code: def testInvalidLam(self):
      invalid_lams = [-0.01, -1.0, -2.0]
      for lam in invalid_lams:
          with self.assertRaisesOpError(
              "Argument `rate` must be non-negative."
          ):
              poisson = self._make_poisson(rate=lam)
              self.evaluate(poisson.rate_parameter())
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import poisson
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import implementation_selection
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 3 for calling the PoissonTest obj's underlying member method code with example usage: obj.testInvalidLam() without return types