Experiment directories created
Namespace(act='relu', ae_batch_size=512, ae_epochs=10, ae_fn=None, ae_lr=0.0001, ae_lr_decay=0.99, ae_optimizer='adam', ae_sched='tri', ae_test_every=20, ae_weight_decay=1e-05, alpha=0.001, ckpt_dir='data/exp_dir/stc/Sep25_1910/checkpoints/', conv_oper='sagc', data_dir='data/', dcec_batch_size=512, dcec_epochs=25, dcec_fn=None, dcec_lr=0.0008, dcec_lr_decay=0.98, dcec_optimizer='adam', dcec_sched='tri', dcec_weight_decay=1e-05, debug=False, device='cuda:1', dpmm_fn=None, dropout=0.3, exp_dir='data/exp_dir', gamma=0.6, headless=False, k_init_batch=4, k_init_downsample=1, n_clusters=10, norm_scale=0, num_transform=5, num_workers=8, optimizer='adam', patch_db=False, patch_features=False, patch_size=16, pose_path={'train': 'data/pose/training/tracked_person/', 'test': 'data/pose/testing/tracked_person/'}, pretrain_epochs=0, prop_norm_scale=0, res_batch_size=256, save_results=1, seed=8171635682061488719, seg_len=12, seg_stride=8, train_seg_conf_th=0.0, update_interval=2.0, verbose=1, vid_path={'train': 'data/training/videos/', 'test': 'data/testing/frames/'})
Traceback (most recent call last):
File "stc_train_eval.py", line 141, in
main()
File "stc_train_eval.py", line 60, in main
model = init_fenet(args, backbone)
File "/tank/newhome/wanghui/anomaly_detection/gepc-master/models/fe/fe_model.py", line 27, in init_fenet
**kwargs)
File "/tank/newhome/wanghui/anomaly_detection/gepc-master/models/gcae/gcae.py", line 60, in init
dec_1st_residual=dec_1st_residual)
File "/tank/newhome/wanghui/anomaly_detection/gepc-master/models/gcae/gcae.py", line 138, in gen_ae
self.build_dec(dec_ch_fac, dec_stride, dec_1st_residual=dec_1st_residual)
File "/tank/newhome/wanghui/anomaly_detection/gepc-master/models/gcae/gcae.py", line 169, in build_dec
st_gcn_dec.append(nn.Upsample(scale_factor=(dec_stride[i], 1), mode='bilinear'))
File "/tank/newhome/wanghui/anaconda3/envs/pytorch/lib/python3.7/site-packages/torch/nn/modules/upsampling.py", line 125, in init
self.scale_factor = float(scale_factor) if scale_factor else None
TypeError: float() argument must be a string or a number, not 'tuple'
when I run the code ,there is this error
Experiment directories created Namespace(act='relu', ae_batch_size=512, ae_epochs=10, ae_fn=None, ae_lr=0.0001, ae_lr_decay=0.99, ae_optimizer='adam', ae_sched='tri', ae_test_every=20, ae_weight_decay=1e-05, alpha=0.001, ckpt_dir='data/exp_dir/stc/Sep25_1910/checkpoints/', conv_oper='sagc', data_dir='data/', dcec_batch_size=512, dcec_epochs=25, dcec_fn=None, dcec_lr=0.0008, dcec_lr_decay=0.98, dcec_optimizer='adam', dcec_sched='tri', dcec_weight_decay=1e-05, debug=False, device='cuda:1', dpmm_fn=None, dropout=0.3, exp_dir='data/exp_dir', gamma=0.6, headless=False, k_init_batch=4, k_init_downsample=1, n_clusters=10, norm_scale=0, num_transform=5, num_workers=8, optimizer='adam', patch_db=False, patch_features=False, patch_size=16, pose_path={'train': 'data/pose/training/tracked_person/', 'test': 'data/pose/testing/tracked_person/'}, pretrain_epochs=0, prop_norm_scale=0, res_batch_size=256, save_results=1, seed=8171635682061488719, seg_len=12, seg_stride=8, train_seg_conf_th=0.0, update_interval=2.0, verbose=1, vid_path={'train': 'data/training/videos/', 'test': 'data/testing/frames/'}) Traceback (most recent call last): File "stc_train_eval.py", line 141, in
main()
File "stc_train_eval.py", line 60, in main
model = init_fenet(args, backbone)
File "/tank/newhome/wanghui/anomaly_detection/gepc-master/models/fe/fe_model.py", line 27, in init_fenet
**kwargs)
File "/tank/newhome/wanghui/anomaly_detection/gepc-master/models/gcae/gcae.py", line 60, in init
dec_1st_residual=dec_1st_residual)
File "/tank/newhome/wanghui/anomaly_detection/gepc-master/models/gcae/gcae.py", line 138, in gen_ae
self.build_dec(dec_ch_fac, dec_stride, dec_1st_residual=dec_1st_residual)
File "/tank/newhome/wanghui/anomaly_detection/gepc-master/models/gcae/gcae.py", line 169, in build_dec
st_gcn_dec.append(nn.Upsample(scale_factor=(dec_stride[i], 1), mode='bilinear'))
File "/tank/newhome/wanghui/anaconda3/envs/pytorch/lib/python3.7/site-packages/torch/nn/modules/upsampling.py", line 125, in init
self.scale_factor = float(scale_factor) if scale_factor else None
TypeError: float() argument must be a string or a number, not 'tuple'
when I run the code ,there is this error