code: def _prepare_inputs(
      self,
      tokens: torch.Tensor,
      segment_labels: torch.Tensor = None,
      positions: torch.Tensor = None,
      token_embeddings: torch.Tensor = None,
      attn_mask: torch.Tensor = None,
  ):
      inputs = [tokens]
      if segment_labels is not None:
          inputs += [segment_labels]
      if positions is not None:
          inputs += [positions]
      if token_embeddings is not None:
          inputs += [token_embeddings]
      if attn_mask is not None:
          inputs += [attn_mask]
      return inputs
  
file_path: pytext/pytext/models/representations/traced_transformer_encoder.py
imports: from typing import Tuple
  import torch
  import torch.cuda
  import torch.nn
  from fairseq.modules import TransformerSentenceEncoder
  from pytext.utils.usage import log_class_usage
label_desc: Use image node_id 3 for calling the TracedTransformerEncoder obj's underlying member method code with example usage: obj._prepare_inputs(tokens, segment_labels, positions, token_embeddings, attn_mask) and returns: inputs