Hello everyone, I am trying to follow the object recognition tutorial from pytorch
https://pytorch.org/tutorials/intermediate/torchvision_tutorial.html 2. I use Windows 10 with CPU only and I have tried both the pip and the conda install for the torch and torchvision packages (CPU version), however, I keep getting the same error shown below. Any help is greatly appreciated. Cheers.

AssertionError                            Traceback (most recent call last)
 in ()
4 for epoch in range(num_epochs):
5     # train for one epoch, printing every 10 iterations
----> 6     train_one_epoch(model, optimizer, data_loader, device, epoch, print_freq=10)
7     # update the learning rate
8     lr_scheduler.step()
D:\Resources\Pytorch Learn\engine.py in train_one_epoch(model, optimizer, data_loader, device, epoch, print_freq)
24         lr_scheduler = utils.warmup_lr_scheduler(optimizer, warmup_iters, warmup_factor)
25
—> 26     for images, targets in metric_logger.log_every(data_loader, print_freq, header):
27         images = list(image.to(device) for image in images)
28         targets = [{k: v.to(device) for k, v in t.items()} for t in targets]
D:\Resources\Pytorch Learn\utils.py in log_every(self, iterable, print_freq, header)
210                     meters=str(self),
211                     time=str(iter_time), data=str(data_time),
–> 212                     memory=torch.cuda.max_memory_allocated() / MB))
213             i += 1
214             end = time.time()
C:\Users\Marinos\Anaconda3\lib\site-packages\torch\cuda\memory.py in max_memory_allocated(device)
298         management.
299     “”"
–> 300     return memory_stats(device=device)[“allocated_bytes.all.peak”]
301
302
C:\Users\Marinos\Anaconda3\lib\site-packages\torch\cuda\memory.py in memory_stats(device)
157             result.append((prefix, obj))
158
–> 159     stats = memory_stats_as_nested_dict(device=device)
160     _recurse_add_to_result("", stats)
161     result.sort()
C:\Users\Marinos\Anaconda3\lib\site-packages\torch\cuda\memory.py in memory_stats_as_nested_dict(device)
166 def memory_stats_as_nested_dict(device=None):
167     r""“Returns the result of :func:~torch.cuda.memory_stats as a nested dictionary.”""
–> 168     device = _get_device_index(device, optional=True)
169     return torch._C._cuda_memoryStats(device)
170
C:\Users\Marinos\Anaconda3\lib\site-packages\torch\cuda_utils.py in _get_device_index(device, optional)
29         if optional:
30             # default cuda device index
—> 31             return torch.cuda.current_device()
32         else:
33             raise ValueError('Expected a cuda device with a specified index ’
C:\Users\Marinos\Anaconda3\lib\site-packages\torch\cuda_init_.py in current_device()
328 def current_device():
329     r""“Returns the index of a currently selected device.”""
–> 330     _lazy_init()
331     return torch._C._cuda_getDevice()
332
C:\Users\Marinos\Anaconda3\lib\site-packages\torch\cuda_init_.py in _lazy_init()
147             raise RuntimeError(
148                 "Cannot re-initialize CUDA in forked subprocess. " + msg)
–> 149         _check_driver()
150         if _cudart is None:
151             raise AssertionError(
C:\Users\Marinos\Anaconda3\lib\site-packages\torch\cuda_init_.py in _check_driver()
45 def _check_driver():
46     if not hasattr(torch._C, ‘_cuda_isDriverSufficient’):
—> 47         raise AssertionError(“Torch not compiled with CUDA enabled”)
48     if not torch._C._cuda_isDriverSufficient():
49         if torch._C._cuda_getDriverVersion() == 0:
AssertionError: Torch not compiled with CUDA enabled