Sockeye

Latest version: v3.1.34

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1.10.0

Changed
- Updated MXNet dependency to 0.12 (w/ MKL support by default).
- Changed `--smoothed-cross-entropy-alpha` to `--label-smoothing`.
Label smoothing should now require significantly less memory due to its addition to MXNet's `SoftmaxOutput` operator.
- `--weight-normalization` now applies not only to convolutional weight matrices, but to output layers of all decoders.
It is also independent of weight tying.
- Transformers now use `--embed-dropout`. Before they were using `--transformer-dropout-prepost` for this.
- Transformers now scale their embedding vectors before adding fixed positional embeddings.
This turns out to be crucial for effective learning.
- `.param` files now use 5 digit identifiers to reduce risk of overflowing with many checkpoints.

Added
- Added CUDA 9.0 requirements file.
- `--loss-normalization-type`. Added a new flag to control loss normalization. New default is to normalize
by the number of valid, non-PAD tokens instead of the batch size.
- `--weight-init-xavier-factor-type`. Added new flag to control Xavier factor type when `--weight-init=xavier`.
- `--embed-weight-init`. Added new flag for initialization of embeddings matrices.

Removed
- `--smoothed-cross-entropy-alpha` argument. See above.
- `--normalize-loss` argument. See above.

1.9.0

Added
- Batch decoding. New options for the translate CLI: ``--batch-size`` and ``--chunk-size``. Translator.translate()
now accepts and returns lists of inputs and outputs.

1.8.4

Added
- Exposing the MXNet KVStore through the ``--kvstore`` argument, potentially enabling distributed training.

1.8.3

Not secure
Added
- Optional smart rollback of parameters and optimizer states after updating the learning rate
if not improved for x checkpoints. New flags: ``--learning-rate-decay-param-reset``,
``--learning-rate-decay-optimizer-states-reset``

1.8.2

Fixed
- The RNN variational dropout mask is now independent of the input
(previously any zero initial state led to the first state being canceled).
- Correctly pass `self.dropout_inputs` float to `mx.sym.Dropout` in `VariationalDropoutCell`.

1.8.1

Changed
- Instead of truncating sentences exceeding the maximum input length they are now translated in chunks.

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