f4d6d3ccb846d555ba7dd3cb7488f5f4e9f1f3b9,networks.py,,unet,#Any#Any#Any#Any#Any#,283

Before Change

	skips = [x5,x4,x3,x2,x0]
	for i in xrange(5):
		x = UpSampling2D()(x)
		x = concatenate([x,skips[i]])
		x = myConv(x,nf_dec[i],dropout=(do_dropout and (i<2)))

	return x

After Change

	x = myConv(x6,nf_enc[10])

	skips = [x5,x4,x3,x2,x0]
	skip_nf = [nf_enc[8],nf_enc[6],nf_enc[4],nf_enc[2],nf_enc[0]]

	for i in xrange(5):
		x = UpSampling2D()(x)
		
		nf = min(128,skip_nf[i])

		x_skip = myConv(skips[i],nf)
		x_skip = myConv(x_skip,nf)

		x = concatenate([x,x_skip])
		x = myConv(x,nf_dec[i]) 

Instances