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