class_docstr: Base class for data converters for sequence classification data sets.
class_docstr_tok: ["Base","class","for","data","converters","for","sequence","classification","data","sets","."]
docstr: Gets an example from a dict with tensorflow tensors.
  
  Args:
      tensor_dict: Keys and values should match the corresponding Glue
          tensorflow_dataset examples.
docstr_tok: ["Gets","an","example","from","a","dict","with","tensorflow","tensors",".","Args",":","tensor_dict",":","Keys","and","values","should","match","the","corresponding","Glue","tensorflow_dataset","examples","."]
code: def get_example_from_tensor_dict(self, tensor_dict):
      """
      Gets an example from a dict with tensorflow tensors.
  
      Args:
          tensor_dict: Keys and values should match the corresponding Glue
              tensorflow_dataset examples.
      """
      raise NotImplementedError()
  
imports: import csv
  import dataclasses
  import json
  from dataclasses import dataclass
  from typing import List, Optional, Union
  from ...utils import is_tf_available, is_torch_available, logging
label_desc: Use image node_id 1 for calling the DataProcessor obj's underlying member method code with example usage: obj.get_example_from_tensor_dict(tensor_dict) without return types