class Config(object): gpu_ids = [0, 1, 2, 3] device = torch.device('cuda:{}'.format(gpu_ids[0])) dataset = 'imagenet' data_root = xtils.get_data_root(data='imagenet') data_augment = {'train': 'rotate-rresize-1crop', 'val': '1resize-1crop', 'imsize': 256, 'insize': 224, 'color': True, 'degree': (0, 0), 'scale': (0.08, 1), 'ratio': (3. / 4, 4. / 3)} arch_name = ['hrnet', 'resnet50', 'resnet152', 'fishnet150', 'scalenet'][-1] arch_kwargs = [hrw18, hrw30, hrw32, vo69, vo72][-2] ckpt_file = os.path.join(xtils.get_pretrained_models(), ['hrnetv2_w18_imagenet_pretrained.pth', 'fishnet150_ckpt.tar', 'resnet50-19c8e357.pth', 'resnet152-b121ed2d.pth', 'scale103-5.09M-71.63-vo69.pth', 'scale59-30.52M-74.86-vo72.pth'][-2]) mgpus_to_sxpu = ['m2s', 's2m', 'none'][-1] image_size = 256 input_size = int(0.875 * image_size) bsize_val = 256 num_workers = 8 print_freq = 20 valid_total_time = 0 random_seed = random.randint(0, 100) or None # 特殊模型的补充字段 mode_custom = False xfc_which = -1
'resume_config': True, 'resume_optimizer': True, 'mgpus_to_sxpu': ['m2s', 's2m', 'none', 'auto'][3], # data config 'dataset': 'cifar10', 'data_info': { 'train_size': train_size, 'val_size': 10000, 'test_size': 5000 }, 'data_root': xtils.get_data_root(data='cifar10'), 'data_augment': { 'train': '1crop-flip', 'val': 'no-aug' }, 'data_kwargs': {}, 'data_workers': 4, # path config 'current_time': '', 'ckpt_suffix': '', # when save a ckpt, u can add a special mark to its filename. 'ckpt_base_dir': xtils.get_base_dir(k='ckpt'),
# device config 'gpu_ids': [0, 1, 2, 3, 4, 5, 6, 7, 8][0:4], # model config 'arch_name': 'srnet', 'arch_kwargs': {}, 'resume': None or '/data1/zhangjp/classify/checkpoints/imagenet/srnet/srnet-exp.sr1' + '/' + 'imagenet-srnet67-ep339-it1701699-acc69.85-best76.20-topv93.11-par32.66M-norm-exp.sr1.ckpt', 'resume_config': True, 'resume_optimizer': True, 'mgpus_to_sxpu': ['m2s', 's2m', 'none', 'auto'][3], # data config 'dataset': 'imagenet', 'data_info': {'train_size': train_size, 'val_size': 10000, 'test_size': 10000}, 'data_root': xtils.get_data_root(data='imagenet'), 'data_augment': {'train': 'rotate-rresize-1crop', 'val': '1resize-1crop', 'imsize': 256, 'insize': 224, 'color': True, 'interp': 'bilinear', 'degree': (0, 0), 'scale': (0.08, 1), 'ratio': (3. / 4, 4. / 3)}, 'data_kwargs': {}, 'data_workers': 24, # path config 'current_time': '', 'ckpt_suffix': '', # when save a ckpt, u can add a special mark to its filename. 'ckpt_base_dir': xtils.get_base_dir(k='ckpt'), 'ckpt_dir': 'auto-setting', 'log_base_dir': xtils.get_base_dir(k='log'), 'log_dir': 'auto-setting', # iter config
# device config 'gpu_ids': [0, 1, 2, 3, 4, 5, 6, 7, 8][0:4], # model config 'arch_name': 'scalenet', 'arch_kwargs': {}, 'resume': None, 'resume_config': True, 'resume_optimizer': True, 'mgpus_to_sxpu': ['m2s', 's2m', 'none', 'auto'][3], # data config 'dataset': 'cifar10', 'data_info': {'train_size': train_size, 'val_size': 10000, 'test_size': 5000}, 'data_root': xtils.get_data_root(data='cifar10'), 'data_augment': {'train': '1crop-flip', 'val': 'no-aug'}, 'data_kwargs': {}, 'data_workers': 4, # path config 'current_time': '', 'ckpt_suffix': '', # when save a ckpt, u can add a special mark to its filename. 'ckpt_base_dir': xtils.get_base_dir(k='ckpt'), 'ckpt_dir': 'auto-setting', 'log_base_dir': xtils.get_base_dir(k='log'), 'log_dir': 'auto-setting', # iter config 'start_iter': 0, 'max_iters': [100 * BN, 90 * BN, 60 * BN, 40 * BN, 120 * BN][0],
# device config 'gpu_ids': [0, 1, 2, 3, 4, 5, 6, 7, 8][0:4], # model config 'arch_name': 'msnet', 'arch_kwargs': {}, 'resume': os.path.join(xtils.get_pretrained_models(), ''), 'resume_config': False, 'resume_optimizer': False, 'mgpus_to_sxpu': ['m2s', 's2m', 'none', 'auto'][3], # data config 'dataset': 'imagenet', 'data_info': {'train_size': train_size, 'val_size': 50000, 'test_size': 50000}, 'data_root': xtils.get_data_root(data='imagenet'), 'data_augment': {'train': 'rotate-rresize-1crop', 'val': '1resize-1crop', 'imsize': 256, 'insize': 224, 'color': True, 'degree': (0, 0), 'scale': (0.08, 1), 'ratio': (3. / 4, 4. / 3)}, 'data_kwargs': {}, 'data_workers': 12, # path config 'current_time': '', 'ckpt_suffix': '', # when save a ckpt, u can add a special mark to its filename. 'ckpt_base_dir': xtils.get_base_dir(k='ckpt'), 'ckpt_dir': 'auto-setting', 'log_base_dir': xtils.get_base_dir(k='log'), 'log_dir': 'auto-setting', # iter config