Comments (2)
Hello,
You are talking about MutanAtt, which inherits from AbstractAtt.
MutanAtt has two kind of fusion layers:
- fusion_classif which will be used to merge the visual and the question vectors with the MutanFusion module.
- fusion_att which will be used to merge the visual tensor from the ConvNet (14x14x2048) and the question vectors with the MutanFusion2d module in a "convolutional" way.
Thus, this activation function att.py#L74 will be computed after the call of the MutanFusion2d att.py#L72 module (and not the MutanFusion module which will be called at the end att.py#L140.
Also, notice that we do not use any activation_mm
in our default MutanAtt model, but we use this option in our default MLBAtt model.
Are my explanations clear enough?
Greetings,
Remi
EDIT: but for sure, you have to be careful to not apply the same activation function twice (if you modify the default options).
from vqa.pytorch.
Thank you for your reply!
from vqa.pytorch.
Related Issues (20)
- Reproduce the problem using fusion scheme of concatenation HOT 2
- Hi cadene,why i get this error when i use demo? HOT 1
- iteration over a 0-d tensor when trying to run the demo HOT 7
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- FileNotFoundError: [Errno 2] No such file or directory: 'data/vqa2/raw/annotations/mscoco_train2014_annotations.json' HOT 1
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