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Pruning problem of deep grouped convolution models. #15

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zbzb-dlut opened this issue Sep 19, 2024 · 1 comment
Open

Pruning problem of deep grouped convolution models. #15

zbzb-dlut opened this issue Sep 19, 2024 · 1 comment

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@zbzb-dlut
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Hello author! May I ask if this model can handle deep grouped convolution models? Additionally, for reparameterized models, is this method applicable during the training stage?

@aponte411
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hi @zbzb-dlut thanks for the question. Our response is late due to recent business travel.

Currently, for grouped conv, we only support the case where groups = out_channels, e.g., the depthwisw conv. However, adding support for different scenarios should be doable, which can be achieved by further development on

class Conv2dOTO(Operator):

As for the reparameterization, it depends on what type of reparameterization, in general, the answer is yes.

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