code: def maxnorm_i_regularizer(scale):
      """Max-norm input regularization removes the neurons of previous layer.
      Returns a function that can be used to apply max-norm regularization to each row of weight matrix.
      The implementation follows `TensorFlow contrib <https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/layers/python/layers/regularizers.py>`__.
  
      Parameters
      ----------
      scale : float
          A scalar multiplier `Tensor`. 0.0 disables the regularizer.
  
      Returns
      ---------
      A function with signature `mn_i(weights, name=None)` that apply Lo regularization.
  
      Raises
      ---------
      ValueError : If scale is outside of the range [0.0, 1.0] or if scale is not a float.
  
      """
      if isinstance(scale, numbers.Integral):
          raise ValueError("scale cannot be an integer: %s" % scale)
  
      if isinstance(scale, numbers.Real):
          if scale < 0.0:
              raise ValueError(
                  "Setting a scale less than 0 on a regularizer: %g"
                  % scale
              )
          # if scale >= 1.:
          #   raise ValueError('Setting a scale greater than 1 on a regularizer: %g' %
          #                    scale)
          if scale == 0.0:
              logging.info("Scale of 0 disables regularizer.")
              return lambda _, name=None: None
  
      def mn_i(weights, name="maxnorm_i_regularizer"):
          """Applies max-norm regularization to weights."""
          with tf.name_scope(name) as scope:
              my_scale = ops.convert_to_tensor(
                  scale, dtype=weights.dtype.base_dtype, name="scale"
              )
              if tf.__version__ <= "0.12":
                  standard_ops_fn = standard_ops.mul
              else:
                  standard_ops_fn = standard_ops.multiply
              return standard_ops_fn(
                  my_scale,
                  standard_ops.reduce_sum(
                      standard_ops.reduce_max(
                          standard_ops.abs(weights), 1
                      )
                  ),
                  name=scope,
              )
  
      return mn_i
  
imports: import numbers
  import tensorflow
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops, math_ops, nn_ops, standard_ops
  from tensorlayer import logging
label_desc: Use image node_id 18 for calling a global function with example usage: maxnorm_i_regularizer(scale) and returns: mn_i, function, standard_ops_fn