Issue for cmt_training.py

[ting-chuan-wang]

I run your code, and got an error, please help me. Thank you.

python cmt_training.py --project_path "./results/0927/" --data_path "/home/tingw/mne_data/physionet-sleep-data/multi_epoch/" --train_data_list [0,1,2,3] --val_data_list [4] --model_type "Seq"

The error message is, Traceback (most recent call last): File "/home/tingw/CMTrans/Cross-Modal-Transformer/cmt_training.py", line 155, in main() File "/home/tingw/CMTrans/Cross-Modal-Transformer/cmt_training.py", line 92, in main train_data_loader, val_data_loader = get_dataset(device,args) File "/home/tingw/CMTrans/Cross-Modal-Transformer/datasets/sleep_edf.py", line 412, in get_dataset train_dataset = SleepEDF_Seq_MultiChan_Dataset_Main(eeg_file = train_eeg_list , File "/home/tingw/CMTrans/Cross-Modal-Transformer/datasets/sleep_edf.py", line 223, in init bin_labels = np.bincount(self.labels) ValueError: object too deep for desired array

== LOG below ==  Torch Version : 1.10.0+cu113 Training Arguements ====================================> project_path : ./results/0927/ data_path : /home/tingw/mne_data/physionet-sleep-data/multi_epoch/ train_data_list : ['[0,1,2,3]'] val_data_list : ['[4]'] is_retrain : False model_path :
save_model_freq : 50 model_type : Seq d_model : 128 dim_feedforward : 512 window_size : 50 num_seq : 15 batch_size : 32 weigths : [1.0, 2.0, 1.0, 2.0, 2.0] lr : 0.001 beta_1 : 0.9 beta_2 : 0.999 eps : 1e-09 weight_decay : 0.0001 n_epochs : 200 step_size : 30 gamma : 0.5 is_neptune : False nep_project :
nep_api :
Project directory created at ./results/0927/ Getting Dataset ===================================> ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/x1.h5', '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/x2.h5', '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/x3.h5', '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/x4.h5', '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/x5.h5'] Training Data Files: ===========================> ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/x1.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/x2.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/x3.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/x4.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog1.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog2.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog3.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog4.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/y1.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/y2.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/y3.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/y4.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/mean1.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/mean2.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/mean3.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/mean4.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/std1.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/std2.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/std3.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/std4.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_m1.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_m2.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_m3.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_m4.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_std1.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_std2.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_std3.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_std4.h5'] Validation Data Files: ===========================> ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/x5.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog5.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/y5.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/mean5.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/std5.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_m5.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_std5.h5'] Loading Train Data for many-to-many classification ==================================> Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/x1.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 43455 Shape of each data : (43455, 5, 3000) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog1.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 43455 Shape of each data : (43455, 5, 3000) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/y1.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 43455 Shape of each data : (43455, 5) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/x2.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 39919 Shape of each data : (39919, 5, 3000) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog2.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 39919 Shape of each data : (39919, 5, 3000) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/y2.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 39919 Shape of each data : (39919, 5) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/x3.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 35112 Shape of each data : (35112, 5, 3000) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog3.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 35112 Shape of each data : (35112, 5, 3000) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/y3.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 35112 Shape of each data : (35112, 5) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/x4.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 40211 Shape of each data : (40211, 5, 3000) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog4.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 40211 Shape of each data : (40211, 5, 3000) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/y4.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 40211 Shape of each data : (40211, 5) Traceback (most recent call last): File "/home/tingw/CMTrans/Cross-Modal-Transformer/cmt_training.py", line 155, in main() File "/home/tingw/CMTrans/Cross-Modal-Transformer/cmt_training.py", line 92, in main train_data_loader, val_data_loader = get_dataset(device,args) File "/home/tingw/CMTrans/Cross-Modal-Transformer/datasets/sleep_edf.py", line 412, in get_dataset train_dataset = SleepEDF_Seq_MultiChan_Dataset_Main(eeg_file = train_eeg_list , File "/home/tingw/CMTrans/Cross-Modal-Transformer/datasets/sleep_edf.py", line 223, in init bin_labels = np.bincount(self.labels) ValueError: object too deep for desired array

