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

Something kind of neat I was reading the other day

https://rigtorp.se/iife/

the tl;dr is that using some compiler attributes and immediately invoked lambdas we can decrease the size of the error functions, and since those error paths take up less space it can allow for better inlining. This is also nice because we don't really care about performance when a function errors s

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.

Just added to SpecialFunctions.jl: JuliaMath/SpecialFunctions.jl#236

The derivative with respect to x is a simple recurrence: https://en.wikipedia.org/wiki/Exponential_integral#Derivatives