Custom build methods, more examples

Features

• New mechanics building of attributes. It allows customizing the creation of model parts. Example here.
• CIFAR example with Distributed Data Parallel, mixed precision, and gradient accumulation cifar_advanced.py.
• Add save_model method to argus.callbacks.checkpoints. It allows customizing checkpoint saving.
• Add logging time and LR to argus.callbacks.logging.LoggingToCSV.
• argus.utils.deep_chunk similar to scatter function in PyTorch DataParallel.
• Dockerfile and Makefile for developing.

Breaking Changes

• Use argus.utils.deep_to function instead method argus.Model.prepare_batch. argus.Model.prepare_batch removed so if you use custom val_train or train_step you should change replace

  input, target = self.prepare_batch(batch, self.device)

  to

  input, target = deep_to(batch, self.device, non_blocking=True)

• Rename max_epochs to num_epochs of argus.Model.fit method.

  model.fit(train_loader,
            val_loader=val_loader,
            num_epochs=1000)

• Remove copy_last parameter from argus.callbacks.checkpoints.
• Remove period parameter from argus.callbacks.checkpoints.MonitorCheckpoint.