docstr: Gets all encoded data.
  
  :param include_target: whether to include the target column in the output or not.
  :return: A `torch.Tensor` with the encoded dataframe.
docstr_tok: ["Gets","all","encoded","data",".",":","param","include_target",":","whether","to","include","the","target","column","in","the","output","or","not",".",":","return",":","A","`","torch.Tensor","`","with","the","encoded","dataframe","."]
code: def get_encoded_data(
      self, include_target: bool = True
  ) -> torch.Tensor:
      """
      Gets all encoded data.
  
      :param include_target: whether to include the target column in the output or not.
      :return: A `torch.Tensor` with the encoded dataframe.
      """
      encoded_dfs = []
      for col in self.data_frame.columns:
          if (
              include_target or col != self.target
          ) and self.encoders.get(col, False):
              encoded_dfs.append(self.get_encoded_column_data(col))
  
      return torch.cat(encoded_dfs, 1)
  
imports: import inspect
  from typing import List, Tuple, Dict
  import torch
  import numpy
  import pandas
  from torch.utils.data import Dataset
  from lightwood.encoder.base import BaseEncoder
label_desc: Use image node_id 7 for calling the EncodedDs obj's underlying member method code with example usage: obj.get_encoded_data(include_target) and returns: torch