The indices return by torch.topk is strange.
In my option, if sorted=False, then the returned indices should be sorted, that is the elements in the indices are ascending.
However, in the following example, t2 has something wrong:
2144,  20,  104,  118,  123,  136,  137,  144,  171

>>> import torch
>>> t0 = torch.load('./t0.pt')
>>> t0.shape
torch.Size([2146])
>>> t0
tensor([4.4721, 4.5826, 4.3589,  ..., 4.5826, 3.7417, 4.0000], device='cuda:0')
>>> t1, t2 = torch.topk(t0, 200, dim=0, largest=False, sorted=False)
>>> t1
tensor([3.1623, 3.7417, 3.6056, 3.7417, 3.6056, 3.7417, 3.7417, 3.6056, 3.7417,
        3.7417, 3.6056, 3.6056, 3.3166, 3.7417, 3.6056, 3.7417, 3.7417, 3.6056,
        3.7417, 3.7417, 3.7417, 3.7417, 3.7417, 3.7417, 3.7417, 3.4641, 3.7417,
        3.7417, 3.7417, 3.6056, 3.6056, 3.6056, 3.7417, 3.4641, 3.7417, 3.6056,
        3.7417, 3.7417, 3.6056, 3.1623, 3.7417, 3.4641, 3.7417, 3.7417, 3.7417,
        3.7417, 3.7417, 3.7417, 3.6056, 3.7417, 3.7417, 3.7417, 3.7417, 3.4641,
        3.4641, 3.7417, 3.1623, 3.4641, 3.3166, 3.4641, 3.7417, 3.3166, 3.4641,
        3.6056, 3.3166, 3.3166, 3.3166, 3.7417, 3.3166, 3.7417, 3.3166, 3.7417,
        3.4641, 3.7417, 3.3166, 3.7417, 3.7417, 3.6056, 3.7417, 3.7417, 3.4641,
        3.7417, 3.3166, 3.7417, 3.4641, 3.7417, 3.7417, 3.7417, 3.7417, 3.7417,
        3.4641, 3.7417, 3.1623, 3.4641, 3.7417, 3.3166, 3.7417, 3.7417, 3.3166,
        3.4641, 3.4641, 3.3166, 3.4641, 3.7417, 3.7417, 3.4641, 3.7417, 3.7417,
        3.3166, 3.3166, 3.7417, 3.3166, 3.3166, 3.7417, 3.7417, 3.4641, 3.6056,
        3.7417, 3.7417, 3.4641, 3.7417, 3.7417, 3.4641, 3.3166, 3.7417, 3.7417,
        3.7417, 3.4641, 3.7417, 3.3166, 3.7417, 3.3166, 3.4641, 3.7417, 3.3166,
        3.3166, 3.4641, 3.3166, 3.3166, 3.7417, 3.7417, 3.1623, 3.3166, 3.4641,
        3.7417, 3.7417, 3.3166, 3.7417, 3.4641, 3.3166, 3.4641, 3.6056, 3.7417,
        3.7417, 3.6056, 3.7417, 3.0000, 3.6056, 3.7417, 3.4641, 3.7417, 3.3166,
        3.7417, 3.7417, 3.3166, 3.3166, 3.3166, 3.3166, 2.8284, 3.4641, 3.3166,
        3.7417, 3.7417, 3.6056, 3.6056, 3.6056, 3.7417, 3.7417, 3.6056, 3.3166,
        3.7417, 3.7417, 3.7417, 3.4641, 3.4641, 2.8284, 3.4641, 3.4641, 3.7417,
        3.1623, 3.7417, 3.7417, 3.8730, 3.8730, 3.8730, 3.8730, 3.8730, 3.8730,
        3.8730, 3.8730], device='cuda:0')
>>> t2
tensor([   6,   18,   22,   30,  119,  127,  148,  202,  205,  211,  218,  221,
         241,  249,  259,  281,  282,  288,  296,  312,  339,  366,  439,  503,
         523,  526,  533,  534,  541,  665,  676,  677,  716,  720,  724,  734,
         787,  797,  798,  823,  850,  879,  887,  913,  931,  933,  954,  955,
         969,  978,  997, 1009, 1016, 1038, 1040, 1044, 1046, 1047, 1082, 1083,
        1095, 1131, 1143, 1145, 1163, 1166, 1241, 1254, 1258, 1262, 1272, 1291,
        1295, 1299, 1305, 1306, 1309, 1310, 1313, 1320, 1328, 1331, 1334, 1339,
        1343, 1347, 1357, 1365, 1390, 1400, 1402, 1416, 1417, 1419, 1439, 1456,
        1466, 1474, 1501, 1519, 1530, 1535, 1539, 1608, 1619, 1622, 1626, 1630,
        1636, 1651, 1657, 1665, 1667, 1668, 1671, 1672, 1685, 1686, 1694, 1696,
        1701, 1707, 1713, 1716, 1717, 1732, 1761, 1781, 1785, 1788, 1810, 1821,
        1822, 1832, 1863, 1868, 1880, 1887, 1899, 1907, 1917, 1971, 1973, 1985,
        1996, 1997, 1998, 2000, 2005, 2009, 2016, 2017, 2020, 2021, 2027, 2029,
        2034, 2041, 2042, 2043, 2051, 2056, 2059, 2060, 2062, 2064, 2067, 2068,
        2070, 2072, 2073, 2074, 2075, 2076, 2078, 2080, 2082, 2084, 2087, 2092,
        2099, 2107, 2113, 2119, 2120, 2124, 2130, 2131, 2134, 2138, 2140, 2144,
          20,  104,  118,  123,  136,  137,  144,  171], device='cuda:0')
>>>