In operations_broadcast_test.go there are some tests that are not yet filled in. The point is to test that broadcasting works for different shapes. The semantics of broadcast probably isn't clear, so please do send me a message for anything.

This is a good first issue for anyone looking to get interested

I'm using TF 2.0, and I get this error when I import tangent, due to a list of non-differentiable functions that includes tf.to_float (line 60), which is deprecated:

https://www.tensorflow.org/versions/r1.14/api_docs/python/tf/to_float

I found that function mod2pi is not implemented yet, but mod works. Is there any list of implemented functions? Minimal working example is:

using Zygote

# This is working
gradient(x -> mod(x, 2pi), 1.)

# This is not
gradient(x -> mod2pi(x), 1.)

Description

We should have inv_tri_low(x) = inverse(x) for x a lower triangular matrix.

It's for more efficiency and simpler derivatives.

Current Version:

v3.2.0

At the moment profiles.h (in pkg/profiles) lacks many (any?) comments. Also lots of variables are declared somewhat separately from where they are associated with heap storage.

Both these make it a bit hard to read.

It would be nicer if it was called PROFILES.h too.

Lots has changed since the docs were first written. #152 addresses a number of things, but there are a few more things that we might want to consider:

• changing all references to autodiff / automatic differentiation to AD / algorithmic differentiation, with a terminology box in the docs somewhere, explaining what we're on about.
• In the "On writing good rrule and frule " bit, we should consi