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)