<commit_before>require 'torch'
require 'image'
require 'pl' -- this is somehow responsible for lapp working in qlua mode
require 'paths'
ok, DISP = pcall(require, 'display')
if not ok then print('display not found. unable to plot') end
ADVERSARIAL = require 'adversarial'
DATASET = require 'dataset'
NN_UTILS = require 'utils.nn_utils'
MODELS = require 'models_ratio15'


----------------------------------------------------------------------
-- parse command-line options
OPT = lapp[[
  --save             (default "logs")       subdirectory to save logs
  --saveFreq         (default 30)           save every saveFreq epochs
  --network          (default "")           reload pretrained network
  --V_dir            (default "logs")       Directory where V networks are saved
  --G_pretrained_dir (default "logs")
  --noplot                                  plot while training
  --D_sgd_lr         (default 0.02)         D SGD learning rate
  --G_sgd_lr         (default 0.02)         G SGD learning rate
  --D_sgd_momentum   (default 0)            D SGD momentum
  --G_sgd_momentum   (default 0)            G SGD momentum
  --batchSize        (default 32)           batch size
  --N_epoch          (default 1000)         Number of examples per epoch (-1 means all)
  --G_L1             (default 0)            L1 penalty on the weights of G
  --G_L2             (default 0e-6)         L2 penalty on the weights of G
  --D_L1             (default 0e-7)         L1 penalty on the weights of D
  --D_L2             (default 1e-4)         L2 penalty on the weights of D
  --D_iterations     (default 1)            number of iterations to optimize D for
  --G_iterations     (default 1)            number of iterations to optimize G for
  --D_maxAcc         (default 1.01)         Deactivate learning of D while above this threshold<commit_msg>Adjusting default images per epoch<commit_after>require 'torch'
require 'image'
require 'pl' -- this is somehow responsible for lapp working in qlua mode
require 'paths'
ok, DISP = pcall(require, 'display')
if not ok then print('display not found. unable to plot') end
ADVERSARIAL = require 'adversarial'
DATASET = require 'dataset'
NN_UTILS = require 'utils.nn_utils'
MODELS = require 'models_ratio15'


----------------------------------------------------------------------
-- parse command-line options
OPT = lapp[[
  --save             (default "logs")       subdirectory to save logs
  --saveFreq         (default 30)           save every saveFreq epochs
  --network          (default "")           reload pretrained network
  --V_dir            (default "logs")       Directory where V networks are saved
  --G_pretrained_dir (default "logs")
  --noplot                                  plot while training
  --D_sgd_lr         (default 0.02)         D SGD learning rate
  --G_sgd_lr         (default 0.02)         G SGD learning rate
  --D_sgd_momentum   (default 0)            D SGD momentum
  --G_sgd_momentum   (default 0)            G SGD momentum
  --batchSize        (default 32)           batch size
  --N_epoch          (default 960)          Number of examples per epoch (-1 means all)
  --G_L1             (default 0)            L1 penalty on the weights of G
  --G_L2             (default 0e-6)         L2 penalty on the weights of G
  --D_L1             (default 0e-7)         L1 penalty on the weights of D
  --D_L2             (default 1e-4)         L2 penalty on the weights of D
  --D_iterations     (default 1)            number of iterations to optimize D for
  --G_iterations     (default 1)            number of iterations to optimize G for
  --D_maxAcc         (default 1.01)         Deactivate learning of D while above this threshold
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