class_docstr: Decoder layer only for inference.
code: def __init__(self, config, initial_weights=None, initial_biases=None):
      super().__init__(config, initial_weights, initial_biases)
  
file_path: lightseq/lightseq/training/cli/fs_modules/ls_fs_transformer_decoder_layer.py
imports: from fairseq.incremental_decoding_utils import with_incremental_state
  from lightseq.training.ops.pytorch.transformer_decoder_layer import LSTransformerDecoderLayer
label_desc: Use image node_id 1 to create a new LSFSTransformerDecoderLayer object from inherited base classes: LSTransformerDecoderLayer with example: obj = LSFSTransformerDecoderLayer(config, initial_weights, initial_biases)