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from typing import Dict, Any, List
from ..graph import Evaluator, Model
from ..integration_api import receive_trial_parameters
from ..utils import ContextStack, import_, get_importable_name
from .base import BaseExecutionEngine
class PythonGraphData:
def __init__(self, class_name: str, init_parameters: Dict[str, Any],
mutation: Dict[str, Any], evaluator: Evaluator) -> None:
self.class_name = class_name
self.init_parameters = init_parameters
self.mutation = mutation
self.evaluator = evaluator
def dump(self) -> dict:
return {
'class_name': self.class_name,
'init_parameters': self.init_parameters,
'mutation': self.mutation,
'evaluator': self.evaluator
}
@staticmethod
def load(data) -> 'PythonGraphData':
return PythonGraphData(data['class_name'], data['init_parameters'], data['mutation'], data['evaluator'])
class PurePythonExecutionEngine(BaseExecutionEngine):
@classmethod
def pack_model_data(cls, model: Model) -> Any:
mutation = get_mutation_dict(model)
graph_data = PythonGraphData(get_importable_name(model.python_class, relocate_module=True),
model.python_init_params, mutation, model.evaluator)
return graph_data
@classmethod
def trial_execute_graph(cls) -> None:
graph_data = PythonGraphData.load(receive_trial_parameters())
class _model(import_(graph_data.class_name)):
def __init__(self):
super().__init__(**graph_data.init_parameters)
with ContextStack('fixed', graph_data.mutation):
graph_data.evaluator._execute(_model)
def _unpack_if_only_one(ele: List[Any]):
if len(ele) == 1:
return ele[0]
return ele
def get_mutation_dict(model: Model):
return {mut.mutator.label: _unpack_if_only_one(mut.samples) for mut in model.history}
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