[Jathurshan0330]

Can you comment out the bin_labels? It is there to check the counts of different classes. I hope it works

[ting-chuan-wang]

Thanks.
I commented out the binlabels. Now it stops at another place. b,, _ = x.shape
ValueError: too many values to unpack (expected 3)

Below I found the issue is that x.shape become 4D data: def forward(self, x: Tensor) -> Tensor: print(">>> forward() In shape: ", x.shape) ### [32, 3000, 5] if x.shape[0]!=1: x = x.squeeze().unsqueeze(dim = 1) ### output [32, 1, 3000, 5]

If I change it to b,, , _ = x.shape The next line is not working. x_1 = self.projection_1(x)

Please help. Thanks.

== LOG below == Torch Version : 1.10.0+cu113 Training Arguements ====================================> project_path : ./results/0930/ data_path : /home/tingw/mne_data/physionet-sleep-data/multi_epoch/ train_data_list : ['[0,1,2,3]'] val_data_list : ['[4]'] is_retrain : False model_path :
save_model_freq : 50 model_type : Seq d_model : 128 dim_feedforward : 512 window_size : 50 num_seq : 15 batch_size : 32 weigths : [1.0, 2.0, 1.0, 2.0, 2.0] lr : 0.001 beta_1 : 0.9 beta_2 : 0.999 eps : 1e-09 weight_decay : 0.0001 n_epochs : 200 step_size : 30 gamma : 0.5 is_neptune : False nep_project :
nep_api :
Project directory already available at ./results/0930/ Getting Dataset ===================================> ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/x1.h5', '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/x2.h5', '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/x3.h5', '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/x4.h5', '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/x5.h5'] Training Data Files: ===========================> ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/x1.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/x2.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/x3.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/x4.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog1.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog2.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog3.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog4.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/y1.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/y2.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/y3.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/y4.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/mean1.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/mean2.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/mean3.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/mean4.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/std1.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/std2.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/std3.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/std4.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_m1.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_m2.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_m3.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_m4.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_std1.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_std2.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_std3.h5' '/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_std4.h5'] Validation Data Files: ===========================> ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/x5.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog5.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/y5.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/mean5.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/std5.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_m5.h5'] ['/home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_std5.h5'] Loading Train Data for many-to-many classification ==================================> Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/x1.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 43455 Shape of each data : (43455, 5, 3000) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog1.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 43455 Shape of each data : (43455, 5, 3000) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/y1.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 43455 Shape of each data : (43455, 5) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/x2.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 39919 Shape of each data : (39919, 5, 3000) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog2.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 39919 Shape of each data : (39919, 5, 3000) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/y2.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 39919 Shape of each data : (39919, 5) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/x3.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 35112 Shape of each data : (35112, 5, 3000) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog3.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 35112 Shape of each data : (35112, 5, 3000) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/y3.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 35112 Shape of each data : (35112, 5) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/x4.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 40211 Shape of each data : (40211, 5, 3000) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog4.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 40211 Shape of each data : (40211, 5, 3000) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/y4.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 40211 Shape of each data : (40211, 5) Shape of EEG : (158697, 5, 3000) , EOG : (158697, 5, 3000) Shape of Labels : torch.Size([158697, 5]) Reading Subject wise mean and sd Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/mean1.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 43455 Shape of each data : (43455,) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/std1.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 43455 Shape of each data : (43455,) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_m1.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 43455 Shape of each data : (43455,) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_std1.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 43455 Shape of each data : (43455,) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/mean2.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 39919 Shape of each data : (39919,) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/std2.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 39919 Shape of each data : (39919,) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_m2.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 39919 Shape of each data : (39919,) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_std2.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 39919 Shape of each data : (39919,) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/mean3.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 35112 Shape of each data : (35112,) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/std3.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 35112 Shape of each data : (35112,) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_m3.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 35112 Shape of each data : (35112,) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_std3.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 35112 Shape of each data : (35112,) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/mean4.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 40211 Shape of each data : (40211,) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/std4.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 40211 Shape of each data : (40211,) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_m4.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 40211 Shape of each data : (40211,) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_std4.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 40211 Shape of each data : (40211,) Shapes of Mean : EEG: (158697,), EOG : (158697,) Shapes of Sd : EEG: (158697,), EOG : (158697,) Loading Val Data for many-to-many classification ==================================> Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/x5.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 36485 Shape of each data : (36485, 5, 3000) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog5.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 36485 Shape of each data : (36485, 5, 3000) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/y5.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 36485 Shape of each data : (36485, 5) Shape of EEG : (36485, 5, 3000) , EOG : (36485, 5, 3000) Shape of Labels : torch.Size([36485, 5]) Reading Subject wise mean and sd Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/mean5.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 36485 Shape of each data : (36485,) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/std5.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 36485 Shape of each data : (36485,) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_m5.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 36485 Shape of each data : (36485,) Reading from /home/tingw/mne_data/physionet-sleep-data/multi_epoch/eog_std5.h5 ==================================================== Keys in the h5py file : <KeysViewHDF5 ['data']> Number of samples : 36485 Shape of each data : (36485,) Shapes of Mean : EEG: (36485,), EOG : (36485,) Shapes of Sd : EEG: (36485,), EOG : (36485,) EEG batch shape: torch.Size([32, 3000, 15, 5]) EOG batch shape: torch.Size([32, 3000, 15, 5]) Labels batch shape: torch.Size([32, 15, 5]) EEG batch shape: torch.Size([32, 3000, 15, 5]) EOG batch shape: torch.Size([32, 3000, 15, 5]) Labels batch shape: torch.Size([32, 15, 5]) EEG Minimum :-11.41333721330944 EEG Maximum :11.627864012828486 EOG Minimum :-13.291103170514944 EOG Maximum :12.179615041092605 EEG Mean :-9.066378188759094e-05 EEG Standard Deviation :0.9713700974582382 EOG Mean :4.682988494505859e-05 EOG Standard Deviation :0.9103014239304752 Initializing Sequence Cross Modal Transformer ==================> ============================= Training Epoch : [1/200]===============================>

