Ok, it works now. Thanks!
On Sunday, July 9, 2017 at 2:32:30 PM UTC-8, Alexander Botev wrote:
>
> If you look at the error the shapes don't match. the conv_out is
> 1x32x16x16 while the bias is 1x1x1x32.
> I guess your bias you did wrong the dimshuffle.
>
> On Saturday, 8 July 2017 01:53:58 UTC+1, zxzh...@gmail.com wrote:
>>
>> conv_out is the output of dnn.dnn_conv. I tried to add the bias to the
>> w^T*x. But it reports me an error:
>>
>>
>>
>> Running network...
>> Traceback (most recent call last):
>>
>> File "<ipython-input-8-b830fbb18105>", line 1, in <module>
>>
>> runfile('/space/xzhang/git_cnn_conversion/MyLasagneCode_CIFAR10/test_convnet_binary_bias.py',
>>
>> wdir='/space/xzhang/git_cnn_conversion/MyLasagneCode_CIFAR10')
>>
>> File
>> "/space/xzhang/anaconda2/lib/python2.7/site-packages/spyder/utils/site/sitecustomize.py",
>>
>> line 866, in runfile
>> execfile(filename, namespace)
>>
>> File
>> "/space/xzhang/anaconda2/lib/python2.7/site-packages/spyder/utils/site/sitecustomize.py",
>>
>> line 94, in execfile
>> builtins.execfile(filename, *where)
>>
>> File
>> "/space/xzhang/git_cnn_conversion/MyLasagneCode_CIFAR10/test_convnet_binary_bias.py",
>>
>> line 161, in <module>
>> main(**kargs)
>>
>> File
>> "/space/xzhang/git_cnn_conversion/MyLasagneCode_CIFAR10/test_convnet_binary_bias.py",
>>
>> line 107, in main
>> dt=dt, max_rate=1000, proc_fn=get_output, reset_fn=final_dense)
>>
>> File "spike_tester_theano.py", line 128, in run_tester
>> out_mem, t, Ntransmittedspikes, conv1_spikes, conv2_spikes,
>> conv3_spikes = proc_fn(inp_images.astype('float32'), float(t))
>>
>> File
>> "/space/xzhang/anaconda2/lib/python2.7/site-packages/theano/compile/function_module.py",
>>
>> line 898, in __call__
>> storage_map=getattr(self.fn, 'storage_map', None))
>>
>> File
>> "/space/xzhang/anaconda2/lib/python2.7/site-packages/theano/gof/link.py",
>> line 325, in raise_with_op
>> reraise(exc_type, exc_value, exc_trace)
>>
>> File
>> "/space/xzhang/anaconda2/lib/python2.7/site-packages/theano/compile/function_module.py",
>>
>> line 884, in __call__
>> self.fn() if output_subset is None else\
>>
>>
>> ValueError: GpuElemwise. Input dimension mis-match. Input 1 (indices
>> start at 0) has shape[3] == 32, but the output's size on that axis is 16.
>> Apply node that caused the error: GpuElemwise{Add}[(0,
>> 0)]<gpuarray>(GpuSubtensor{::, ::, int64:int64:, int64:int64:}.0,
>> InplaceGpuDimShuffle{x,x,x,0}.0)
>> Toposort index: 250
>> Inputs types: [GpuArrayType<None>(float32, 4D),
>> GpuArrayType<None>(float32, (True, True, True, False))]
>> Inputs shapes: [(1, 32, 16, 16), (1, 1, 1, 32)]
>> Inputs strides: [(51200, 1600, 80, 4), (128, 128, 128, 4)]
>> Inputs values: ['not shown', 'not shown']
>> Outputs clients: [[HostFromGpu(gpuarray)(GpuElemwise{Add}[(0,
>> 0)]<gpuarray>.0)]]
>>
>> HINT: Re-running with most Theano optimization disabled could give you a
>> back-trace of when this node was created. This can be done with by setting
>> the Theano flag 'optimizer=fast_compile'. If that does not work, Theano
>> optimizations can be disabled with 'optimizer=None'.
>> HINT: Use the Theano flag 'exception_verbosity=high' for a debugprint and
>> storage map footprint of this apply node.
>>
>
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