def deconvLayer(self,kernel,outchn,stride=1,pad='SAME',activation=-1,batch_norm=False): self.result = L.deconv2D(self.result,kernel,outchn,'deconv_'+str(self.layernum),stride=stride,pad=pad) if batch_norm: self.result = L.batch_norm(self.result,'batch_norm_'+str(self.layernum),training=self.bntraining,epsilon=self.epsilon) self.layernum+=1 self.inpsize = self.result.get_shape().as_list() self.activate(activation) return self.result
def deconvLayer(self,
kernel,
outchn,
stride=1,
pad='SAME',
activation=-1,
batch_norm=False):
self.result = L.deconv2D(self.result,
kernel,
outchn,
'deconv_' + str(self.layernum),
stride=stride,
pad=pad)
if batch_norm:
self.result = L.batch_norm(self.result,
'batch_norm_' + str(self.layernum))
self.layernum += 1
self.inpsize[1] *= stride
self.inpsize[2] *= stride
self.inpsize[3] = outchn
self.activate(activation)
return [self.result, list(self.inpsize)]