code: def test_mutated_at_most_one_implicit_dimension(self):
      batch_shape = tf.Variable([1, 1])
      self.evaluate(batch_shape.initializer)
      dist = normal_lib.Normal([[0]], [[1]])
      d = batch_reshape.BatchReshape(
          dist, batch_shape, validate_args=True
      )
      self.evaluate(d.sample(seed=test_util.test_seed()))
      with self.assertRaisesOpError(
          "At most one dimension can be unknown"
      ):
          with tf.control_dependencies([batch_shape.assign([-1, -1])]):
              self.evaluate(d.sample(seed=test_util.test_seed()))
  
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector_test_util
  from tensorflow_probability.python.distributions import batch_reshape
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import poisson
  from tensorflow_probability.python.distributions import triangular
  from tensorflow_probability.python.distributions import uniform
  from tensorflow_probability.python.distributions import wishart
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.util.deferred_tensor import DeferredTensor
label_desc: Use image node_id 15 for calling the _BatchReshapeTest obj's underlying member method code with example usage: obj.test_mutated_at_most_one_implicit_dimension() without return types