在Keras中保存模型和重量（单个文件中）

Question

I have Python code that generates a deep convolutional neural network using Keras. I'm trying to save the model, but the result is gigantic (100s of MBs). I'd like to pare that down a bit to make something more manageable.

The problem is that model.save() stores (quoting the Keras FAQ):

• the architecture of the model, allowing to re-create the model
• the weights of the model
• the training configuration (loss, optimizer)
• the state of the optimizer, allowing to resume training exactly where you left off.

If I'm not doing any more training, I think I just need the first two.

I can use model.to_json() to make a JSON string of the architecture and save that off, and model.save_weights() to make a separate file containing the weights. That's about a third the size of the full model.save() result. But I'm wondering if there's some way to store these in a single self-contained file? (Short of outputting two files, zipping them together, and deleting the originals.) Alternatively, maybe there's a way to delete the training configuration and optimizer state when training is complete, so that model.save() doesn't give me something nearly so big?

Thanks.

Answer 1

模型的保存功能具有完全相同的参数，称为include_optimizer，将其设置为false将保存模型而不包括优化器状态，​​这将导致更小的HDF5文件：

model.save("something.hdf5", include_optimizer=False)