code: def __call__(self, input_ids, attention_mask, token_type_ids):
      extended_attention_mask = attention_mask.unsqueeze(1).unsqueeze(2)
      extended_attention_mask = (
          1.0 - extended_attention_mask
      ) * -10000.0
  
      embedding_output = self.embeddings(input_ids, token_type_ids)
      encoder_outputs = self.encoder(
          embedding_output, extended_attention_mask
      )
  
      return encoder_outputs
  
imports: from tinygrad.tensor import Tensor
  from tinygrad.nn import Linear, LayerNorm, Embedding
  from tinygrad.helpers import fetch, get_child
  from pathlib import Path
label_desc: Use image node_id 2 for calling the Bert obj's underlying member method code with example usage: obj.__call__(input_ids, attention_mask, token_type_ids) and returns: encoder_outputs