| | import numba |
| |
|
| |
|
| | @numba.jit( |
| | numba.void( |
| | numba.int32[:, :, ::1], |
| | numba.float32[:, :, ::1], |
| | numba.int32[::1], |
| | numba.int32[::1], |
| | ), |
| | nopython=True, |
| | nogil=True, |
| | ) |
| | def maximum_path_jit(paths, values, t_ys, t_xs): |
| | b = paths.shape[0] |
| | max_neg_val = -1e9 |
| | for i in range(int(b)): |
| | path = paths[i] |
| | value = values[i] |
| | t_y = t_ys[i] |
| | t_x = t_xs[i] |
| |
|
| | v_prev = v_cur = 0.0 |
| | index = t_x - 1 |
| |
|
| | for y in range(t_y): |
| | for x in range(max(0, t_x + y - t_y), min(t_x, y + 1)): |
| | if x == y: |
| | v_cur = max_neg_val |
| | else: |
| | v_cur = value[y - 1, x] |
| | if x == 0: |
| | if y == 0: |
| | v_prev = 0.0 |
| | else: |
| | v_prev = max_neg_val |
| | else: |
| | v_prev = value[y - 1, x - 1] |
| | value[y, x] += max(v_prev, v_cur) |
| |
|
| | for y in range(t_y - 1, -1, -1): |
| | path[y, index] = 1 |
| | if index != 0 and ( |
| | index == y or value[y - 1, index] < value[y - 1, index - 1] |
| | ): |
| | index = index - 1 |
| |
|
