class_docstr: A `Bijector` that computes the reciprocal `b(x) = 1. / x` entrywise.
  
  This bijector accepts any non-zero values for both `forward` and `inverse`.
  
  #### Examples
  
  ```python
  bijector.Reciprocal().forward(x=[[1., 2.], [4., 5.]])
  # Result: [[1., .5], [.25, .2]], i.e., 1 / x
  
  bijector.Reciprocal().forward(x=[[0., 2.], [4., 5.]])
  # Result: AssertionError, doesn't accept zero.
  
  bijector.Square().inverse(y=[[1., 2.], [4., 5.]])
  # Result: [[1., .5], [.25, .2]], i.e. 1 / x
  
  ```
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docstr: Instantiates the `Reciprocal`.
  
  Args:
    validate_args: Python `bool` indicating whether arguments should be
      checked for correctness.
    name: Python `str` name given to ops managed by this object.
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code: def __init__(self, validate_args=False, name="reciprocal"):
      """Instantiates the `Reciprocal`.
  
      Args:
        validate_args: Python `bool` indicating whether arguments should be
          checked for correctness.
        name: Python `str` name given to ops managed by this object.
      """
      parameters = dict(locals())
      with tf.name_scope(name) as name:
          super(Reciprocal, self).__init__(
              forward_min_event_ndims=0,
              validate_args=validate_args,
              parameters=parameters,
              name=name,
          )
  
file_path: probability/tensorflow_probability/python/bijectors/reciprocal.py
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import dtype_util
label_desc: Use image node_id 1 to create a new Reciprocal object from inherited base classes: bijector, bijector with example: obj = Reciprocal(validate_args, name)