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# numpy.asanyarray

`numpy.``asanyarray`(a, dtype=None, order=None)

  Convert the input to an ndarray, but pass ndarray subclasses through.

  Parameters: | a : array_like Input data, in any form that can be converted to an array. This includes scalars, lists, lists of tuples, tuples, tuples of tuples, tuples of lists, and ndarrays. dtype : data-type, optional By default, the data-type is inferred from the input data. order : {‘C’, ‘F’}, optional Whether to use row-major (C-style) or column-major (Fortran-style) memory representation. Defaults to ‘C’.
  Returns: | out : ndarray or an ndarray subclass Array interpretation of a. If a is an ndarray or a subclass of ndarray, it is returned as-is and no copy is performed.

  See also

  `asarray`
    Similar function which always returns ndarrays.
  `ascontiguousarray`
    Convert input to a contiguous array.
  `asfarray`
    Convert input to a floating point ndarray.
  `asfortranarray`
    Convert input to an ndarray with column-major memory order.
  `asarray_chkfinite`
    Similar function which checks input for NaNs and Infs.
  `fromiter`
    Create an array from an iterator.
  `fromfunction`
    Construct an array by executing a function on grid positions.

  Examples

  Convert a list into an array:

      >>> a = [1, 2]
      >>> np.asanyarray(a)
      array([1, 2])

  Instances of `ndarray` subclasses are passed through as-is:

      >>> a = np.matrix([1, 2])
      >>> np.asanyarray(a) is a
      True