v1.1.1

Adds indexing based on Tensor indices.

v1.1.0

Includes many improvements from contributors to some of the autograd functionality and random distribution generation.

v1.0.0

Library Interface Overhaul (#61)

* Start of new library interface

* Don't always use arrow to avoid importing gobject

* more testing

* Tensor(T, S) implementation

* better backend abstraction

* more abstraction

* CPU Backend nearly complete

* OpenCL Backend with broadcasting

* linear algebra and grad

* Working through OpenCL Grad

* Continue working through OpenCL grad

* A lot more testing

* Custom kernel is an abomination

* NN Primitives

* Complete OpenCL activation + reduction

* Beginning NN layers

* More gates and axis reductions for Tensor(T, OCL(T))

* Why is this not checked in anymore

* Fixing NN

* Fix tri iterator

* Einsum work + various improvements

* Test coverage for einsum

* Einsum working with plenty of test coverage

* Run reformatting on docstrings + start working with mkdocs

* More docs

* Update ignore to include certain doc files

* More documentation

* Working with last couple OpenCL NN related fns

* OpenCL NN Work

* Move kernels to singletons start

* Actual singleton implementations for OCL methods

* All OpenCL Kernels moved to singletons except custom

* More Kernel work

* Most kernels completed

* Completely moved to OpenCL Singletons

* I always do that with relu loss

* Extending more functionality to OpenCL Backend

* Finish documentation

* Greater test coverage

* Test build pipeline with mkdocs

* Final commit for 1.0

* Numpy comparison

* Re-enable branch check for docs

v0.4.7

Bump version to have release + shard.yml match (#71)

v0.4.6

Doc fixes + creation methods re-added.

v0.4.5: 1.0.0 breaking changes (#65)

* 1.0.0 breaking changes

* ignore versions for now

v0.4.4

Fix yield iterations for Tensors with negative strides (#60)

v0.4.3

0.4.3 NN - Autograd - Random - Plot - Faster iteration (#42)

* testing yielding over iterators

* tri iterator

* iter complete

* sorting for tensors

* matrix exponential using pade

* neural network basics

* remove req

* move images

* full implementation of autograd and better networks

* Added plplot bindings

* merge PRs

* docs

* remove dataframes

* more activation

* default bias

* random creation methods using alea

0.4.2

bump shard version

0.4.1

tensordot and reshape bug (#37)