

def hstack(blocks, format=None, dtype=None):
    '\n    Stack sparse matrices horizontally (column wise).\n\n    This wrap the method hstack from scipy.\n\n    Parameters\n    ----------\n    blocks\n        List of sparse array of compatible shape.\n    format\n        String representing the output format. Default is csc.\n    dtype\n        Output dtype.\n\n    Returns\n    -------\n    array\n        The concatenation of the sparse array column wise.\n\n    Notes\n    -----\n    The number of line of the sparse matrix must agree.\n\n    The grad implemented is regular, i.e. not structured.\n\n    '
    blocks = [as_sparse_variable(i) for i in blocks]
    if (dtype is None):
        dtype = theano.scalar.upcast(*[i.dtype for i in blocks])
    return HStack(format=format, dtype=dtype)(*blocks)

dataset/ETHPy150Open rizar/attention-lvcsr/libs/Theano/theano/sparse/basic.py hstack/original