RuntimeError: Given input size: (1536x5x5). Calculated output size: (1536x0x0). Output size is too small

[JinhaSong]

I tried to run a test that trains only 20 of VGGFace2's train data.
And I tried to use inceptionresnet v2 as the network architecture, but it does not run with the following error.

RuntimeError: Given input size: (1536x5x5). Calculated output size: (1536x0x0). Output size is too small

Please let me know if there is any guessing or wrong part of the reason.

[tamerthamoqa]

Hello JinhaSong,

Did you specify the input image to be 299x299? I think the minimum should be 150x150 but I am not sure on that to be honest.

For reference, I have imported the Inception-ResNet-V2 implementation from Cadene's repository here:
https://github.com/Cadene/pretrained-models.pytorch/blob/master/pretrainedmodels/models/inceptionresnetv2.py

[JoannisAretakis]

Hi JinhaSong,
I had similar issue and I managed to fix it by setting AvgPool2d kernel_size to 5. Since the
VGGFace2 images are smaller the current network at that layer ends up with tensor 1536x5x5 instead of 1536x8x8.
Applying pooling with kernel_size 8 which is larger that what is provided by the previous layer causes this issue. Hope that helps !