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![image](https://user-images.githubusercontent.com/26426412/33496897-c62a3832-d680-11e7-9dfc-3781185fab4f.png)
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```def update_weights(inputs, outputs, weights, lr):
original_weights = deepcopy(weights)
temp_weights = deepcopy(weights)
updated_weights = deepcopy(weights)
original_loss = feed…
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Let's introduce training configure tool. This tool should find a configuration for network training with some optimal memory costs.
The Training Tool will be able to perform actions to improve the tr…
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The following error occurred when running the code:
File "/home/xxx/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch/tensor.py", line 102, in backward
torch.autograd.backward(self, gr…
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I first freeze the model parameters:
`for param in self.parameters():
param.requires_grad = False
`
Then, I unfreeze the parameters of the new layer that I want to train:
`for param in ne…
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Hello!
Thanks for your wonderful work.
In the Optimization section of the paper, it said that "In order to optimize (2) via backpropagation, we need to compute a subgradient of the nuclear norm of a…
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We need to finish this very basic part of the code to get to the more interesting stuff later, i.e. the unsupervised classification/learning using contrastive divergence in restricted Boltzmann machin…
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On sait que le réseau n'est backpropagé qu'une fois la partie finie. Néanmoins on ignore encore comment faire cela.
Commentez donc avec des ressources ou des explications quant à la **Backpropagati…
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Thank you for your excellent work. I was wondering if there are any plans to release the training or fine-tuning code?