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MousaviSajad / SleepEEGNet

SleepEEGNet: Automated Sleep Stage Scoring with Sequence to Sequence Deep Learning Approach
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Memory limited #7

Open DongqiShen opened 4 years ago

DongqiShen commented 4 years ago

Hi, Thanks for you paper and code which helped me a lot. I tried to run the code, but it stoped at 'X_train, y_train, X_test, y_test = data_loader.load_data(seq_len=hparams.max_time_step)' It remained me that I don't have enough memory. My pc is ubuntu18.04 with 16GB, and also, I set swap area as 16 GB, but the problem existed still. Is there any way to solve this without installing a new memory. Thanks

MousaviSajad commented 4 years ago

Hello, Thank you for your email. One way is to store all folds (k-fold cross-validation) on the disk storage and then load each data fold while you are training the model.

Regards, Sajad

On Wed, Mar 4, 2020 at 8:52 PM dongqi shen notifications@github.com wrote:

Hi, Thanks for you paper and code which helped me a lot. I tried to run the code, but it stoped at 'X_train, y_train, X_test, y_test = data_loader.load_data(seq_len=hparams.max_time_step)' It remained me that I don't have enough memory. My pc is ubuntu18.04 with 16GB, and also, I set swap area as 16 GB, but the problem existed still. Is there any way to solve this without installing a new memory. Thanks

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