code: def testValidateArgs(self):
      with self.assertRaisesOpError("concentration must be positive"):
          k = exponential_curve.ExponentialCurve(
              concentration=-1.0, rate=1.0, validate_args=True
          )
          self.evaluate(k.apply([[1.0]], [[1.0]]))
  
      if not tf.executing_eagerly():
          with self.assertRaisesOpError("rate must be positive"):
              k = exponential_curve.ExponentialCurve(
                  concentration=1.0, rate=-1.0, validate_args=True
              )
              self.evaluate(k.apply([[1.0]], [[1.0]]))
  
file_path: probability/tensorflow_probability/python/math/psd_kernels/exponential_curve_test.py
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.math.psd_kernels import exponential_curve
label_desc: Use image node_id 3 for calling the ExponentialCurveTest obj's underlying member method code with example usage: obj.testValidateArgs() without return types