automatic-differentiation

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

Feature details

The qml.kernels.utils.py file contains the utility functions to compute the square kernel matrix of a training set as well as the kernel matrix between training and test data. There are some aspects that could be updated though:

• These functions are not compatible with all frameworks, for example the usage of np.array in these functions prohibits using them with Torch or

We have ZygoteRuleConfig for this, so there should be no major technical limitations. rrules generally have far better UX than @adjoints (as anyone who has had to read a stacktrace from Zygote can attest). The ultimate end goal would be to get rid of ZygoteRules entirely.

https://llvm.org/docs/NewPassManager.html

The tricky part is to keep our custom command line options working.

As per #909, environment.yml does not work on ARM Macs because of MKL.

We can create another environment file, environment-arm.yml, with an alternate BLAS specification. This file may also be used on Linux-ARM systems.

I'd propose adding the following two lines:

  - nomkl
  - openblas

• Operating system: ARM Mac
• How did you install Aesara: conda

Description

Describe the issue as clearly as possible. Issues are meant for bug reports and feature requests. The issue should contain enough information for a developer to put together a solution.

If this is a general question, please post to the forums.

Example

Here's the current errors.

mkdir -p doc/api
doxygen doxygen/doxygen.cfg
warn

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

The init module has been deprecated, and the recommend approach for generating initial weights is to use the Template.shape method:

>>> from pennylane.templates import StronglyEntanglingLayers
>>> qml.init.strong_ent_layers_normal(n_layers=3, n_wires=2) # deprecated
>>> np.random.random(StronglyEntanglingLayers.shape(n_layers=3, n_wires=2))  # new approach

We should upd

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

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.