class_docstr: Tests correctness of the floor transformation.
code: def testBijectorApproximatesIdentityHighTemperature(self):
      # Let's make this look like the identity.
      floor = softfloor.Softfloor(self.dtype(1e4))
      pos_values = np.linspace(2.01, 2.99, 100).astype(self.dtype)
      neg_values = np.linspace(-2.99, -2.01, 100).astype(self.dtype)
      self.assertAllClose(
          self.evaluate(floor.forward(pos_values)),
          pos_values,
          rtol=1e-5,
      )
      self.assertAllClose(
          self.evaluate(floor.forward(neg_values)),
          neg_values,
          rtol=1e-5,
      )
  
      self.assertAllClose(
          self.evaluate(floor.inverse(pos_values)),
          pos_values,
          rtol=5e-4,
      )
      self.assertAllClose(
          self.evaluate(floor.inverse(neg_values)),
          neg_values,
          rtol=5e-4,
      )
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector_test_util
  from tensorflow_probability.python.bijectors import softfloor
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math.gradient import value_and_gradient
label_desc: Use image node_id 3 for calling the _SoftFloorBijectorBase obj's underlying member method code with example usage: obj.testBijectorApproximatesIdentityHighTemperature() without return types