Prepare a model for distributed training

You've decided to use the Hugging Face Accelerator library to train your language translation model. Now it's time to prepare your model for distributed training!

Some data has been pre-loaded:

accelerator is an instance of Accelerator
model, optimizer, train_dataloader, and lr_scheduler have been defined

This exercise is part of the course

Efficient AI Model Training with PyTorch

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Exercise instructions

Call a method to prepare objects for distributed training.
Pass the training objects as positional arguments to accelerator.prepare(), matching the order of the output.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Prepare objects for distributed training
model, optimizer, train_dataloader, lr_scheduler = ____.____(
    # Pass in the training objects matching the order of the output
    ____,
    ____,
    ____,
    ____)

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