multiml.agent.pytorch.pytorch_asngnas module

class multiml.agent.pytorch.pytorch_asngnas.PytorchASNGNASAgent(verbose=1, num_epochs=1000, max_patience=5, batch_size={'length': 500, 'test': 100, 'type': 'equal_length'}, asng_args={'alpha': 1.5, 'clipping_value': None, 'delta': 0.0, 'lam': 2, 'range_restriction': True}, optimizer=None, optimizer_args=None, scheduler=None, scheduler_args=None, **kwargs)

Bases: PytorchConnectionRandomSearchAgent

Agent packing subtasks using Pytorch ASNG-NAS Model.

__init__(verbose=1, num_epochs=1000, max_patience=5, batch_size={'length': 500, 'test': 100, 'type': 'equal_length'}, asng_args={'alpha': 1.5, 'clipping_value': None, 'delta': 0.0, 'lam': 2, 'range_restriction': True}, optimizer=None, optimizer_args=None, scheduler=None, scheduler_args=None, **kwargs)

Parameters:

• training_choiceblock_model (bool) – Training choiceblock model after connecting submodels

• **kwargs – Arbitrary keyword arguments

execute()

Execute Currently, only categorical ASNG NAS is implemented.