Added custom speedometer to exactly track samples/sec and words/sec d…

…uring training (awslabs#260)

Fix entry points in setup.py (awslabs#258)

Missing commata.

Update to mxnet==1.0 (awslabs#244)

* Fix inference dims for mxnet 1.0

* Improved mx.NDArray indexing: removed intermediate numpy arrays for scores and topk hyp/word indices

* Removed unused parameter

* Reformatting inference.py

* simplify _get_inference_input()

* Update dependencies to mxnet==1.0.0

* Expose nccl kvstore and gradient compression

* Update major version

Fixed the maximum input length calculation at inference. (awslabs#255)

* Fixed the maximum input length calculation at inference.

* doc string

Bugfix: --num-samples-per-shard must be int (awslabs#254)

* Bugfix: --num-samples-per-shard must be int

* bump version

Sharded data iterator. (awslabs#241)

* Sharded data iterator.

* Added remaining sockeye/*.py files to typechecked files (awslabs#242)

* Tests to see we get the right number of batches.

* Improved log message about vocabs a little bit

* Factored validation iter creation into separate function

* Covering prepare data in the system tests.

* Writing a data version.

Remove RNN parameter packing, FusedRNN support; refactored core model…

… components (awslabs#189)

* Removed RNN parameter packing and FusedRNN support

* Refactor embedding and output layers (awslabs#196)

* Removed RNN parameter packing and FusedRNN support

* Refactoring of sockeye model: source embed/target embed/output layers are now separate components in model

* Make training and inference work. Remove lexical biasing code.

Update to MXNet version 0.12.1. (awslabs#213)

Yet another fix for the data iterator. Added a test. (awslabs#188)

* Yet another fix for the data iterator. Added a test that would catch this kind of problem

* Bump minor version

Hotfix: use correct vocab and add_bos setting for target side validat…

…ion data (awslabs#186)