Zha0q1 opened a new issue #19362:
URL: https://github.com/apache/incubator-mxnet/issues/19362
``` python
import mxnet as mx
from mxnet import np, nd, npx, profiler
import numpy as _np
from mxnet.gluon import HybridBlock
AA = np.random.normal(0, 10, size=(2,5,99999), dtype='float16', ctx=mx.gpu())
BB = np.argmin(AA, 2)
CC = _np.argmin(AA.asnumpy(), 2)
print(BB)
print(CC)
```
outputs:
```
[ 39904 48736 58816
2708 36896 11056
45600 9223372036854775807 8020
9223372036854775807 9223372036854775807 9223372036854775807
9223372036854775807 34176 30160
19456 9223372036854775807 12008
9223372036854775807 52640] @gpu(0)
[39904 48728 58812 2709 36908 11059 45615 69962 8019 68762 83795 96961
89943 34176 30167 19451 65951 12011 75882 52637]
```
This is reproducible on master and 1.7, both on cpu and gpu. This has not
been noticed before because in `test_np_argmin_argmax` we were only using very
small tensors. I added in a large tensor case yesterday and multiple ci failed
https://github.com/apache/incubator-mxnet/pull/19359.
This might be a memory alignment issue. We probably also need to see if any
other operators are affected too.
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