possible bug

[denkorzh]

https://github.com/mahmoudnafifi/mixedillWB/blob/aeee3b8ab16e9d8e8d462e7ad32f0cb1a91b1654/src/gridnet.py#L150

You seem to use the same latent_x for all columns of the decoder part. I suggest this is a bug in your implementation of GridNet.

[mahmoudnafifi]

Thanks for your comment. At first res block, x_latent is returned "if j == 0: x_latent = res_blck(latent_x)", then for next blocks I use x_latent. It is bad naming i agree, but it looks not an implementation bug to me.

[denkorzh]

the line I pointed to is NOT under if j == 0

[denkorzh]

As far as I understand, for j>0 you do not process the processed, you process the same encoder output latent_xwith a new residual block. Thefore, the output of the previous residual block in the decoder row is just unemployed.

ср, 16 мар. 2022 г., 20:04 Mahmoud Afifi @.***>:

yes I understand your point. Res_blocks are arranged horizontally. Each row received the processed latent from encoder and process it sequentially. If we are at the beginning of the row, then we retrieve the encoder latent of this row once and process it, otherwise we process the processed latent in this row:

    if j == 0:
      latent_x = latent_forward[k]
    x_latent = res_blck(latent_x)

Makes sense?

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[mahmoudnafifi]

I checked the code carefully and yes you are right. It should be x_latent. It means the current implementation practically has a single decoder column. I will not change it to make trained models work as trained. But let's keep this issue open to help people find out.

[mahmoudnafifi]

Updated readme and referred to this issue. Thanks @denkorzh!

[denkorzh]

You're welcome!