code: def testNonStrictTurnsOffAllChecks(self):
      # Make totally invalid input.
      alpha = [[-1.0, 2]]  # alpha should be positive.
      counts = [[1.0, 0], [0.0, -1]]  # counts should be non-negative.
      n = [
          -5.3
      ]  # n should be a non negative integer equal to counts.sum.
      dist = dm.DirichletMultinomial(n, alpha, validate_args=False)
      self.evaluate(dist.prob(counts))
  
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import dirichlet_multinomial
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 24 for calling the DirichletMultinomialTest obj's underlying member method code with example usage: obj.testNonStrictTurnsOffAllChecks() without return types