Hi Everyone, I am trying to use strides (subsample) in LeNet example.
So I have just changed:
# convolve input feature maps with filters
conv_out = conv2d(
input=input,
filters=self.W,
filter_shape=filter_shape,
input_shape=image_shape
)
# pool each feature map individually, using maxpooling
pooled_out = pool.pool_2d(
input=conv_out,
ds=poolsize,
ignore_border=True
)
into:
conv_out = conv.conv2d(
input=input,
filters=self.W,
subsample=(2,2),
filter_shape=filter_shape,
input_shape=image_shape
)
# downsample each feature map individually, using maxpooling
pooled_out = pool.pool_2d(
input=conv_out,
ds=poolsize,
ignore_border=True,
mode='max'
)
And I am having the following error:
Traceback (most recent call last):
... building the model
File "/home/beaa/Escritorio/Theano/Lenet_original/ejemploCNN_LeNet.py", line
427, in <module>
evaluate_lenet5()
File "/home/beaa/Escritorio/Theano/Lenet_original/ejemploCNN_LeNet.py", line
193, in evaluate_lenet5
poolsize=(2, 2)ut
File "/home/beaa/Escritorio/Theano/Lenet_original/ejemploCNN_LeNet.py", line
105, in __init__
input_shape=image_shape
File
"/home/beaa/.local/lib/python2.7/site-packages/theano/tensor/nnet/conv.py",
line 151, in conv2d
imshp=imshp, kshp=kshp, nkern=nkern, bsize=bsize, **kargs)
TypeError: __init__() got an unexpected keyword argument 'input_shape'
Also, I would k¡like to know if the 'fanout' variable had to be changed,
because the number of output neurons would not be the same, any ideas?
Thanks for your help.
Regards.
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