code: def bloom_convert_to_bloom_cache(
      past_key_value: Tuple[Tuple["torch.Tensor", "torch.Tensor"]]
  ) -> Tuple[Tuple["torch.Tensor", "torch.Tensor"]]:
      """
      Converts the cache to the format expected by Bloom, i.e. to tuple(tuple([batch_size * num_heads, ...]))
      """
      batch_size, num_heads, head_dim, seq_length = past_key_value[0][
          0
      ].shape
      batch_size_times_num_heads = batch_size * num_heads
      # key:  [batch_size, num_heads, head_dim, seq_length] -> [batch_size * num_heads, head_dim, seq_length]
      # value: [batch_size, num_heads, seq_length, head_dim] -> [batch_size * num_heads, seq_length, head_dim]
      return tuple(
          (
              layer_past[0].view(
                  batch_size_times_num_heads, head_dim, seq_length
              ),
              layer_past[1].view(
                  batch_size_times_num_heads, seq_length, head_dim
              ),
          )
          for layer_past in past_key_value
      )
  
label_desc: Use image node_id 2 for calling a global function with example usage: bloom_convert_to_bloom_cache(past_key_value) and returns: tuple