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Hi,
this is not a real issue, but just a note regarding the online docs of the Inception_v3 at this link.
I think it is better to insert a note in the page about the input shape as stated in the code documentation as:
.. note::
**Important**: In contrast to the other models the inception_v3 expects tensors with a size of
N x 3 x 299 x 299, so ensure your images are sized accordingly.
N must be greater than 1, otherwise it will throw an error, the strange thing is that it is reported as a training error even in pretrained mode (pretrained=True).
In the online docs it is not reported so well.
Best regards.
The text was updated successfully, but these errors were encountered:
During training, N needs to be greater than 1 because the model expects more than 1 value per channel. If you run the model in eval mode (model.eval()), it is OK to pass single image i.e N=1.
Hi,
this is not a real issue, but just a note regarding the online docs of the Inception_v3 at this link.
I think it is better to insert a note in the page about the input shape as stated in the code documentation as:
N must be greater than 1, otherwise it will throw an error, the strange thing is that it is reported as a training error even in pretrained mode (pretrained=True).
In the online docs it is not reported so well.
Best regards.
The text was updated successfully, but these errors were encountered: