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Implementation for the paper "SpaceNet: Make Free Space For Continual Learning" in PyTorch.

License: MIT License

Python 100.00%

brain-inspired catastrophic-forgetting continual-learning deep-learning deep-neural-networks incremental-learning life-long-learning sparse-neural-networks sparse-representations sparse-training

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convolutional neural network

I have a problem when I try to implement with convolutional neural network for CIFAR. Between the last convolutional layer and first fully connected layer is max pooling layer. And the problem occurs when i run this code, the shape of output of conv layer is node same as the shape of input of FC layer
How can i fix this?

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