code: def forward(self, input, conditioning=0):
      return self._forward(
          self.word_emb(input),
          (input != self.padding_idx).unsqueeze(2),
          conditioning,
      )
  
imports: from typing import Optional
  import torch
  import torch.nn
  import torch.nn.functional
  from nemo.collections.tts.modules.submodules import ConditionalInput, ConditionalLayerNorm, LinearNorm
  from nemo.collections.tts.parts.utils.helpers import get_mask_from_lengths
  from nemo.core.classes import NeuralModule, adapter_mixins, typecheck
  from nemo.core.neural_types.elements import EncodedRepresentation, LengthsType, MaskType, TokenIndex
  from nemo.core.neural_types.neural_type import NeuralType
label_desc: Use image node_id 3 for calling the FFTransformerEncoder obj's underlying member method code with example usage: obj.forward(input, conditioning) and returns: self