forward() In shape: torch.Size([32, 3000, 5]) forward() shape: torch.Size([32, 1, 3000, 5]) Traceback (most recent call last): File "/home/tingw/CMTrans/Cross-Modal-Transformer/cmt_training.py", line 155, in main() File "/home/tingw/CMTrans/Cross-Modal-Transformer/cmt_training.py", line 152, in main train_seq_cmt(Net, train_data_loader, val_data_loader, criterion, optimizer, lr_scheduler, device, args)
File "/home/tingw/CMTrans/Cross-Modal-Transformer/models/sequence_cmt.py", line 328, in train_seqcmt outputs, = Net(eeg.float().to(device), eog.float().to(device)) File "/home/tingw/anaconda3/envs/CMTrans/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl return forward_call(*input, kwargs) File "/home/tingw/CMTrans/Cross-Modal-Transformer/models/sequence_cmt.py", line 196, in forward epoch_1,feat_1 = self.epoch_1(eeg[:,:,0,:],eog[:,:,0,:])#[0] File "/home/tingw/anaconda3/envs/CMTrans/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl return forward_call(*input, *kwargs) File "/home/tingw/CMTrans/Cross-Modal-Transformer/models/sequence_cmt.py", line 39, in forward self_eeg = self.eeg_atten(eeg) File "/home/tingw/anaconda3/envs/CMTrans/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl return forward_call(input, kwargs) File "/home/tingw/CMTrans/Cross-Modal-Transformer/models/model_blocks.py", line 147, in forward src = self.window_embed(x) File "/home/tingw/anaconda3/envs/CMTrans/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl return forward_call(*input, **kwargs) File "/home/tingw/CMTrans/Cross-Modal-Transformer/models/modelblocks.py", line 107, in forward b,, _ = x.shape
ValueError: too many values to unpack (expected 3)

[Jathurshan0330]

x should be three dimensional, can you share the shape of x given as input

[ting-chuan-wang]

The input x was [32, 3000, 5] but x = x.squeeze().unsqueeze(dim = 1) change it to 4D [32, 1, 3000, 5]