What is the difference between the kernels of kaggle and googlecolab?

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.

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 ()
5 plt.figure(figsize=(16,12))
—-> 6 image, label = train_dataset[i]
8 plt.imshow(image[0])

4 frames
/usr/local/lib/python3.7/dist-packages/albumentations/pytorch/transforms.py in apply(self, img, **params)
91 def apply(self, img, **params): # skipcq: PYL-W0613
—> 92 return torch.from_numpy(img.transpose(2, 0, 1))
94 def apply_to_mask(self, mask, **params): # skipcq: PYL-W0613

ValueError: axes don’t match array

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