Open Zero0zz opened 7 years ago
Hi, thanks for your comment. My implementation is not precisely the same. I followed the techniques described in their paper rather than trying to follow their original source code.
The output of the convolution layers has shape (batch_size, num_nodes, output_size * num_conv)
. The two differences from the author's source code is the batch_size
and num_conv
dimensions. The batch_size
dimension is simply the size of the batches.
I believe the author's code uses batch sizes of 1. Additionally, I enable the possibility of learning multiple separate convolutions, inspired by the way CNN layers typically work on image datasets. By setting num_conv
to something larger than 1 (the default) you can train multiple, separate convolutions (conv_node
s) which are concatenated together as inputs to the next layer. I have observed no improvements by setting num_conv > 1
, but it may be useful for more complex problems.
求一下联系方式,有偿提问。thanks.
I confused with the output_size of conv_layer function.Then I compared the code with the paper. I found that, the output of the feature detectors in the code is not same as the formula in the paper described. Is there something wrong?