class_docstr: Bijector to associate a numeric inverse with any invertible function.
class_docstr_tok: ["Bijector","to","associate","a","numeric","inverse","with","any","invertible","function","."]
code: def _inverse_no_gradient(self, y):
      # Search for a root in unconstrained space.
      unconstrained_root, _, num_iterations = self.root_search_fn(
          lambda ux: (
              self.bound_fn(self.domain_constraint_fn(ux)) - y
          ),  # pylint: disable=not-callable
          tf.ones_like(y),
          max_iterations=self.max_iterations,
      )
      x = self.domain_constraint_fn(
          unconstrained_root
      )  # pylint: disable=not-callable
      if self.require_convergence:
          x = tf.where(
              num_iterations < self.max_iterations,
              x,
              tf.cast(np.nan, x.dtype),
          )
      return x
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector
  from tensorflow_probability.python.internal import callable_util
  from tensorflow_probability.python.internal import custom_gradient
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.math import root_search
label_desc: Use image node_id 11 for calling the ScalarFunctionWithInferredInverse obj's underlying member method code with example usage: obj._inverse_no_gradient(y) and returns: x