def TestLoader(schedule):
return BahamasLoaderPaired(sets=sets,
grouping=grouping,
batch_size=ntest,
ntest=ntest,
transform=transforms,
train_set=False)
def TrainLoader(schedule):
return BahamasLoaderPaired(sets=sets,
grouping=grouping,
batch_size=schedule['batch_size'],
ntest=ntest,
transform=transforms,
train_set=True)
'd_optim_opts': paper_opts,
'sample_interval': 205,
'batch_size': 2,
'epochs': 201,
'save_model_interval': None,
'save_img_interval': None,
'save_dir': os.getenv('SDIR') + '/patchgan_variations/patch_70_l1_1_res1/',
'save_summary': {
'epochs': np.arange(10, 210, 10).tolist(),
'box_size': (100,100),
'transform': FCS(k=4, inverse=True),
'n': 4,
'grid_size': (2,2)
}
}
train_loader = BahamasLoaderPaired([os.getenv('D32'), os.getenv('G32')],
batch_size=schedule['batch_size'],
ntest=10,
transform=transform_fcs,
train_set=True)
test_loader = BahamasLoaderPaired([os.getenv('D32'), os.getenv('G32')],
batch_size=10,
ntest=10,
transform=transform_fcs,
train_set=False)
'g_optimizer': 'adam',
'd_optimizer': 'adam',
'g_optim_opts': paper_opts,
'd_optim_opts': paper_opts,
'sample_interval': 100,
'batch_size': 16,
'epochs': epoch_end,
'save_model_interval': None,
'save_img_interval': None,
'save_dir': os.getenv('SDIR') + name,
'save_summary': {
'epochs': np.arange(0, (epoch_end + 1), 5).tolist(),
'box_size': (100, 100),
'n': 4,
'grid_size': (2, 2)
}
}
train_loader = BahamasLoaderPaired(sets=sets,
grouping=grouping,
batch_size=schedule['batch_size'],
ntest=ntest,
transform=transforms,
train_set=True)
test_loader = BahamasLoaderPaired(sets=sets,
batch_size=ntest,
ntest=ntest,
transform=transforms,
train_set=False)