code: def empty(shape, dtype=None, chunk_size=None, gpu=None, order="C"):
      """
      Return a new tensor of given shape and type, without initializing entries.
  
      Parameters
      ----------
      shape : int or tuple of int
          Shape of the empty tensor
      dtype : data-type, optional
          Desired output data-type.
      chunk_size : int or tuple of int or tuple of ints, optional
          Desired chunk size on each dimension
      gpu : bool, optional
          Allocate the tensor on GPU if True, False as default
      order : {'C', 'F'}, optional, default: 'C'
          Whether to store multi-dimensional data in row-major
          (C-style) or column-major (Fortran-style) order in
          memory.
  
      Returns
      -------
      out : Tensor
          Tensor of uninitialized (arbitrary) data of the given shape, dtype, and
          order.  Object arrays will be initialized to None.
  
      See Also
      --------
      empty_like, zeros, ones
  
      Notes
      -----
      `empty`, unlike `zeros`, does not set the array values to zero,
      and may therefore be marginally faster.  On the other hand, it requires
      the user to manually set all the values in the array, and should be
      used with caution.
  
      Examples
      --------
      >>> import mars.tensor as mt
      >>> mt.empty([2, 2]).execute()
      array([[ -9.74499359e+001,   6.69583040e-309],
             [  2.13182611e-314,   3.06959433e-309]])         #random
      >>> mt.empty([2, 2], dtype=int).execute()
      array([[-1073741821, -1067949133],
             [  496041986,    19249760]])                     #random
      """
      tensor_order = get_order(
          order,
          None,
          available_options="CF",
          err_msg="only 'C' or 'F' order is permitted",
      )
      op = TensorEmpty(dtype=dtype, gpu=gpu, order=order)
      return op(shape, chunk_size=chunk_size, order=tensor_order)
  
imports: import numpy
  from ...None import opcodes
  from ...serialization.serializables import KeyField, StringField
  from ...lib.sparse import SparseNDArray
  from ...lib.sparse.core import naked, get_array_module, get_sparse_module
  from ..array_utils import create_array
  from ..utils import get_order
  from .core import TensorNoInput, TensorLike
  from .array import tensor
label_desc: Use image node_id 1 for calling a global function with example usage: empty(shape, dtype, chunk_size, gpu, order) and returns: op