Data Science

Describe the issue linked to the documentation

Link the site https://scikit-learn.org/scikit-learn-benchmarks/ and https://github.com/scikit-learn/scikit-learn-benchmarks in the homepage https://scikit-learn.org.

Follow-up on #17026

Screenshot

I've added a red vertical ruler so that you see the issue

Description

As already explained in numerous issues, the use of 'Inter' font is problematic, it does not allow to align dates for instance,
and does not play nice with numbers either.

In my supe

Problem

When checkpointing a Torch model's state_dict, there may be some inconsistencies when saving/loading depending on whether the model is wrapped in DDP.

Proposal

Provide a utility method that always fetches the non-DDP version of the state_dict.

Without DDP:

model.state_dict()

With DDP:

model.module.state_dict()

Also see

[torch.nn.modu

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 refactor

Deprecate tpu_global_core_rank in favor of global_rank.

Pitch

It "looks" like tpu_global_core_rank in the TPUPlugin is just another name for what is known as the global rank. After #10896 we should investigate whether the two are equivalent and revert back to using the unified global_rank property exclusively.

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

It's been unused and deprecated for years.

1. It should emit a warning when parameter is passed in.
2. the deprecation should say since when it's deprecated.

Once this is done, we can think of removing it in a couple of years.

As discussed in #21874, there aren't reprs on the locators and formatters. Reprs of the form where eval(repr) = call, something like

eval('AutoDateLocator(maxticks=8)') = AutoDateLocator(maxticks)

would mean reprs could be used in the documentation examples, which would help keep the labels in sync. This is useful for the new example #21874 &

• https://matplotlib.org/devdocs/g

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.