def zeros(stype, shape, ctx=None, dtype=None, **kwargs):
    """Return a new array of given shape and type, filled with zeros.

    Parameters
    ----------
    stype: string
        The storage type of the empty array, such as 'row_sparse', 'csr', etc
    shape : int or tuple of int
        The shape of the empty array
    ctx : Context, optional
        An optional device context (default is the current default context)
    dtype : str or numpy.dtype, optional
        An optional value type (default is `float32`)

    Returns
    -------
    RowSparseNDArray or CSRNDArray
        A created array
    Examples
    --------
    >>> mx.nd.sparse.zeros('csr', (1,2))
    <CSRNDArray 1x2 @cpu(0)>
    >>> mx.nd.sparse.zeros('row_sparse', (1,2), ctx=mx.cpu(), dtype='float16').asnumpy()
    array([[ 0.,  0.]], dtype=float16)
    """
    # pylint: disable= no-member, protected-access
    if stype == 'default':
        return _zeros_ndarray(shape, ctx=ctx, dtype=dtype, **kwargs)
    if ctx is None:
        ctx = current_context()
    dtype = mx_real_t if dtype is None else dtype
    if stype in ('row_sparse', 'csr'):
        aux_types = _STORAGE_AUX_TYPES[stype]
    else:
        raise ValueError("unknown storage type" + stype)
    out = _ndarray_cls(_new_alloc_handle(stype, shape, ctx, True, dtype, aux_types))
    return _internal._zeros(shape=shape, ctx=ctx, dtype=dtype, out=out, **kwargs)
def zeros ( stype , shape , ctx = None , dtype = None , ** kwargs ) : if stype == 'default' : return _zeros_ndarray ( shape , ctx = ctx , dtype = dtype , ** kwargs ) if ctx is None : ctx = current_context ( ) dtype = mx_real_t if dtype is None else dtype if stype in ( 'row_sparse' , 'csr' ) : aux_types = _STORAGE_AUX_TYPES [ stype ] else : raise ValueError ( "unknown storage type" + stype ) out = _ndarray_cls ( _new_alloc_handle ( stype , shape , ctx , True , dtype , aux_types ) ) return _internal . _zeros ( shape = shape , ctx = ctx , dtype = dtype , out = out , ** kwargs )
Return a new array of given shape and type, filled with zeros.

    Parameters
    ----------
    stype: string
        The storage type of the empty array, such as 'row_sparse', 'csr', etc
    shape : int or tuple of int
        The shape of the empty array
    ctx : Context, optional
        An optional device context (default is the current default context)
    dtype : str or numpy.dtype, optional
        An optional value type (default is `float32`)

    Returns
    -------
    RowSparseNDArray or CSRNDArray
        A created array
    Examples
    --------
    >>> mx.nd.sparse.zeros('csr', (1,2))
    <CSRNDArray 1x2 @cpu(0)>
    >>> mx.nd.sparse.zeros('row_sparse', (1,2), ctx=mx.cpu(), dtype='float16').asnumpy()
    array([[ 0.,  0.]], dtype=float16)