(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

BigQuery error is hard to read.

Expected results

In Explore, when creating a bad expression (say DATE_TRUNC(column_that_dont_exist, DAY)) in BigQuery, the DatabaseError is shown as a UnknownError. In SQL Lab, DatabaseErrors are surfaced properly and make sure to use a monospace font so that the formatting is preserved. For most database, the formatting doesn't matter much, but for BigQ

This is the comment as mentioned here https://github.com/ray-project/ray/pull/14122/files#diff-10f3fda5ddb0ff3dbb8f347dd7fc53101d2dd140585e72f2d55be831bd5455dbR134

What is the problem?

In most cases, a client object's lifetime matches its ID, but this isn't so with named actors. Performance can be improved by reverting this call to non-blocking.

Reproduction outline

Here's how na

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

Any logic to compare different DistributedTypes should be encapsulated by the enum itself.

Motivation

• PyTorchLightning/pytorch-lightning#5743 (comment)
• PyTorchLightning/pytorch-lightning#5743 (comment)
• [#5970] PyTorchLightning/pytorch-lightning#5970 (comment)

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)

Unfortunately, I can't find any examples of what it "does" do, but it appears to take a file that is NOT in json format, but has a complete json representation on every single line of the file, with two keys: "text" and "label".

The code showing that is in its _read method:
....
def _read(self, file_path):
with open(cached_path(file_path), "r") as data_file:
for line in

I'm using mxnet to do some work, but there is nothing when I search the mxnet trial and example.

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 `

The expressions editor window includes a Help tab that has some plain-text information about each variable and function.

I am editing this text right now to match the user manual. I'd like the fields to render with links (they currently just have full URLS that users can copy-pa