Error on train Faster-RCNN

[KirtoXX]

When I train Faster-RCNN on Mxnet-cu80, it arrise a bug:
mxnet.base.MXNetError: Cannot find argument 'static_alloc', Possible Arguments:
And I cannot use RoiAlign on this addition

[KirtoXX]

Traceback (most recent call last):
File "D:/mxnet-test/train2.py", line 422, in
train(args)
File "D:/mxnet-test/train2.py", line 364, in train
cls_pred, box_pred, roi, samples, matches, rpn_score, rpn_box, anchors = net(data, gt_box)
File "C:\Anaconda3\lib\site-packages\mxnet\gluon\block.py", line 413, in call
return self.forward(*args)
File "C:\Anaconda3\lib\site-packages\mxnet\gluon\block.py", line 621, in forward
return self._call_cached_op(x, *args)
File "C:\Anaconda3\lib\site-packages\mxnet\gluon\block.py", line 522, in _call_cached_op
self._build_cache(*args)
File "C:\Anaconda3\lib\site-packages\mxnet\gluon\block.py", line 483, in _build_cache
self._cached_op = ndarray.CachedOp(out, self._flags)
File "C:\Anaconda3\lib\site-packages\mxnet_ctypes\ndarray.py", line 115, in init
ctypes.byref(self.handle)))
File "C:\Anaconda3\lib\site-packages\mxnet\base.py", line 149, in check_call
raise MXNetError(py_str(_LIB.MXGetLastError()))
mxnet.base.MXNetError: Cannot find argument 'static_alloc', Possible Arguments:

inline_limit : int (non-negative), optional, default=2
Maximum number of operators that can be inlined.
forward_bulk_size : int (non-negative), optional, default=15
Segment size of bulk execution during forward pass.
backward_bulk_size : int (non-negative), optional, default=15
Segment size of bulk execution during backward pass.

Process finished with exit code 1

[zhreshold]

There are some features not in mxnet 1.2.0 release, but you can use pip install mxnet-cuxx --upgrade --pre to install the nightly build of mxnet

[KirtoXX]

Thanks!!!!!!