differentiable-programming

There comes one special case which requires a reverse loop, so I used “ti.ndrange(8,0)” instead. However, the reverse loop just didn’t work with zero warnings or errors (I have no idea whether ti.ndrange can be used to loop in reverse order at that time)
Perhaps a warning message can be given when n1 > n2 in ti.ndrange((n1,n2))

import taichi as ti
ti.init(arch=ti.gpu, debug=True, de

When installing the S4TF toolchain, it's not always clear whether all components are intact and versions are compatible. It would be helpful to have a quick verification tool that uses the toolchain and reports success.

This is especially useful for installations involving accelerators, so the first two features could be:

• Can invoke the toolchain and import TensorFlow
• Can run on

Ankit Shah and I are trying to use Gen to support a project and would love the addition of a dirichlet distribution

Model summary formatting is rudimentary and could be improved so that tabs align. Potentially use some ideas from swift-benchmark.

Generate code coverage reports for our tests.

Debugging Kotlin∇ code within IntelliJ IDEA can be somewhat cumbersome due to the functional API structure (lots of deeply-nested stack traces and context switching). To facilitate more user-friendly debugging, we should add support for visual debugging by exposing Kaliningraph’s built-in graph visualization capabilities. For example, the use

For the reverse CI it would be good to use a multi-threaded testsuite (x-ref EnzymeAD/Enzyme#531)

I think https://github.com/RelationalAI-oss/XUnit.jl is the only alternative to Test that supports this.

Instead, we could error in forward and backward.