class_docstr: Tests the correctness of the Y = g(X) = X / (1 + |X|) transformation.
class_docstr_tok: ["Tests","the","correctness","of","the","Y","=","g","(","X",")","=","X","\/","(","1","+","|X|",")","transformation","."]
code: def testBijectiveAndFinite(self):
      bijector = softsign.Softsign(validate_args=True)
      x = np.linspace(-20.0, 20.0, 100).astype(np.float32)
      y = np.linspace(-0.99, 0.99, 100).astype(np.float32)
      bijector_test_util.assert_bijective_and_finite(
          bijector,
          x,
          y,
          eval_func=self.evaluate,
          event_ndims=0,
          rtol=1e-3,
          atol=1e-3,
      )
  
file_path: probability/tensorflow_probability/python/bijectors/softsign_test.py
imports: import numpy
  from tensorflow_probability.python.bijectors import bijector_test_util
  from tensorflow_probability.python.bijectors import softsign
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 9 for calling the SoftsignBijectorTest obj's underlying member method code with example usage: obj.testBijectiveAndFinite() without return types