call last): File "example.py", line 79, in test_sentence_score() File "example.py", line 72, in test_sentence_score mover = sentence_score(sys, refs) File "example.py", line 23, in sentence_score scores = word_mover_score(references, hypothesis, idf_dict_ref, idf_dict_hyp, stop_words=[], n_gram=1, remove_subwords=False) File "/usr/lib/python3.7/site-packages/moverscore_v2.py", line 128, in word_mover_score device=device) File "/usr/lib/python3.7/site-packages/moverscore_v2.py", line 100, in get_bert_embedding batch_embedding = torch.stack(batch_embedding) TypeError: stack(): argument 'tensors' (position 1) must be tuple of Tensors, not str

vejvarm commented 1 year ago

Had the same problem due to PyPI version of moverscore being outdated,

Please try installing moverscore from the git repo as refered in this solution.

jsl5710 commented 3 weeks ago

I am having the same error and installing moverscore from the git repo as referred in this https://github.com/AIPHES/emnlp19-moverscore/issues/22#issuecomment-1049560990 did not work. Can someone please help?

from moverscore_v2 import get_idf_dict, word_mover_score from collections import defaultdict

Define your texts here

references = ["The quick brown fox jumps over the lazy dog.", "A stitch in time saves nine."] translations = ["The speedy brown fox leaps over the lazy dog.", "A stitch at the right time saves nine."]

Get IDF dictionaries

idf_dict_hyp = get_idf_dict(translations) # Using default if not specified idf_dict_ref = get_idf_dict(references) # Using default if not specified

Calculate MoverScore

try: scores = word_mover_score(references, translations, idf_dict_ref, idf_dict_hyp, stop_words=[], n_gram=1, remove_subwords=True) print("Scores:", scores) except Exception as e: print("Error during scoring:", str(e))