@dispatch(nelements, np.ndarray)
def compute_up(expr, data, **kwargs):
    axis = expr.axis
    if expr.keepdims:
        shape = tuple(data.shape[i] if i not in axis else 1
                                    for i in range(ndim(expr._child)))
    else:
        shape = tuple(data.shape[i] for i in range(ndim(expr._child))
                      if axis not in i)
    value = np.prod([data.shape[i] for i in axis])
    result = np.empty(shape)
    result.fill(value)
    result = result.astype('int64')

    return result



# Note the use of 'week': 'M8[D]' here.

# We truncate week offsets "manually" in the compute_up implementation by first
# converting to days then multiplying our measure by 7 this simplifies our code
# by only requiring us to calculate the week offset relative to the day of week.
dataset/ETHPy150Open blaze/blaze/blaze/compute/numpy.py/compute_up/swapped operands of `not in`