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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