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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def dense_dropconnect(inputs, output_size, dropconnect_dropout=0.0, name="dense_dropconnect", **kwargs):
 """Dense layer with dropconnect."""


  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)