class_docstr: A baseclass for modules to perform various classification tasks.
class_docstr_tok: ["A","baseclass","for","modules","to","perform","various","classification","tasks","."]
docstr: Returns definitions of module input ports.
  We implement it here since all NLP classifiers have the same inputs
docstr_tok: ["Returns","definitions","of","module","input","ports",".","We","implement","it","here","since","all","NLP","classifiers","have","the","same","inputs"]
code: def input_types(self) -> Optional[Dict[str, NeuralType]]:
      """
      Returns definitions of module input ports.
      We implement it here since all NLP classifiers have the same inputs
      """
      return {
          "hidden_states": NeuralType(("B", "T", "D"), ChannelType())
      }
  
file_path: NeMo/nemo/collections/nlp/modules/common/classifier.py
imports: from typing import Dict, Optional
  import torch
  from torch import nn
  from nemo.collections.common.parts import transformer_weights_init
  from nemo.core.classes import Exportable, NeuralModule
  from nemo.core.neural_types import ChannelType, NeuralType
label_desc: Use image node_id 1 for calling the Classifier obj's underlying member method code with example usage: obj.input_types() and returns: dict