class_docstr: Shape auto-encoder with multiple convex polytopes.
  
  Attributes:
    n_params: int, the number of hyperplane parameters.
class_docstr_tok: ["Shape","auto-encoder","with","multiple","convex","polytopes",".","Attributes",":","n_params",":","int",",","the","number","of","hyperplane","parameters","."]
docstr: Compute overlap loss.
docstr_tok: ["Compute","overlap","loss","."]
code: def _compute_overlap_loss(self, overlap):
      """Compute overlap loss."""
      return tf.reduce_mean(tf.square(tf.nn.relu(overlap - 2.0)))
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow.compat.v1
  from tensorflow_graphics.projects.cvxnet.lib import resnet
label_desc: Use image node_id 8 for calling the MultiConvexNet obj's underlying member method code with example usage: obj._compute_overlap_loss(overlap) and returns: tf