class_docstr: The Seq2Edits model. See file docstring.
docstr: Decodes Transformer outputs, see transformer.transformer_decode().
docstr_tok: ["Decodes","Transformer","outputs",",","see","transformer.transformer_decode","(",")","."]
code: def decode(
      self,
      decoder_input,
      encoder_output,
      encoder_decoder_attention_bias,
      decoder_self_attention_bias,
      hparams,
      cache=None,
      decode_loop_step=None,
      nonpadding=None,
      losses=None,
      **kwargs,
  ):
      """Decodes Transformer outputs, see transformer.transformer_decode()."""
      return transformer.transformer_decode(
          self._decoder_function,
          decoder_input,
          encoder_output,
          encoder_decoder_attention_bias,
          decoder_self_attention_bias,
          hparams,
          attention_weights=self.attention_weights,
          cache=cache,
          decode_loop_step=decode_loop_step,
          nonpadding=nonpadding,
          losses=losses,
          **kwargs,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import logging
  from tensor2tensor.layers import common_attention
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import transformer_layers
  from tensor2tensor.models import transformer
  from tensor2tensor.utils import registry
  from tensor2tensor.utils import t2t_model
  import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling the TransformerSeq2edits obj's underlying member method code with example usage: obj.decode(decoder_input, encoder_output, encoder_decoder_attention_bias, decoder__attention_bias, hparams, cache, decode_loop_step, nonpadding, losses) and returns: transformer