title: AssertionError: Torch not compiled with CUDA enabled
body: <p>From <a href="https://pytorch.org/" rel="noreferrer">https://pytorch.org/</a></p>
  
  <p>to install pytorch on MacOS the following is stated : </p>
  
  <pre><code>conda install pytorch torchvision -c pytorch
  # MacOS Binaries dont support CUDA, install from source if CUDA is needed
  </code></pre>
  
  <p>Why would want to install pytorch without cuda enabled ?</p>
  
  <p>Reason I ask is I receive error : </p>
  
  <blockquote>
    <p>--------------------------------------------------------------------------- AssertionError                            Traceback (most recent call
    last)  in ()
         78 #     predicted = outputs.data.max(1)[1]
         79 
    ---> 80     output = model(torch.tensor([[1,1]]).float().cuda())
         81     predicted = output.data.max(1)[1]
         82 </p>
    
    <p>~/anaconda3/lib/python3.6/site-packages/torch/cuda/<strong>init</strong>.py in
    _lazy_init()
        159         raise RuntimeError(
        160             "Cannot re-initialize CUDA in forked subprocess. " + msg)
    --> 161     _check_driver()
        162     torch._C._cuda_init()
        163     _cudart = _load_cudart()</p>
    
    <p>~/anaconda3/lib/python3.6/site-packages/torch/cuda/<strong>init</strong>.py in
    _check_driver()
         73 def _check_driver():
         74     if not hasattr(torch._C, '_cuda_isDriverSufficient'):
    ---> 75         raise AssertionError("Torch not compiled with CUDA enabled")
         76     if not torch._C._cuda_isDriverSufficient():
         77         if torch._C._cuda_getDriverVersion() == 0:</p>
    
    <p>AssertionError: Torch not compiled with CUDA enabled</p>
  </blockquote>
  
  <p>when attempting to execute code : </p>
  
  <pre><code>x = torch.tensor([[0,0] , [0,1] , [1,0]]).float()
  print(x)
  
  y = torch.tensor([0,1,1]).long()
  print(y)
  
  my_train = data_utils.TensorDataset(x, y)
  my_train_loader = data_utils.DataLoader(my_train, batch_size=2, shuffle=True)
  
  # Device configuration
  device = 'cpu'
  print(device)
  
  # Hyper-parameters 
  input_size = 2
  hidden_size = 100
  num_classes = 2
  
  
  learning_rate = 0.001
  
  train_dataset = my_train
  
  train_loader = my_train_loader
  
  pred = []
  
  
  for i in range(0 , model_iters) : 
      # Fully connected neural network with one hidden layer
      class NeuralNet(nn.Module):
          def __init__(self, input_size, hidden_size, num_classes):
              super(NeuralNet, self).__init__()
              self.fc1 = nn.Linear(input_size, hidden_size) 
              self.relu = nn.ReLU()
              self.fc2 = nn.Linear(hidden_size, num_classes)  
  
          def forward(self, x):
              out = self.fc1(x)
              out = self.relu(out)
              out = self.fc2(out)
              return out
  
      model = NeuralNet(input_size, hidden_size, num_classes).to(device)
  
      # Loss and optimizer
      criterion = nn.CrossEntropyLoss()
      optimizer = torch.optim.Adam(model.parameters(), lr=learning_rate)  
  
      # Train the model
      total_step = len(train_loader)
      for epoch in range(num_epochs):
          for i, (images, labels) in enumerate(train_loader):  
              # Move tensors to the configured device
              images = images.reshape(-1, 2).to(device)
              labels = labels.to(device)
  
              # Forward pass
              outputs = model(images)
              loss = criterion(outputs, labels)
  
              # Backward and optimize
              optimizer.zero_grad()
              loss.backward()
              optimizer.step()
  {:.4f}'.format(epoch+1, num_epochs, i+1, total_step, loss.item()))
  
      output = model(torch.tensor([[1,1]]).float().cuda())
  </code></pre>
  
  <p>To fix this error I need to install pytorch from source with cuda already installed ?</p>