OpenNMT-tf 2.24.0

New features

• Add experimental parameter mask_loss_outliers to mask high loss values considered as outliers (requires the tensorflow-probability module)

Fixes and improvements

• Fix TensorFlow Lite conversion for models using a PositionEmbedder layer
• Automatically pad the weights of linear layers to enable Tensor Cores in mixed precision training
• Correctly set the CTranslate2 options alignment_layer and alignment_heads when converting models using the attention reduction AVERAGE_LAST_LAYER
• Raise an error if a training dataset or annotation file has an unexpected size
• Warn about duplicated tokens when loading vocabularies