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maryam089 avatar maryam089 commented on May 19, 2024

When I try to load the pre-trained network and then want to update it with more training it gives me following error.......... any help @pathak22 ??
/home/maryam/torch/install/bin/lua: /home/maryam/torch/install/share/lua/5.2/nn/Module.lua:327: check that you are sharing parameters and gradParameters
stack traceback:
[C]: in function 'assert'
/home/maryam/torch/install/share/lua/5.2/nn/Module.lua:327: in function 'getParameters'
train.lua:270: in main chunk
[C]: in function 'dofile'
...ryam/torch/install/lib/luarocks/rocks/trepl/scm-1/bin/th:150: in main chunk
[C]: in ?

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maryam089 avatar maryam089 commented on May 19, 2024

@pathak22 kindly help me

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pathak22 avatar pathak22 commented on May 19, 2024

@maryam089
Can you paste the full log? Where is this pre-trained network from? Was it trained from the context encoder training code? Are the architecture and other details same?

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maryam089 avatar maryam089 commented on May 19, 2024

Well i am using your already trained network on imageNet 100k ..(center region inpaint).... but now i want to add few thousand more images to it and train it again ... how i can i load the weights and parameters to the network when i try to train it again for 1 or 2 more epoch on by loading already trained network @pathak22

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NerminSalem avatar NerminSalem commented on May 19, 2024

@pathak22 if i stopped traing for any reason can i resume tge training from the epoch it stopped in as it always start from the beginning

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pathak22 avatar pathak22 commented on May 19, 2024

@NerminSalem @maryam089

Sorry I didn't provide this functionality in the training code (I should have!). But it should not be hard to implement if you look at this file and see how the network is first loaded. After this, the loaded network is same as the one defined here, and hence you won't need to define it again. Feel free to make a pull request if you would like. Thanks!

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harshithabk avatar harshithabk commented on May 19, 2024

@pathak22
Hi,
This is regrading re-training the imagenet/paris model that you have shared.
We referred the below two links:
https://github.com/torch/demos/blob/master/train-a-digit-classifier/train-on-mnist.lua
facebookarchive/fb.resnet.torch#116
And we understand that there is a command line argument to indicate whether its re-training or training from beginning.
Do you have any such command line argument to be passed to indicate regarding retraining in your code?
Can you please suggest me the code changes that could be done?

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