differentiable-programming

The current Field APIs, including ScalarField, MatrixField, and Structfield (after #2627) use assertions statements to check input validity, for example,

https://github.com/taichi-dev/taichi/blob/03e2923d103704048c101051d337fa31f9dbb1de/python/taichi/lang/matrix.py#L207

In software engineering practice, assertion is used to verify whether the program itself is implemented correctly regardles

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.

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

What would you think of moving the current examples to Literate ?