# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import List
from nvflare.apis.dxo import DXO
from nvflare.apis.event_type import EventType
from nvflare.apis.fl_context import FLContext
from nvflare.app_common.abstract.model import model_learnable_to_dxo
from nvflare.app_common.abstract.model_locator import ModelLocator
from nvflare.app_common.abstract.model_persistor import ModelPersistor
[docs]class ListModelLocator(ModelLocator):
def __init__(self, persistor_id: str, model_list={}):
"""The ModelLocator's job is to find and locate the models inventory saved during training.
Args:
persistor_id (str): ModelPersistor component ID
model_list: a list of model_names and locations
"""
super().__init__()
self.persistor_id = persistor_id
self.model_persistor = None
self.model_list = model_list
[docs] def handle_event(self, event_type: str, fl_ctx: FLContext):
if event_type == EventType.START_RUN:
self._initialize(fl_ctx)
def _initialize(self, fl_ctx: FLContext):
engine = fl_ctx.get_engine()
self.model_persistor: ModelPersistor = engine.get_component(self.persistor_id)
if self.model_persistor is None or not isinstance(self.model_persistor, ModelPersistor):
raise ValueError(
f"persistor_id component must be PTFileModelPersistor. " f"But got: {type(self.model_persistor)}"
)
[docs] def get_model_names(self, fl_ctx: FLContext) -> List[str]:
"""Returns the list of model names that should be included from server in cross site validation.add().
Args:
fl_ctx (FLContext): FL Context object.
Returns:
List[str]: List of model names.
"""
return list(self.model_list.keys())
[docs] def locate_model(self, model_name, fl_ctx: FLContext) -> DXO:
"""Call to locate and load the model weights of model_name.
Args:
model_name: name of the model
fl_ctx: FLContext
Returns: model_weight DXO
"""
if model_name not in list(self.model_list.keys()):
raise ValueError(f"model inventory does not contain: {model_name}")
location = self.model_list[model_name]
model_learnable = self.model_persistor.get_model_from_location(location, fl_ctx)
dxo = model_learnable_to_dxo(model_learnable)
return dxo