LibMTL.architecture.abstract_arch

class AbsArchitecture(task_name, encoder_class, decoders, rep_grad, multi_input, device, **kwargs)

Bases: torch.nn.Module

An abstract class for MTL architectures.

Parameters:

• task_name (list) – A list of strings for all tasks.

• encoder_class (class) – A neural network class.

• decoders (dict) – A dictionary of name-decoder pairs of type (str, torch.nn.Module).

• rep_grad (bool) – If True, the gradient of the representation for each task can be computed.

• multi_input (bool) – Is True if each task has its own input data, otherwise is False.

• device (torch.device) – The device where model and data will be allocated.

• kwargs (dict) – A dictionary of hyperparameters of architectures.

forward(inputs, task_name=None)

Parameters:

• inputs (torch.Tensor) – The input data.

• task_name (str, default=None) – The task name corresponding to inputs if multi_input is True.

Returns:

A dictionary of name-prediction pairs of type (str, torch.Tensor).

Return type:

dict

get_share_params()

Return the shared parameters of the model.

zero_grad_share_params()

Set gradients of the shared parameters to zero.