Add codes to evaluate the FLOPs and parameters for ResNeSt
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								exps/experimental/test-resnest.py
									
									
									
									
									
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								exps/experimental/test-resnest.py
									
									
									
									
									
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| ##################################################### | ||||
| # Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2019.01 # | ||||
| ##################################################### | ||||
| #  | ||||
| import sys, time, torch, random, argparse | ||||
| from PIL     import ImageFile | ||||
| ImageFile.LOAD_TRUNCATED_IMAGES = True | ||||
| from copy    import deepcopy | ||||
| from pathlib import Path | ||||
|  | ||||
| lib_dir = (Path(__file__).parent / '..' / '..' / 'lib').resolve() | ||||
| if str(lib_dir) not in sys.path: sys.path.insert(0, str(lib_dir)) | ||||
| from utils        import get_model_infos | ||||
|  | ||||
| torch.hub.list('zhanghang1989/ResNeSt', force_reload=True) | ||||
|  | ||||
| for model_name, xshape in [('resnest50', (1,3,224,224)), | ||||
|                            ('resnest101', (1,3,256,256)), | ||||
|                            ('resnest200', (1,3,320,320)), | ||||
|                            ('resnest269', (1,3,416,416))]: | ||||
|   # net = torch.hub.load('zhanghang1989/ResNeSt', model_name, pretrained=True) | ||||
|   net = torch.hub.load('zhanghang1989/ResNeSt', model_name, pretrained=False) | ||||
|   print('Model : {:}, input shape : {:}'.format(model_name, xshape)) | ||||
|   flops, param  = get_model_infos(net, xshape) | ||||
|   print('flops  : {:.3f}M'.format(flops)) | ||||
|   print('params : {:.3f}M'.format(param)) | ||||
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