code: def __call__(self, hidden_states, attention_mask):
      mixed_query_layer = self.query(hidden_states)
      mixed_key_layer = self.key(hidden_states)
      mixed_value_layer = self.value(hidden_states)
  
      query_layer = self.transpose_for_scores(mixed_query_layer)
      key_layer = self.transpose_for_scores(mixed_key_layer)
      value_layer = self.transpose_for_scores(mixed_value_layer)
  
      context_layer = Tensor.scaled_dot_product_attention(
          query_layer,
          key_layer,
          value_layer,
          attention_mask,
          self.dropout,
      )
  
      context_layer = context_layer.transpose(1, 2)
      context_layer = context_layer.reshape(
          context_layer.shape[0],
          context_layer.shape[1],
          self.all_head_size,
      )
  
      return context_layer
  
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 BertSelfAttention obj's underlying member method code with example usage: obj.__call__(hidden_states, attention_mask) and returns: context_layer