class_docstr: Represents a sequence-to-sequence generator.
class_docstr_tok: ["Represents","a","sequence-to-sequence","generator","."]
docstr: :param source_seqs:
      The source sequences. *Shape:* :math:`(N,S,*)`, where :math:`N` is
      the batch size, :math:`S` is the sequence length, and :math:`*` is
      any number of sequence-specific dimensions including none.
  :param source_padding_mask:
      The padding mask of ``source_seqs``. *Shape:* :math:`(N,S)`, where
      :math:`N` is the batch size and :math:`S` is the sequence length.
  :param prompt_seqs:
      The prompt sequences. *Shape:* :math:`(N,S_{prm})`, where :math:`N`
      is the batch size and :math:`S_{prm}` is the prompt sequence length.
  :param prompt_padding_mask:
      The padding mask of ``prompt_seqs``. *Shape:* Same as ``prompt_seqs``.
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code: def __call__(
      self,
      source_seqs: Tensor,
      source_padding_mask: Optional[PaddingMask],
      prompt_seqs: Tensor,
      prompt_padding_mask: Optional[PaddingMask],
  ) -> Seq2SeqGeneratorOutput:
      """
      :param source_seqs:
          The source sequences. *Shape:* :math:`(N,S,*)`, where :math:`N` is
          the batch size, :math:`S` is the sequence length, and :math:`*` is
          any number of sequence-specific dimensions including none.
      :param source_padding_mask:
          The padding mask of ``source_seqs``. *Shape:* :math:`(N,S)`, where
          :math:`N` is the batch size and :math:`S` is the sequence length.
      :param prompt_seqs:
          The prompt sequences. *Shape:* :math:`(N,S_{prm})`, where :math:`N`
          is the batch size and :math:`S_{prm}` is the prompt sequence length.
      :param prompt_padding_mask:
          The padding mask of ``prompt_seqs``. *Shape:* Same as ``prompt_seqs``.
      """
  
imports: from __future__ import annotations
  from abc import ABC, abstractmethod
  from collections import OrderedDict
  from dataclasses import dataclass
  from typing import Dict, List, Optional, Protocol
  from torch import Tensor
  from torch.utils.hooks import RemovableHandle
  from fairseq2.models.decoder import DecoderModel
  from fairseq2.models.encoder_decoder import EncoderDecoderModel
  from fairseq2.nn.padding import PaddingMask
label_desc: Use image node_id 2 for calling the Seq2SeqGenerator obj's underlying member method code with example usage: obj.__call__(source_seqs, source_padding_mask, prompt_seqs, prompt_padding_mask) without return types