tensor

Motivation

Currently lots of C++ based unit tests are executed directly from test.sh/win-test.sh for example:
https://github.com/pytorch/pytorch/blob/0bd8d0951dcb4063c0f7552a7404bd7f0e7b6e6f/.jenkins/pytorch/test.sh#L317

Which have following drawbacks:

• It excluded those test runtime from auto-sharding/auto-categorization
• Make them subject of running on only particular platform (

Support Series.median()

Hey Contributor!

Thanks for checking out HyperLearn!! Super appreciate it.

Since the package is new (only started like August 27th)..., Issues are the best place to start helping out, and or check out the Projects tab. There's a whole list of stuff I envisioned to complete.

Also, if you have a NEW idea: please post an issue and label it new enhancement.

In terms of priorities, I wanted

Tests for following standard libraries seem to be missing. Although some libraries might be difficult to test (such as random.egi or io.egi), it'd be nice to have some tests that make sure all the functions in these libraries can be (at least) executed without dynamic errors.

• lib/core/io.egi
• lib/core/random.egi
• lib/core/shell.egi
• lib/core/sort.egi
• Every

Add a function and module that permits spike-time decoding, as suggested by @schmitts https://twitter.com/sbstnschmtthd/status/1432343373072019461