class_docstr: Abstract class for the encoder.
  
  An encoder takes a `target` sequence with corresponding covariates and maps
  it into a static latent and a dynamic latent code with the same length as
  the `target` sequence.
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docstr: Parameters
  ----------
  F:
      A module that can either refer to the Symbol API or the NDArray
      API in MXNet.
  target
      target time series,
      shape (batch_size, sequence_length)
  static_features
      static features,
      shape (batch_size, num_feat_static)
  dynamic_features
      dynamic_features,
      shape (batch_size, sequence_length, num_feat_dynamic)
  
  Returns
  -------
  Tensor
      static code,
      shape (batch_size, num_feat_static)
  Tensor
      dynamic code,
      shape (batch_size, sequence_length, num_feat_dynamic)
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code: def hybrid_forward(
      self,
      F,
      target: Tensor,
      static_features: Tensor,
      dynamic_features: Tensor,
  ) -> Tuple[Tensor, Tensor]:
      """
      Parameters
      ----------
      F:
          A module that can either refer to the Symbol API or the NDArray
          API in MXNet.
      target
          target time series,
          shape (batch_size, sequence_length)
      static_features
          static features,
          shape (batch_size, num_feat_static)
      dynamic_features
          dynamic_features,
          shape (batch_size, sequence_length, num_feat_dynamic)
  
      Returns
      -------
      Tensor
          static code,
          shape (batch_size, num_feat_static)
      Tensor
          dynamic code,
          shape (batch_size, sequence_length, num_feat_dynamic)
      """
      raise NotImplementedError
  
imports: from typing import List, Tuple
  from mxnet.gluon import nn
  from gluonts.core.component import validated
  from gluonts.mx import Tensor
  from gluonts.mx.block.cnn import CausalConv1D
  from gluonts.mx.block.mlp import MLP
  from gluonts.mx.block.rnn import RNN
label_desc: Use image node_id 1 for calling the Seq2SeqEncoder obj's underlying member method code with example usage: obj.hybrid_forward(F, target, static_features, dynamic_features) without return types