class_docstr: Compute `g(X) = X^2`; X is a positive real number.
  
  g is a bijection between the non-negative real numbers (R_+) and the
  non-negative real numbers.
  
  #### Examples
  
  ```python
  bijector.Square().forward(x=[[1., 0], [2, 1]])
  # Result: [[1., 0], [4, 1]], i.e., x^2
  
  bijector.Square().inverse(y=[[1., 4], [9, 1]])
  # Result: [[1., 2], [3, 1]], i.e., sqrt(y).
  ```
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code: def _forward_log_det_jacobian(self, x):
      with tf.control_dependencies(self._assertions(x)):
          return np.log(2.0) + tf.math.log(x)
  
file_path: probability/tensorflow_probability/python/bijectors/square.py
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector
  from tensorflow_probability.python.internal import assert_util
label_desc: Use image node_id 6 for calling the Square obj's underlying member method code with example usage: obj._forward_log_det_jacobian(x) and returns: unknown