Trainer¶
- class classy_vision.trainer.ClassyTrainer¶
Base class for shared training code.
A trainer is responsible for setting up the environment for training, for instance: configuring rendezvous for distributed training, deciding what GPU to use and so on. Trainers also control the outer portion of the training loop, but delegate to the task to decide how exactly to perform inference, compute loss etc. That allows combining tasks with different trainers depending on whether you want to train on your current machine, AWS cluster etc.
- train(task: classy_vision.tasks.classy_task.ClassyTask)¶
Runs training phases, phases are generated from the config.
- Parameters
task – Task to be used in training. It should contain everything that is needed for training