Source code for immuneML.dsl.instruction_parsers.MLApplicationParser

import os
import shutil
from pathlib import Path
from typing import Tuple

from immuneML.IO.ml_method.MLImport import MLImport
from immuneML.dsl.symbol_table.SymbolTable import SymbolTable
from immuneML.dsl.symbol_table.SymbolType import SymbolType
from immuneML.environment.Label import Label
from immuneML.environment.LabelConfiguration import LabelConfiguration
from immuneML.hyperparameter_optimization.HPSetting import HPSetting
from immuneML.util.ParameterValidator import ParameterValidator
from immuneML.util.PathBuilder import PathBuilder
from immuneML.workflows.instructions.ml_model_application.MLApplicationInstruction import MLApplicationInstruction


[docs]class MLApplicationParser: """ Specification example for the MLApplication instruction: .. highlight:: yaml .. code-block:: yaml instruction_name: type: MLApplication dataset: d1 config_path: ./config.zip number_of_processes: 4 label: CD store_encoded_data: True """
[docs] def parse(self, key: str, instruction: dict, symbol_table: SymbolTable, path: Path) -> MLApplicationInstruction: location = MLApplicationParser.__name__ ParameterValidator.assert_keys(instruction.keys(), ['type', 'dataset', 'number_of_processes', 'config_path', 'store_encoded_data'], location, key) ParameterValidator.assert_in_valid_list(instruction['dataset'], symbol_table.get_keys_by_type(SymbolType.DATASET), location, f"{key}: dataset") ParameterValidator.assert_type_and_value(instruction['number_of_processes'], int, location, f"{key}: number_of_processes", min_inclusive=1) ParameterValidator.assert_type_and_value(instruction['config_path'], str, location, f'{key}: config_path') ParameterValidator.assert_type_and_value(instruction['store_encoded_data'], bool, location, f'{key}: store_encoded_data') hp_setting, label = self._parse_hp_setting(instruction, path, key) instruction = MLApplicationInstruction(dataset=symbol_table.get(instruction['dataset']), name=key, number_of_processes=instruction['number_of_processes'], label_configuration=LabelConfiguration([label]), hp_setting=hp_setting, store_encoded_data=instruction['store_encoded_data']) return instruction
def _parse_hp_setting(self, instruction: dict, path: Path, key: str) -> Tuple[HPSetting, Label]: assert os.path.isfile(instruction['config_path']), f'MLApplicationParser: {instruction["config_path"]} is not file path.' assert '.zip' in instruction['config_path'], f'MLApplicationParser: {instruction["config_path"]} is not a zip file.' config_dir = PathBuilder.build_from_objects(path / f"unpacked_{key}/") shutil.unpack_archive(instruction['config_path'], config_dir, 'zip') hp_setting, label = MLImport.import_hp_setting(config_dir) return hp_setting, label