gigl.src.training.v1.lib.training_process#

Functions

`generate_trainer_instance`
`get_torch_profiler_instance`
`setup_model_device`	Configures the model by setting it on device, syncing batch norm, and wrapping the model with DDP with the relevant flags, such as find_unused_parameters Args: model (torch.nn.Module): Model initialized for training supports_distributed_training (bool): Whether distributed training is supported, defined in the modeling task spec should_enable_find_unused_parameters (bool): Whether we allow for parameters to not receive gradient on backward pass in DDP device (torch.device): Torch device to set the model to

Classes