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show_model_content.lua
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show_model_content.lua
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require 'paths'
require 'nn'
require 'cutorch'
require 'cunn'
require 'LeakyReLU'
require 'dpnn'
require 'layers.cudnnSpatialConvolutionUpsample'
require 'stn'
OPT = lapp[[
--save (default "logs") subdirectory in which the model is saved
--network (default "adversarial.net") name of the model file
]]
local filepath = paths.concat(OPT.save, OPT.network)
local tmp = torch.load(filepath)
if tmp.epoch then print("") print("Epoch:") print(tmp.epoch) end
if tmp.opt then print("") print("OPT:") print(tmp.opt) end
if tmp.G then print("") print("G:") print(tmp.G) end
if tmp.G1 then print("") print("G1:") print(tmp.G1) end
if tmp.G2 then print("") print("G2:") print(tmp.G2) end
if tmp.G3 then print("") print("G3:") print(tmp.G3) end
if tmp.D then print("") print("D:") print(tmp.D) end