Is your feature request related to a problem? Please describe.
There are parts of the website that can use improvements in increasing the accessibility of the website.

**Describe the solution you

GTest exports the following targets:

• GTest::gtest
• GTest::gtest_main
• GTest::gmock
• GTest::gmock_main

This targets should also be available when adding gtest with add_subdirectory (or FetchContent), because this should behave the same way as adding GTest with find_package. So somewhere, we should add the aliases to these targets, i.e.

add_library(GTest::gtest ALIAS 

Triggered by #1072

psf/black's 88 chars per line is more modern than PEP8's meager 79.
A personal favorite is 127 which allows reading code on GitHub's file viewer without requiring left/right scrolling.

To get us down to flake8 linting having a max line length of 127, I believe we only need to change ~17 lines. This would enable the codebase to be much more readable in side by side ed

❯ rg keras
machine_learning/lstm/lstm_prediction.py_tf
9:from keras.layers import LSTM, Dense
10:from keras.models import Sequential

And thus, removing the keras dependency from requirements.txt.

Ref:

• https://github.com/keras-team/keras#under-construction
• https://keras.io/guides/functional_api/#setup

What example does this report relate to?

with-Apollo

What version of Next.js are you using?

10.0.0

What version of Node.js are you using?

10.14.2

What browser are you using?

chrome

What operating system are you using?

macOS

How are you deploying your application?

Other platform

Describe the Bug

The Apollo client query response is s

Description

Apparently FSWatchUtil starts an Executor, but the threads this is spawning have name patterns like pool-406-thread-1.

It would be highly preferreable for all of our components to specify a good name for threads which are being started, to help with diagnostics.

New Operator

Describe the operator

Why is this operator necessary? What does it accomplish?

This is a frequently used operator in tensorflow/keras

Can this operator be constructed using existing onnx operators?

If so, why not add it as a function?

I don't know.

Is this operator used by any model currently? Which one?

Are you willing to contribute it?

Hi there, thanks for your work :)

Is there a way to export a comprehensive file/report of the metrics showed in the Fairness Dashboard? Or a line of code through Fairlearn.Metrics to do so?

Many thanks