Can only run the HAR dataset; encountering errors when running other datasets.

[lllllllwdwd]

For the Sleep-EDF dataset, the following error is reported:
Traceback (most recent call last):
File "/media/qiu/DataDisk/yue/Raincoat-main (1)/Raincoat-main/main.py", line 37, in
trainer.train()
File "/media/qiu/DataDisk/yue/Raincoat-main (1)/Raincoat-main/trainers/trainer.py", line 113, in train
losses = algorithm.update(src_x, src_y, trg_x)
File "/media/qiu/DataDisk/yue/Raincoat-main (1)/Raincoat-main/algorithms/RAINCOAT.py", line 161, in update
src_feat, out_s = self.feature_extractor(src_x)
File "/home/qiu/anaconda3/envs/sleepstage/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/media/qiu/DataDisk/yue/Raincoat-main (1)/Raincoat-main/algorithms/RAINCOAT.py", line 110, in forward
ef = F.relu(self.bn_freq(self.avg(ef).squeeze()))
File "/home/qiu/anaconda3/envs/sleepstage/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/home/qiu/anaconda3/envs/sleepstage/lib/python3.7/site-packages/torch/nn/modules/batchnorm.py", line 182, in forward
self.eps,
File "/home/qiu/anaconda3/envs/sleepstage/lib/python3.7/site-packages/torch/nn/functional.py", line 2451, in batch_norm
input, weight, bias, running_mean, running_var, training, momentum, eps, torch.backends.cudnn.enabled
RuntimeError: running_mean should contain 100 elements not 600

For the HHAR dataset, the following error is reported:
Traceback (most recent call last):
File "/media/qiu/DataDisk/yue/Raincoat-main (1)/Raincoat-main/main.py", line 37, in
trainer.train()
File "/media/qiu/DataDisk/yue/Raincoat-main (1)/Raincoat-main/trainers/trainer.py", line 113, in train
losses = algorithm.update(src_x, src_y, trg_x)
File "/media/qiu/DataDisk/yue/Raincoat-main (1)/Raincoat-main/algorithms/RAINCOAT.py", line 174, in update
src_pred = self.classifier(src_feat)
File "/home/qiu/anaconda3/envs/sleepstage/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/media/qiu/DataDisk/yue/Raincoat-main (1)/Raincoat-main/models/models.py", line 70, in forward
predictions = self.logits(x)/self.tmp
File "/home/qiu/anaconda3/envs/sleepstage/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/home/qiu/anaconda3/envs/sleepstage/lib/python3.7/site-packages/torch/nn/modules/linear.py", line 114, in forward
return F.linear(input, self.weight, self.bias)
RuntimeError: mat1 and mat2 shapes cannot be multiplied (32x192 and 128x6)

For the WISDM dataset, the following error is reported:
Traceback (most recent call last):
File "/media/qiu/DataDisk/yue/Raincoat-main (1)/Raincoat-main/main.py", line 37, in
trainer.train()
File "/media/qiu/DataDisk/yue/Raincoat-main (1)/Raincoat-main/trainers/trainer.py", line 113, in train
losses = algorithm.update(src_x, src_y, trg_x)
File "/media/qiu/DataDisk/yue/Raincoat-main (1)/Raincoat-main/algorithms/RAINCOAT.py", line 174, in update
src_pred = self.classifier(src_feat)
File "/home/qiu/anaconda3/envs/sleepstage/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/media/qiu/DataDisk/yue/Raincoat-main (1)/Raincoat-main/models/models.py", line 70, in forward
predictions = self.logits(x)/self.tmp
File "/home/qiu/anaconda3/envs/sleepstage/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/home/qiu/anaconda3/envs/sleepstage/lib/python3.7/site-packages/torch/nn/modules/linear.py", line 114, in forward
return F.linear(input, self.weight, self.bias)
RuntimeError: mat1 and mat2 shapes cannot be multiplied (64x256 and 192x6)

Could you please clarify whether there are any parameters that haven't been set, or if there might be some other reasons for this issue?