code: def __call__(self, chunk_size=None):
      N = self.mean.size
      if self.size is None:
          shape = (N,)
      else:
          try:
              shape = tuple(self.size) + (N,)
          except TypeError:
              shape = (self.size, N)
  
      return self.new_tensor(None, shape, raw_chunk_size=chunk_size)
  
file_path: mars/mars/tensor/random/multivariate_normal.py
imports: import itertools
  import numpy
  from ...None import opcodes
  from ...serialization.serializables import NDArrayField, StringField, Float64Field
  from ...config import options
  from ..utils import decide_chunk_sizes, gen_random_seeds
  from ..array_utils import array_module, device
  from .core import TensorRandomOperandMixin, TensorDistribution, TENSOR_CHUNK_TYPE
label_desc: Use image node_id 1 for calling the TensorMultivariateNormal obj's underlying member method code with example usage: obj.__call__(chunk_size) and returns: self