[GitHub] lionel92 opened a new issue #10807: Asnumpy() error with gluon dense under both GPU/CPU/MKLDNN environment

[GitBox <gi...@apache.org>]

lionel92 opened a new issue #10807: Asnumpy() error with gluon dense under both GPU/CPU/MKLDNN  environment
URL: https://github.com/apache/incubator-mxnet/issues/10807
 
 
   ## Description
   I try to use gluon API to test mkldnn while an error occurs when do asnumpy() operation after the network's backward propogation. So I performed the test under gpu and native cpu environment, and the error still exists.
   You can run the following mininum example to reproduce the error.
   
   ```
   import mxnet as mx
   from mxnet import gluon
   from mxnet.gluon import nn
   from mxnet.test_utils import assert_almost_equal
   from common import setup_module, with_seed
   import numpy as np
   import random
   from nose.tools import raises
   
   #mx.Context.default_ctx = mx.Context('gpu', 0)
   mx.Context.default_ctx = mx.Context('cpu', 0)
   
   layer = nn.Dense(1000)
   x = mx.nd.random.uniform(shape=(16, 128, 300, 300))
   #x = mx.nd.random.uniform(shape=(1, 2, 30, 30))
   x.attach_grad()
   layer.collect_params().initialize()
   with mx.autograd.record():
       out = layer(x)
   out.backward()
   print x.grad.shape
   print x.grad.asnumpy().shape
   ```
   
   Error message:
    print x.grad.asnumpy().shape
     File "/home/linliu/mxnet_gpu/incubator-mxnet/python/mxnet/ndarray/ndarray.py", line 1876, in asnumpy
       ctypes.c_size_t(data.size)))
     File "/home/linliu/mxnet_gpu/incubator-mxnet/python/mxnet/base.py", line 149, in check_call
       raise MXNetError(py_str(_LIB.MXGetLastError()))
   mxnet.base.MXNetError:  ([04:25:06] include/mxnet/././tensor_blob.h:257: Check failed: this->shape_.Size() == shape.Size() (11520000000 vs. 2930065408) TBlob.get_with_shape: new and old shape do not match total elements
   

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