title: TypeError: reshape(): argument 'input' (position 1) must be Tensor, not numpy.ndarray
body: <p>I am a high school student who doesn't having much experience in using PyTorch and LIME. I'm having a lot of trouble with my image shape. Initially my image shape was (3,224,224), however the LIME algorithm only works with images that are in this shape(...,...,3). As a result, I tried transposing the image earlier. It seemed that I made some more progress by doing that, however, now I am getting a different error. Here is some of my code to understand what I have been doing before the error came up.</p>
  <pre><code>def get_preprocess_transform():    
  transf = transforms.Compose([
    #  transforms.ToPILImage(), #had to convert image to PIL as error was showing up two cells below about needing it in pil
      transforms.Resize(input_size),
      transforms.CenterCrop(input_size),
      transforms.ToTensor(),
      transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),
      
  ])    
  
  return transf    
  
  preprocess_transform = get_preprocess_transform() ## use your data_transform but in a method version
  </code></pre>
  <pre><code>def batch_predict(image):
      model_ft.eval()
      batch = torch.reshape(image,(1,3,224,224))
      print(type(batch))
      
      
      
      logits = model_ft(batch)
      probs = F.softmax(logits, dim=1)
      return probs.detach().cpu().numpy()
  
  </code></pre>
  <pre><code>print(img_t.shape)
  img_t = torch.reshape(img_t,(1,3,224,224))
  test_pred = batch_predict(img_t)
  test_pred.squeeze().argmax()
  </code></pre>
  <pre><code>img_t = np.ones((3, 224, 224))
  np.transpose(img_t, (2,1,0)).shape
  </code></pre>
  <pre><code>img_x = np.transpose(img_t, (2, 1, 0))
  print(img_x.shape)
  </code></pre>
  <pre><code>from lime import lime_image
  </code></pre>
  <pre><code>explainer = lime_image.LimeImageExplainer()
  explanation = explainer.explain_instance(img_x, ## pass your image, do not transform
                                          batch_predict, # classification function
                                          top_labels=5, 
                                          hide_color=0, 
                                          num_samples=1000)
  </code></pre>
  <p><a href="https://i.stack.imgur.com/SNLnx.png" rel="nofollow noreferrer">Here is the error message that comes from the &quot;explainer cell&quot;</a></p>