code: def input_types(self):
      return {
          "text": NeuralType(("B", "T_text"), TokenIndex()),
          "durs": NeuralType(("B", "T_text"), TokenDurationType()),
          "pitch": NeuralType(("B", "T_audio"), RegressionValuesType()),
          "energy": NeuralType(
              ("B", "T_audio"), RegressionValuesType(), optional=True
          ),
          "speaker": NeuralType(("B"), Index(), optional=True),
          "pace": NeuralType(optional=True),
          "spec": NeuralType(
              ("B", "D", "T_spec"), MelSpectrogramType(), optional=True
          ),
          "attn_prior": NeuralType(
              ("B", "T_spec", "T_text"), ProbsType(), optional=True
          ),
          "mel_lens": NeuralType(("B"), LengthsType(), optional=True),
          "input_lens": NeuralType(("B"), LengthsType(), optional=True),
          "reference_spec": NeuralType(
              ("B", "D", "T_spec"), MelSpectrogramType(), optional=True
          ),
          "reference_spec_lens": NeuralType(
              ("B"), LengthsType(), optional=True
          ),
      }
  
imports: import torch
  from nemo.collections.tts.modules.submodules import ConditionalInput, ConditionalLayerNorm
  from nemo.collections.tts.parts.utils.helpers import binarize_attention_parallel, regulate_len
  from nemo.core.classes import NeuralModule, adapter_mixins, typecheck
  from nemo.core.neural_types.elements import EncodedRepresentation, Index, LengthsType, LogprobsType, MelSpectrogramType, ProbsType, RegressionValuesType, TokenDurationType, TokenIndex, TokenLogDurationType
  from nemo.core.neural_types.neural_type import NeuralType
label_desc: Use image node_id 2 for calling the FastPitchModule obj's underlying member method code with example usage: obj.input_types() and returns: dict