from keras.applications.vgg16 import VGG16
model=VGG16(include_top=False, weights='imagenet', input_tensor=None,
input_shape=None, pooling=None, classes=1000)
model.summary()
I ran this code very successful on the CPU, but the error on the GPU as
follows:
Using Theano backend.
Using cuDNN version 5105 on context None
Mapped name None to device cuda: GeForce GTX TITAN X (0000:02:00.0)
Traceback (most recent call last):
File "/home/xy/workspace/MyProject/1.py", line 12, in <module>
model=VGG16(include_top=False, weights='imagenet', input_tensor=None,
input_shape=None, pooling=None, classes=1000)
File
"/usr/local/lib/python2.7/dist-packages/Keras-2.0.3-py2.7.egg/keras/applications/vgg16.py",
line 171, in VGG16
layer_utils.convert_all_kernels_in_model(model)
File
"/usr/local/lib/python2.7/dist-packages/Keras-2.0.3-py2.7.egg/keras/utils/layer_utils.py",
line 148, in convert_all_kernels_in_model
K.batch_set_value(to_assign)
File
"/usr/local/lib/python2.7/dist-packages/Keras-2.0.3-py2.7.egg/keras/backend/theano_backend.py",
line 1126, in batch_set_value
x.set_value(np.asarray(value, dtype=x.dtype))
File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/type.py", line
637, in set_value
self.container.value = value
File "/usr/local/lib/python2.7/dist-packages/theano/gof/link.py", line 477,
in __set__
**kwargs)
File "/usr/local/lib/python2.7/dist-packages/theano/gpuarray/type.py", line
296, in filter_inplace
old_data.write(data)
File "pygpu/gpuarray.pyx", line 1655, in pygpu.gpuarray.GpuArray.write
(pygpu/gpuarray.c:20879)
ValueError: ('Destination GpuArray is not contiguous', 'Container name
"block1_conv1/kernel"')
How can i solve it?
my configuration is :
ubuntu 14.04
python 2.7
theano 0.9.0
keras 2.0.3
cudnn 5.1
cuda 7.5
I tried to let VGG16's weights = None，also succeeded. So I guess the data
type of the weight is not compatible with the GPU. But I do not know what
to do with it.
I mentioned the problem in the keras page, get the following answer from
the Owner：
The error occurs when we attempt to set the value of a Theano variable
using a Numpy array, at line
x.set_value(np.asarray(value, dtype=x.dtype))
This appears to be a Theano issue, so you should ask on the Theano mailing
list / repo.
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