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Hi @hackiey thanks for your question. The "conv" function used here has an argument "kernel_size" and is by default equal to 1 if not specified. This is actually 1x1 convolution which is same as fully connected network. I just use conv function instead of dense layer because it is more robust with different input ranks. If this sounds confusing, check out here.
The only time "conv" function is actually used for narrow convolution is here where the kernel_size is 5.
The author didn't mention they use conv layer in paper. thanks for any reply!
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