(e.g. for links and images), because some of these examples are now being rendered in the docs.

Added by @fchollet in requests for contributions.

Most functions in scipy.linalg functions (e.g. svd, qr, eig, eigh, pinv, pinv2 ...) have a default kwarg check_finite=True that we typically leave to the default value in scikit-learn.

As we already validate the input data for most estimators in scikit-learn, this check is redundant and can cause significant overhead, especially at predict / transform time. We should probably a

Currently, after user editing a metric in Edit dataset modal in Explore, the edited metric jump to the bottom of the metric list.
it create a few issues:

1. when the metric list is long, by dropping to the bottom, user might take a while to find it or think the most recent edited metic is lost.
2. every time users edit a single metric, they see a different order of metric list showing in the

Describe your feature request

Hi guys,

It would be awesome to add API that has same output as ray memory command.
Also, it would be good to add some additional output info for ray.objects(). For example, node IP, IDs of objects which are created in in-process stores, IDs of objects from remote calls (when remote calls are still being executed).

Thanks in advance!

Travis is not going to automatically offer the free tier for all open source projects; We likely want o migrate away from travis.

Setting up github actions to replace travis would be a welcomed contribution.

In recent versions (can't say from exactly when), there seems to be an off-by-one error in dcc.DatePickerRange. I set max_date_allowed = datetime.today().date(), but in the calendar, yesterday is the maximum date allowed. I see it in my apps, and it is also present in the first example on the DatePickerRange documentation page.

E

Summary

When a function has print('sth', file=sys.stderr) in the body I get:

InternalHashError: [Errno 2] No such file or directory: '<stderr>'

While caching the body of eval_models_on_all_data(), Streamlit encountered an object of type _io.TextIOWrapper, which it does not know how to hash.

Steps to reproduce

Code snippet:

@st.cache
def f():
   prin

🚀 Feature

See title

https://github.com/PyTorchLightning/pytorch-lightning/blob/9137b16068fe03e6db8df548235363e5f5476aac/pytorch_lightning/trainer/connectors/logger_connector/epoch_result_store.py#L25-L42

Motivation

No longer used after #5579

Pitch

Proper deprecation process

Not a high-priority at all, but it'd be more sensible for such a tutorial/testing utility corpus to be implemented elsewhere - maybe under /test/ or some other data- or doc- related module – rather than in gensim.models.word2vec.

Originally posted by @gojomo in RaRe-Technologies/gensim#2939 (comment)

more details at: allenai/allennlp#2264 (comment)

What would you like to be added: As title

Why is this needed: All pruning schedule except AGPPruner only support level, L1, L2. While there are FPGM, APoZ, MeanActivation and Taylor, it would be much better if we can choose any pruner with any pruning schedule.

**Without this feature, how does current nni

Current pytorch implementation ignores the argument split_f in the function train_batch_ch13 as shown below.

def train_batch_ch13(net, X, y, loss, trainer, devices):
    if isinstance(X, list):
        # Required for BERT Fine-tuning (to be covered later)
        X = [x.to(devices[0]) for x in X]
    else:
        X = X.to(devices[0])
...

Todo: Define the argument `

Test the Column / Text filter

Proposed solution

Add a test for the behavior with

• an exact string, check the number of occurrences
• a partial string, also check the number of occurrences
• Test case sensitive
• Test a regular expression