def array(source_array, ctx=None, dtype=None):
    """Creates an array from any object exposing the array interface.

    Parameters
    ----------
    source_array : array_like
        An object exposing the array interface, an object whose `__array__`
        method returns an array, or any (nested) sequence.
    ctx : Context, optional
        Device context (default is the current default context).
    dtype : str or numpy.dtype, optional
        The data type of the output array. The default dtype is ``source_array.dtype``
        if `source_array` is an `NDArray`, `float32` otherwise.

    Returns
    -------
    NDArray, RowSparseNDArray or CSRNDArray
        An array with the same contents as the `source_array`.

    Examples
    --------
    >>> import numpy as np
    >>> mx.nd.array([1, 2, 3])
    <NDArray 3 @cpu(0)>
    >>> mx.nd.array([[1, 2], [3, 4]])
    <NDArray 2x2 @cpu(0)>
    >>> mx.nd.array(np.zeros((3, 2)))
    <NDArray 3x2 @cpu(0)>
    >>> mx.nd.array(np.zeros((3, 2)), mx.gpu(0))
    <NDArray 3x2 @gpu(0)>
    >>> mx.nd.array(mx.nd.zeros((3, 2), stype='row_sparse'))
    <RowSparseNDArray 3x2 @cpu(0)>
    """
    if spsp is not None and isinstance(source_array, spsp.csr.csr_matrix):
        return _sparse_array(source_array, ctx=ctx, dtype=dtype)
    elif isinstance(source_array, NDArray) and source_array.stype != 'default':
        return _sparse_array(source_array, ctx=ctx, dtype=dtype)
    else:
        return _array(source_array, ctx=ctx, dtype=dtype)
Creates an array from any object exposing the array interface.

    Parameters
    ----------
    source_array : array_like
        An object exposing the array interface, an object whose `__array__`
        method returns an array, or any (nested) sequence.
    ctx : Context, optional
        Device context (default is the current default context).
    dtype : str or numpy.dtype, optional
        The data type of the output array. The default dtype is ``source_array.dtype``
        if `source_array` is an `NDArray`, `float32` otherwise.

    Returns
    -------
    NDArray, RowSparseNDArray or CSRNDArray
        An array with the same contents as the `source_array`.

    Examples
    --------
    >>> import numpy as np
    >>> mx.nd.array([1, 2, 3])
    <NDArray 3 @cpu(0)>
    >>> mx.nd.array([[1, 2], [3, 4]])
    <NDArray 2x2 @cpu(0)>
    >>> mx.nd.array(np.zeros((3, 2)))
    <NDArray 3x2 @cpu(0)>
    >>> mx.nd.array(np.zeros((3, 2)), mx.gpu(0))
    <NDArray 3x2 @gpu(0)>
    >>> mx.nd.array(mx.nd.zeros((3, 2), stype='row_sparse'))
    <RowSparseNDArray 3x2 @cpu(0)>