Can I write a custom layer in tensorflow in python with existing ops such as conv2d and tensor operations?
<p>As stated in the title, I want to implement a custom layer in tensorflow with the existing ops and tensor operations. I wonder if I can do it in python just like what can be done in theano. In this layer, the input may be some matrices, the batch input and some weights and biases need to be learned. After some tensor operations, the output will be fed to the following layer. The computation in this layer may be complex, so I wonder if tensorflow can do auto-diff for me.</p>