I am now running a Python program using Pytorch. I use my own dataset, not torch.data.dataset. I download data from a pickle file extracted from feature extraction. But the following errors appear: Traceback (most recent call last): File "C:\Users\hp\Downloads\efficient_densenet_pytorch-master\demo-emotion.py", line 326, in <module> fire.Fire(demo) File "C:\Users\hp\Anaconda3\envs\tf-gpu\lib\site-packages\fire\core.py", line 138, in Fire component_trace = _Fire(component, args, parsed_flag_args, context, name) File "C:\Users\hp\Anaconda3\envs\tf-gpu\lib\site-packages\fire\core.py", line 468, in _Fire target=component.__name__) File "C:\Users\hp\Anaconda3\envs\tf-gpu\lib\site-packages\fire\core.py", line 672, in _CallAndUpdateTrace component = fn(*varargs, **kwargs) File "C:\Users\hp\Downloads\efficient_densenet_pytorch-master\demo-emotion.py", line 304, in demo train(model,train_set1, valid_set=valid_set, test_set=test1, save=save, n_epochs=n_epochs,batch_size=batch_size,seed=seed) File "C:\Users\hp\Downloads\efficient_densenet_pytorch-master\demo-emotion.py", line 172, in train n_epochs=n_epochs, File "C:\Users\hp\Downloads\efficient_densenet_pytorch-master\demo-emotion.py", line 37, in train_epoch loader=np.asarray(list(loader)) File "C:\Users\hp\Anaconda3\envs\tf-gpu\lib\site-packages\torch\utils\data\dataloader.py", line 345, in __next__ data = self._next_data() File "C:\Users\hp\Anaconda3\envs\tf-gpu\lib\site-packages\torch\utils\data\dataloader.py", line 385, in _next_data data = self._dataset_fetcher.fetch(index) # may raise StopIteration File "C:\Users\hp\Anaconda3\envs\tf-gpu\lib\site-packages\torch\utils\data\_utils\fetch.py", line 44, in fetch data = [self.dataset[idx] for idx in possibly_batched_index] File "C:\Users\hp\Anaconda3\envs\tf-gpu\lib\site-packages\torch\utils\data\_utils\fetch.py", line 44, in <listcomp> data = [self.dataset[idx] for idx in possibly_batched_index] File "C:\Users\hp\Anaconda3\envs\tf-gpu\lib\site-packages\torch\utils\data\dataset.py", line 257, in __getitem__ return self.dataset[self.indices[idx]] TypeError: 'DataLoader' object is not subscriptable The code is: train_set1 = Owndata() train1, test1 = train_set1 .get_splits() # prepare data loaders train_dl = torch.utils.data.DataLoader(train1, batch_size=32, shuffle=True) test_dl =torch.utils.data.DataLoader(test1, batch_size=1024, shuffle=False) test_set1 = Owndata() '''print('test_set# ',test_set)''' if valid_size: valid_set = Owndata() indices = torch.randperm(len(train_set1)) train_indices = indices[:len(indices) - valid_size] valid_indices = indices[len(indices) - valid_size:] train_set1 = torch.utils.data.Subset(train_dl, train_indices) valid_set = torch.utils.data.Subset(valid_set, valid_indices) else: valid_set = None model = DenseNet( growth_rate=growth_rate, block_config=block_config, num_classes=10, small_inputs=True, efficient=efficient, ) train(model,train_set1, valid_set=valid_set, test_set=test1, save=save, n_epochs=n_epochs, batch_size=batch_size, seed=seed) Any help is appreciated! Thanks a lot in advance!! Continue reading...