File size: 3,138 Bytes
853e22b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 |
# Copyright (c) MONAI Consortium
# 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 __future__ import annotations
import os
from monai.apps.auto3dseg.bundle_gen import BundleAlgo
from monai.auto3dseg import algo_from_pickle, algo_to_pickle
from monai.utils.enums import AlgoKeys
__all__ = ["import_bundle_algo_history", "export_bundle_algo_history", "get_name_from_algo_id"]
def import_bundle_algo_history(
output_folder: str = ".", template_path: str | None = None, only_trained: bool = True
) -> list:
"""
import the history of the bundleAlgo objects as a list of algo dicts.
each algo_dict has keys name (folder name), algo (bundleAlgo), is_trained (bool),
Args:
output_folder: the root path of the algorithms templates.
template_path: the algorithm_template. It must contain algo.py in the follow path:
``{algorithm_templates_dir}/{network}/scripts/algo.py``.
only_trained: only read the algo history if the algo is trained.
"""
history = []
for name in sorted(os.listdir(output_folder)):
write_path = os.path.join(output_folder, name)
if not os.path.isdir(write_path):
continue
obj_filename = os.path.join(write_path, "algo_object.pkl")
if not os.path.isfile(obj_filename): # saved mode pkl
continue
algo, algo_meta_data = algo_from_pickle(obj_filename, template_path=template_path)
best_metric = algo_meta_data.get(AlgoKeys.SCORE, None)
if best_metric is None:
try:
best_metric = algo.get_score()
except BaseException:
pass
is_trained = best_metric is not None
if (only_trained and is_trained) or not only_trained:
history.append(
{AlgoKeys.ID: name, AlgoKeys.ALGO: algo, AlgoKeys.SCORE: best_metric, AlgoKeys.IS_TRAINED: is_trained}
)
return history
def export_bundle_algo_history(history: list[dict[str, BundleAlgo]]) -> None:
"""
Save all the BundleAlgo in the history to algo_object.pkl in each individual folder
Args:
history: a List of Bundle. Typically, the history can be obtained from BundleGen get_history method
"""
for algo_dict in history:
algo = algo_dict[AlgoKeys.ALGO]
algo_to_pickle(algo, template_path=algo.template_path)
def get_name_from_algo_id(id: str) -> str:
"""
Get the name of Algo from the identifier of the Algo.
Args:
id: identifier which follows a convention of "name_fold_other".
Returns:
name of the Algo.
"""
return id.split("_")[0]
|