code: def dense_dropconnect(inputs,
                        output_size,
                        dropconnect_dropout=0.0,
                        name="dense_dropconnect",
                        **kwargs):
    
  
    if dropconnect_dropout != 0.0:
      tf.logging.info("Applying dropconnect as the kernel regularization.")
      kwargs["kernel_regularizer"] = functools.partial(
          tf.nn.dropout, keep_prob=1.0 - dropconnect_dropout)
  
    return dense(inputs, output_size, use_bias=True, name=name, **kwargs)
docs: Dense layer with dropconnect.