Data Science

These examples take quite a long time to run, and they make our documentation CI fail quite frequently due to timeout. It'd be nice to speed the up a little bit.

To contributors: if you want to work on an example, first have a look at the example, and if you think you're comfortable working on it and have found a potential way to speed-up execution time while preserving the educational message

A clear and concise description of what the bug is.
The superset chart table sets the number of pagination rows to select the setting, and add the option of whether to select all

like this
![image](https://user-images.githubusercontent.com/52438024/141405677-f9e25aef-e0d3-4e99-986a

Search before asking

• I had searched in the issues and found no similar feature requirement.

Description

We have introduced detached flag to indicate the lifetime of the actor in Python as following.

counter = Counter.options(name="CounterActor", lifetime="detached").remote()

But we have not introduced it for J

Summary

Aesthetically trivial, yet I've spotted a discrepancy with font sizes in our tooltip (front-end + back-end screenshots below).
I believe sections #1 and #2 should have the same font size?

![image](https://user-images.githubusercontent.com/27242399/139825179-4d62e3

Proposed refactoring or deprecation

Motivation

Lightning has a utility defined for all gather with gradients here: https://github.com/PyTorchLightning/pytorch-lightning/blob/d515bcac969c2a485ada673e302bfac51f142331/pytorch_lightning/utilities/distributed.py#L200-L222

However, this is already available in torch dist

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

For regular lists:

In [11]: list(range(50))
Out[11]: 
[0,
 1,
 2,
 3,
 4,
...
 46,
 47,
 48,
 49]

However:

In [13]: collections.UserList(range(50))
Out[13]: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49]

Bug summary

The ax.invertxaxis() and ax.invert_yaxis() function both produce the same output, a scatterplot with a flipped X axis.

Code for reproduction

from mpl_toolkits import mplot3d
import matplotlib.pyplot as plt

ax = plt.axes(projection='3d')
plt.title("Invert Z")
ax.scatter3D(1,1,1)
# ax.invert_xaxis()
ax.invert_yaxis()
# ax.invert_zaxis()

Actual o

In gensim/models/fasttext.py:

    model = FastText(
        vector_size=m.dim,
        vector_size=m.dim,
        window=m.ws,
        window=m.ws,
        epochs=m.epoch,
        epochs=m.epoch,
        negative=m.neg,
        negative=m.neg,
        # FIXME: these next 2 lines read in unsupported FB FT modes (loss=3 softmax or loss=4 onevsall,
        # or model=3 supervi

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.