khaotik commented on issue #6526:
URL:
https://github.com/apache/incubator-mxnet/issues/6526#issuecomment-790279925
Hi, I'm looking for simple issues for my first PR. Upon reviewing C++ code,
it seems this issue is already resolved, or am I missing anything?
I also made a small test case:
```python
#!/usr/bin/env python
from itertools import product
import numpy as np
import mxnet as mx
CTX_LIST = [mx.gpu(), mx.cpu()]
DTYPE_LIST = ['float16', 'float32', 'float64']
for CTX, DTYPE in product(CTX_LIST, DTYPE_LIST):
with mx.autograd.record():
v_x = mx.nd.random.uniform(
-1., 1., shape=(4,5,6),
dtype=DTYPE, ctx=CTX)
v_x.attach_grad(grad_req='add')
v_x.grad[:] = 0.
v_y = mx.nd.swapaxes(v_x, 1, 2)
v_err = mx.nd.square(v_y)
v_err.backward(retain_graph=True)
v_y = mx.nd.swapaxes(v_x, 0, 1)
v_err = mx.nd.square(v_y)
v_err.backward(retain_graph=True)
v_y = mx.nd.swapaxes(v_x, 0, 2)
v_err = mx.nd.square(v_y)
v_err.backward(retain_graph=True)
assert(np.allclose(v_x.asnumpy()*6, v_x.grad.asnumpy()))
```
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