code: def __init__(
      self,
      embedding_size,
      n_heads,
      hidden_size,
      n_layers,
      dropout,
      total_speakers,
  ):
      super().__init__()
      self.pos_encoder = PositionalEncoding(embedding_size, dropout=0.0)
      encoder_layers = TransformerEncoderLayer(
          embedding_size, n_heads, hidden_size, dropout=dropout
      )
      self.transformer_encoder = TransformerEncoder(
          encoder_layers, n_layers
      )
  
      self.embedding_size = embedding_size
      self.classifier = torch.nn.Linear(embedding_size, total_speakers)
  
imports: import math
  import torch
  import torch.nn
  from torch.nn import TransformerEncoder, TransformerEncoderLayer
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new Classifier object from inherited base classes: torch.nn with example: obj = Classifier(embedding_size, n_heads, hidden_size, n_layers, dropout, total_speakers)