code: def _make_masked_constraint(mask, constraint=None):
      constraint = tf_keras.constraints.get(constraint)
  
      def masked_constraint(x):
          x = tf.convert_to_tensor(x, dtype_hint=tf.float32, name="x")
          if constraint is not None:
              x = constraint(x)
          return tf.cast(mask, x.dtype) * x
  
      return masked_constraint
  
imports: import numpy
  import six
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector
  from tensorflow_probability.python.bijectors import chain
  from tensorflow_probability.python.bijectors import scale
  from tensorflow_probability.python.bijectors import shift
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import tf_keras
  from tensorflow_probability.python.math.numeric import clip_by_value_preserve_gradient
  from tensorflow.python.util import deprecation
label_desc: Use image node_id 11 for calling a global function with example usage: _make_masked_constraint(mask, constraint) and returns: masked_constraint, unknown