code: def test_non_positive_shape(self):
      dims = 2
      old_batch_shape = [4]
      if self.is_static_shape:
          # Unknown first dimension does not trigger size check. Note that
          # any dimension < 0 is treated statically as unknown.
          new_batch_shape = [-1, 0]
      else:
          new_batch_shape = [
              -2,
              -2,
          ]  # -2 * -2 = 4, same size as the old shape.
  
      new_batch_shape_ph = (
          tf.constant(np.int32(new_batch_shape))
          if self.is_static_shape
          else tf1.placeholder_with_default(
              np.int32(new_batch_shape), shape=None
          )
      )
  
      scale = np.ones(old_batch_shape + [dims], self.dtype)
      scale_ph = tf1.placeholder_with_default(
          scale, shape=scale.shape if self.is_static_shape else None
      )
      mvn = mvn_diag.MultivariateNormalDiag(
          scale_diag=scale_ph, validate_args=True
      )
  
      if self.is_static_shape or tf.executing_eagerly():
          with self.assertRaisesRegexp(
              ValueError, r".*must be >=(-1| 0).*"
          ):
              batch_reshape.BatchReshape(
                  distribution=mvn,
                  batch_shape=new_batch_shape_ph,
                  validate_args=True,
              )
  
      else:
          with self.assertRaisesOpError(r".*must be >=(-1| 0).*"):
              self.evaluate(
                  batch_reshape.BatchReshape(
                      distribution=mvn,
                      batch_shape=new_batch_shape_ph,
                      validate_args=True,
                  ).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 11 for calling the _BatchReshapeTest obj's underlying member method code with example usage: obj.test_non_positive_shape() without return types