🚀 Feature request

At the moment we cannot return a list of attention weight outputs in Flax as we can do in PyTorch.

In PyTorch, there is a output_attentions boolean in the forward call of every function, see here which when set to True collects

Refer to doc2vec.py, infer_vector function seems to be using epochs for the number of iterations and steps is not in used.

However, in the similarity_unseen_docs function, steps is used when calling the infer_vector function.

Is your feature request related to a problem? Please describe.
I typically used compressed datasets (e.g. gzipped) to save disk space. This works fine with AllenNLP during training because I can write my dataset reader to load the compressed data. However, the predict command opens the file and reads lines for the Predictor. This fails when it tries to load data from my compressed files.

Hi
Wikiann dataset needs to have "spans" columns, which is necessary to be able to use this dataset, but this column is missing from huggingface datasets, could you please have a look? thank you @lhoestq

Hi I would like to propose a better implementation for 'test_indices':

We can remove the unneeded np.array casting:

Cleaner/New:
test_indices = list(set(range(len(texts))) - set(train_indices))

Old:
test_indices = np.array(list(set(range(len(texts))) - set(train_indices)))