I fell in love with machine learning, the sun.
I have one question.
Why is it that I can run it in kaggle’s kernel, but not in googlecolab?
I don’t know how to make it work.
Please help me.

  
      

      kaggle.com
  

  
    

G2Net / efficientnet_b7 / baseline [training]

  Explore and run machine learning code with Kaggle Notebooks | Using data from multiple data sources


  

  
    
    
  

  


By the way, I am using timm’s efficientnet.
![file:///Users/SN/Pictures/Screenshot_2021-08-22%2013.36.07_QLL1wr.png](url to embed)

CQT kernels created, time used = 0.0308 seconds
/usr/local/lib/python3.7/dist-packages/nnAudio/utils.py:326: SyntaxWarning: If fmax is given, n_bins will be ignored
warnings.warn(‘If fmax is given, n_bins will be ignored’,SyntaxWarning)
ValueError                                Traceback (most recent call last)
 in ()
4
5     plt.figure(figsize=(16,12))
----> 6     image, label = train_dataset[i]
7
8     plt.imshow(image[0])
4 frames
/usr/local/lib/python3.7/dist-packages/albumentations/pytorch/transforms.py in apply(self, img, **params)
90
91     def apply(self, img, **params):  # skipcq: PYL-W0613
—> 92         return torch.from_numpy(img.transpose(2, 0, 1))
93
94     def apply_to_mask(self, mask, **params):  # skipcq: PYL-W0613
ValueError: axes don’t match array