feevos commented on issue #16736:
URL:
https://github.com/apache/incubator-mxnet/issues/16736#issuecomment-698848735
Dear all,
using the new version of mxnet (2.0) solves this problem:
```python
In [1]: import mxnet as mx
...: from mxnet import nd, gluon
...: from mxnet.gluon import HybridBlock
...: from mxnet import np, npx
...: npx.set_np()
...: class Demo(HybridBlock):
...: def __init__(self, kernel_sizes = [3]*17,**kwards):
...: super().__init__(**kwards)
...:
...:
...: self.net = gluon.nn.HybridSequential()
...: for k in kernel_sizes:
...:
self.net.add(gluon.nn.Conv2D(32,kernel_size=k,padding=1))
...:
...: def forward(self,input):
...: x = input
...: for conv in self.net:
...: x = x + conv(input)
...:
...: return x
...:
...: # This reproduces the error.
...: nfilters=32
...: F = 256
...:
...: net = Demo(kernel_sizes=[3]*7) # <=== CHANGE HERE, for length of
list < 7 this script runs fine.
...: net.initialize()
...: net.hybridize()
...: xx = np.random.rand(7,nfilters,F,F)
...: out = net(xx)
/usr/local/lib/python3.7/site-packages/joblib/_multiprocessing_helpers.py:45:
UserWarning: [Errno 28] No space left on device. joblib will operate in serial
mode
warnings.warn('%s. joblib will operate in serial mode' % (e,))
[18:14:54] ../src/storage/storage.cc:199: Using Pooled (Naive)
StorageManager for CPU
In [2]: out = net(xx)
In [3]: out.shape
Out[3]: (7, 32, 256, 256)
```
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