code: def make_mvn(self, dims, new_batch_shape, old_batch_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
      )
      reshape_mvn = batch_reshape.BatchReshape(
          distribution=mvn,
          batch_shape=new_batch_shape_ph,
          validate_args=True,
      )
      return mvn, reshape_mvn
  
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 7 for calling the _BatchReshapeTest obj's underlying member method code with example usage: obj.make_mvn(dims, new_batch_shape, old_batch_shape) and returns: mvn,  reshape_mvn