leezu commented on issue #18765:
URL:
https://github.com/apache/incubator-mxnet/issues/18765#issuecomment-662047865
Simpler reproducible example for latest master:
```
import mxnet as mx
from mxnet import gluon
from mxnet.gluon import nn
a = mx.nd.random.uniform(shape=(1,3,224,224))
backbone = gluon.model_zoo.vision.resnet18_v1()
backbone.initialize()
backbone.hybridize()
backbone(a)
# Alternative:
# backbone.reset_ctx(mx.gpu(0))
# b = backbone(a.as_in_context(mx.gpu(0)))
# print([x.shape for x in b])
sym_file, params_file = backbone.export('/tmp/model')
f = gluon.SymbolBlock.imports(sym_file, 'data', params_file)
f.reset_ctx(mx.gpu(0))
b = f(a.as_in_context(mx.gpu(0)))
print([x.shape for x in b])
```
It fails with
```
[18:59:34] ../src/storage/storage.cc:198: Using Pooled (Naive)
StorageManager for CPU
/home/ubuntu/src/mxnet-master/python/mxnet/gluon/block.py:1723: UserWarning:
Cannot decide type for the following arguments. Consider providing them as
input:
data: None
input_sym_arg_type = in_param.infer_type()[0]
[18:59:37] ../src/storage/storage.cc:198: Using Pooled (Naive)
StorageManager for GPU
[(1000,)]
[18:59:38] ../src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running
performance tests to find the best convolution algorithm, this can take a
while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to
disable)
Segmentation fault: 11
zsh: abort (core dumped) python3 symbolblockbug.py
```
However, the following will work:
```
import mxnet as mx
from mxnet import gluon
from mxnet.gluon import nn
a = mx.nd.random.uniform(shape=(1,3,224,224))
backbone = gluon.model_zoo.vision.resnet18_v1()
backbone.initialize()
backbone.hybridize()
# backbone(a)
# Alternative:
backbone.reset_ctx(mx.gpu(0))
b = backbone(a.as_in_context(mx.gpu(0)))
print([x.shape for x in b])
sym_file, params_file = backbone.export('/tmp/model')
f = gluon.SymbolBlock.imports(sym_file, 'data', params_file)
f.reset_ctx(mx.gpu(0))
b = f(a.as_in_context(mx.gpu(0)))
print([x.shape for x in b])
```
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
us...@infra.apache.org
