1eeb316d66b5ab7c377f1926fc24302dd1e9d418,VAEs/vq-vae/models/vq_vae.py,Model,decoder,#Model#Any#,203

Before Change

	def decoder(self, x):
		with nn.parameter_scope("decoder"):
			out = PF.convolution(x, self.num_hidden, (3,3), stride=(1,1),
				pad=(1,1), name="conv_1", rng=self.rng)
			out = self.decoder_res_stack(out)
			out = PF.deconvolution(out, self.num_hidden//2, (4,4), stride=(2,2),
				pad=(1,1), name="deconv_1", rng=self.rng)

After Change

			out = PF.deconvolution(out, self.num_hidden, (4,4), stride=(2,2),
				pad=(1,1), name="deconv_1", rng=self.rng)
			out = PF.batch_normalization(out)
			out = F.relu(out)
			out = PF.deconvolution(out, self.in_channels, (4,4), stride=(2,2),
				pad=(1,1), name="deconv_2", rng=self.rng) 
			out = F.tanh(out)

		return out

	def __call__(self, img, iteration):

Instances