Random#

Experiment Runner#

class archai.supergraph.algos.random.random_exp_runner.RandomExperimentRunner(config_filename: str, base_name: str, clean_expdir=False)[source]#
model_desc_builder() → RandomModelDescBuilder[source]#
trainer_class() → Type[ArchTrainer] | None[source]#

Model Description Builder#

class archai.supergraph.algos.random.random_model_desc_builder.RandOps(n_nodes: int, max_edges: int)[source]#

Container to store (op_names, to_states) for each nodes

PRIMITIVES = ['max_pool_3x3', 'avg_pool_3x3', 'skip_connect', 'sep_conv_3x3', 'sep_conv_5x5', 'dil_conv_3x3', 'dil_conv_5x5']#
class archai.supergraph.algos.random.random_model_desc_builder.RandomModelDescBuilder[source]#
build_cells(in_shapes: List[List[List[int | float]]], conf_model_desc: Config) → Tuple[List[CellDesc], List[AuxTowerDesc | None]][source]#
build_nodes(stem_shapes: List[List[int | float]], conf_cell: Config, cell_index: int, cell_type: CellType, node_count: int, in_shape: List[int | float], out_shape: List[int | float]) → Tuple[List[List[int | float]], List[NodeDesc]][source]#