Sockeye

Latest version: v3.1.34

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1.14.3

Changed
- Fast decoding for transformer models. Caches keys and values of self-attention before softmax.
Changed decoding flag `--bucket-width` to apply only to source length.

1.14.2

Added
- Gradient norm clipping (`--gradient-clipping-type`) and monitoring.
Changed
- Changed `--clip-gradient` to `--gradient-clipping-threshold` for consistency.

1.14.1

Changed
- Sorting sentences during decoding before splitting them into batches.
- Default chunk size: The default chunk size when batching is enabled is now batch_size * 500 during decoding to avoid
users accidentally forgetting to increase the chunk size.

1.14.0

Changed
- Downscaled fixed positional embeddings for CNN models.
- Renamed `--monitor-bleu` flag to `--decode-and-evaluate` to illustrate that it computes
other metrics in addition to BLEU.

Added
- `--decode-and-evaluate-use-cpu` flag to use CPU for decoding validation data.
- `--decode-and-evaluate-device-id` flag to use a separate GPU device for validation decoding. If not specified, the
existing and still default behavior is to use the last acquired GPU for training.

1.13.2

Added
- A tool that extracts specified parameters from params.x into a .npz file for downstream applications or analysis.

1.13.1

Added
- Added chrF metric
([Popovic 2015: chrF: character n-gram F-score for automatic MT evaluation](http://www.statmt.org/wmt15/pdf/WMT49.pdf)) to Sockeye.
sockeye.evaluate now accepts `bleu` and `chrf` as values for `--metrics`

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