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When I keep model in memory, model can be saved and loaded.
BUT, with large training data, the RAM is run out quickly.
And, as same env, set keep memory set_keep_model_in_mem(False), the saved model only have header information without actually model content.
set_keep_model_in_mem(False)
So, how to fix it?
The text was updated successfully, but these errors were encountered:
At present, I can find same matter in https://stackoverflow.com/questions/55020860/how-to-predict-using-a-gcforest-model-when-i-did-not-keep-the-model-in-memory, but does not resove this problem.
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When I keep model in memory, model can be saved and loaded.
BUT, with large training data, the RAM is run out quickly.
And, as same env, set keep memory
set_keep_model_in_mem(False)
, the saved model only have header information without actually model content.So, how to fix it?
The text was updated successfully, but these errors were encountered: