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Multiple x sizes can lead to the same y size in conv and pool operations. Our current API picks one in the deconv and unpool implementations. Check out whether other frameworks use the same default and how we can give the user the option to pick different sizes in the API.
The text was updated successfully, but these errors were encountered:
denizyuret
changed the title
deconv default output size not always correct
deconv/unpool default output size not always correct
Dec 12, 2020
Tensorflow needs an output size to be specified. However, Pytorch does not need an output size to be specified according to their definitions here: https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/nn/conv3d_transpose https://pytorch.org/docs/stable/generated/torch.nn.ConvTranspose3d.html
The Pytorch implementation, however, takes arguments to add zero paddings to one (specified by 'output_padding' argument) or both sides (specified by 'padding' argument) to get a desired output shape. More information about the output shape and padding is available on the PyTorch link above.
However, I think specifying the output shape and adding the 'SAME' padding as in tensorflow implementation seems more user friendly.
Multiple x sizes can lead to the same y size in conv and pool operations. Our current API picks one in the deconv and unpool implementations. Check out whether other frameworks use the same default and how we can give the user the option to pick different sizes in the API.
The text was updated successfully, but these errors were encountered: