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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2020/04/06 14:51:00 UTC
[GitHub] [incubator-mxnet] chinakook opened a new issue #17981: block.export
bug
chinakook opened a new issue #17981: block.export bug
URL: https://github.com/apache/incubator-mxnet/issues/17981
## Description
net.hybridize may optimize out some ops. These ops are alive in nn.Block(also nn.HybridBlock), but its names are not contained in symbol's arg_names list. So ignore these ops except that their name are end with 'running_mean' or 'running_var'.
To fix this, please refer to https://github.com/apache/incubator-mxnet/pull/17970
### Error Message
```/home/bluews/dev/mx/python/mxnet/gluon/block.py:698: UserWarning: Parameter conv3_weight, conv3_bias is not used by any computation. Is this intended?
out = self.forward(*args)
Traceback (most recent call last):
File "/home/xxxxx/dev/U-Net/linux_scripts/little_test.py", line 39, in <module>
net.export('bar')
File "/home/xxxxx/dev/mx/python/mxnet/gluon/block.py", line 1274, in export
assert name in aux_names
AssertionError
```
## To Reproduce
```
import mxnet as mx
from mxnet import gluon
from mxnet.gluon import nn
class Foo(nn.HybridBlock):
def __init__(self):
super(Foo, self).__init__()
self.conv0 = nn.Conv2D(4, 1)
self.conv1 = nn.Conv2D(6, 1)
def hybrid_forward(self, F, x):
x = self.conv0(x)
y = self.conv1(x)
return tuple([x,y])
foo = Foo()
foo.collect_params().initialize()
x = mx.nd.random.uniform(shape=(1,3,64,64))
y = foo(x)
foo.save_parameters('foo.params')
class Bar(nn.HybridBlock):
def __init__(self):
super(Bar, self).__init__()
self.foo = Foo()
self.foo.load_parameters('foo.params')
def hybrid_forward(self, F, x):
return self.foo(x)[0]
net = Bar()
net.collect_params().initialize()
net.hybridize()
x = mx.nd.random.uniform(shape=(1,3,64,64))
y = net(x)
net.export('bar')
```
### Steps to reproduce
(Paste the commands you ran that produced the error.)
1.
2.
## What have you tried to solve it?
1.
2.
## Environment
We recommend using our script for collecting the diagnositc information. Run the following command and paste the outputs below:
```
curl --retry 10 -s https://raw.githubusercontent.com/dmlc/gluon-nlp/master/tools/diagnose.py | python
# paste outputs here
```
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[GitHub] [incubator-mxnet] sxjscience commented on issue #17981: block.export bug
Posted by GitBox <gi...@apache.org>.
sxjscience commented on issue #17981:
URL: https://github.com/apache/incubator-mxnet/issues/17981#issuecomment-640419247
@leezu @yzhliu I'm tagging it as `gluon`, `numpy` and `2.0` because it's the bug of Gluon and also appears in the numpy interface and should be solved in 2.0.
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[GitHub] [incubator-mxnet] sxjscience commented on issue #17981: block.export bug
Posted by GitBox <gi...@apache.org>.
sxjscience commented on issue #17981:
URL: https://github.com/apache/incubator-mxnet/issues/17981#issuecomment-640412921
I can reproduce the error.
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[GitHub] [incubator-mxnet] chinakook commented on issue #17981: block.export bug
Posted by GitBox <gi...@apache.org>.
chinakook commented on issue #17981:
URL: https://github.com/apache/incubator-mxnet/issues/17981#issuecomment-641042696
@sxjscience I made a fix as https://github.com/apache/incubator-mxnet/pull/17970. It may be ugly, but it works fine for me. It would be appreciated if you have better solution.
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[GitHub] [incubator-mxnet] sxjscience commented on issue #17981: block.export bug
Posted by GitBox <gi...@apache.org>.
sxjscience commented on issue #17981:
URL: https://github.com/apache/incubator-mxnet/issues/17981#issuecomment-640418724
@chinakook Thanks for reporting this. I just simplified the example as follows. The root cause is that `conv1` is not used in the computation of `Bar` but still appears in `.collect_params()`. So the symbolic saving breaks here:
https://github.com/apache/incubator-mxnet/blob/e3493e7b47ddcaa6974280ee432c82eb89d0f756/python/mxnet/gluon/block.py#L1281-L1287
```python
import mxnet as mx
from mxnet import gluon
from mxnet.gluon import nn
mx.npx.set_np()
class Foo(nn.HybridBlock):
def __init__(self):
super(Foo, self).__init__()
self.conv0 = nn.Conv2D(4, 1, in_channels=3)
self.conv1 = nn.Conv2D(6, 1, in_channels=4)
def hybrid_forward(self, F, x):
x = self.conv0(x)
y = self.conv1(x)
return tuple([x,y])
class Bar(nn.HybridBlock):
def __init__(self):
super(Bar, self).__init__()
with self.name_scope():
self.foo = Foo()
def hybrid_forward(self, F, x):
return self.foo(x)[0]
net = Bar()
net.hybridize()
net.initialize()
x = mx.np.random.uniform(0, 1, (1,3,64,64))
y = net(x)
print(y)
net.export('bar')
```
Error:
```
~/.local/lib/python3.6/site-packages/mxnet/gluon/block.py in export(self, path, epoch, remove_amp_cast)
1284 arg_dict['arg:%s'%name] = param._reduce()
1285 else:
-> 1286 assert name in aux_names
1287 arg_dict['aux:%s'%name] = param._reduce()
1288 save_fn = _mx_npx.save if is_np_array() else ndarray.save
AssertionError:
```
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[GitHub] [incubator-mxnet] leezu commented on issue #17981: block.export bug
Posted by GitBox <gi...@apache.org>.
leezu commented on issue #17981:
URL: https://github.com/apache/incubator-mxnet/issues/17981#issuecomment-683894680
https://discuss.mxnet.io/t/assertion-error-for-aux-state-when-exporting-model-with-dangling-layer/6549 faces the same issue
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