class_docstr: Representation for a sequence of sentences
  Each sentence will be embedded with a DocNN model,
  then all the sentences are embedded with another DocNN/BiLSTM model
code: def __init__(self, config: Config, embed_dim: int) -> None:
      super().__init__(config)
      self.doc_rep = create_module(
          config.doc_representation, embed_dim=embed_dim
      )
      self.doc_representation_dim = self.doc_rep.representation_dim
  
      self.seq_rep = create_module(
          config.seq_representation,
          embed_dim=self.doc_representation_dim,
      )
      self.representation_dim = self.seq_rep.representation_dim
      log_class_usage(__class__)
  
file_path: pytext/pytext/models/representations/seq_rep.py
imports: from typing import Union
  import torch
  from pytext.config import ConfigBase
  from pytext.models.module import create_module
  from pytext.utils.usage import log_class_usage
  from .bilstm_doc_attention import BiLSTMDocAttention
  from .docnn import DocNNRepresentation
  from .representation_base import RepresentationBase
label_desc: Use image node_id 1 to create a new SeqRepresentation object from inherited base classes: RepresentationBase with example: obj = SeqRepresentation(config, embed_dim)