1.18.78

[1.18.78]

Changed

• Dynamic batch sizes: Translator.translate() will adjust batch size in beam search to the actual number of inputs without using padding.

[1.18.77]

Added

• sockeye.score now loads data on demand and doesn't skip any input lines

[1.18.76]

Changed

• Do not compare scores from translation and scoring in integration tests.

Added

• Adding the option via the flag --stop-training-on-decoder-failure to stop training in case the checkpoint decoder dies (e.g. because there is not enough memory).
  In case this is turned on a checkpoint decoder is launched right when training starts in order to fail as early as possible.

[1.18.75]

Changed

• Do not create dropout layers for inference models for performance reasons.

[1.18.74]

Changed

• Revert change in 1.18.72 as no memory saving could be observed.

[1.18.73]

Fixed

• Fixed a bug where source-factors-num-embed was not correctly adjusted to num-embed
  when using prepared data & source-factor-combine sum.