class_docstr: Tests correctness of the softclip transformation.
class_docstr_tok: ["Tests","correctness","of","the","softclip","transformation","."]
code: def test_constraints_are_satisfied(self, low, high, hinge_softness):
      xs = tf.convert_to_tensor(
          [-1e6, -100.0, -3.0, 0.0, 1.3, 4.0, 123.0, 1e6], self.dtype
      )
  
      low_tensor = (
          tf.convert_to_tensor(low, self.dtype)
          if low is not None
          else low
      )
      high_tensor = (
          tf.convert_to_tensor(high, self.dtype)
          if high is not None
          else high
      )
      hinge_softness = tf.convert_to_tensor(hinge_softness, self.dtype)
      b = soft_clip.SoftClip(low_tensor, high_tensor, hinge_softness)
      ys = self.evaluate(b.forward(xs))
      if low is not None:
          self.assertAllGreaterEqual(ys, low)
          self.assertAllClose(ys[0], low)
      if high is not None:
          self.assertAllLessEqual(ys, high)
          self.assertAllClose(ys[-1], high)
  
file_path: probability/tensorflow_probability/python/bijectors/soft_clip_test.py
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import soft_clip
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 1 for calling the _SoftClipBijectorBase obj's underlying member method code with example usage: obj.test_constraints_are_satisfied(low, high, hinge_softness) without return types