def ConvUp_single(a_gp, f_gp, moduleStride, paddingStart):
assert f_gp.shape[3] == 1
f_16 = gp.zeros((f_gp.shape[0], f_gp.shape[1], f_gp.shape[2], 16))
f_16[:, :, :, :1] = f_gp
q_gp = ConvNet.convUp(a_gp,
f_16,
moduleStride=moduleStride,
paddingStart=paddingStart)
return q_gp[:1, :, :, :]
def ConvUp(images, filters, moduleStride, paddingStart):
if filters.shape[3] == 1:
filters_16 = gp.zeros(
(filters.shape[0], filters.shape[1], filters.shape[2], 16))
filters_16[:, :, :, :1] = filters
out = ConvNet.convUp(images,
filters_16,
moduleStride=moduleStride,
paddingStart=paddingStart)
return out[:1, :, :, :]
elif filters.shape[3] == 3:
filters_16 = gp.zeros(
(filters.shape[0], filters.shape[1], filters.shape[2], 16))
filters_16[:, :, :, :3] = filters
out = ConvNet.convUp(images,
filters_16,
moduleStride=moduleStride,
paddingStart=paddingStart)
return out[:3, :, :, :]
elif filters.shape[3] % 16 == 0:
return ConvNet.convUp(images, filters, moduleStride, paddingStart)
else:
raise Exception("Filters Mode 16")
