Merge pull request #784 from scap3yvt/783-rename-parseconfig-to-confi…

…gmanager-for-consistency

Rename parseconfig for consistency

GANDLF/cli/generate_metrics.py

@@ -8,7 +8,7 @@
 import SimpleITK as sitk
 import numpy as np
 
-from GANDLF.parseConfig import parseConfig
+from GANDLF.config_manager import ConfigManager
 from GANDLF.utils import find_problem_type_from_parameters, one_hot
 from GANDLF.metrics import (
     overall_stats,
@@ -58,7 +58,7 @@ def generate_metrics_dict(input_csv: str, config: str, outputfile: str = None) -
         assert column in headers, f"The input csv should have a column named {column}"
 
     overall_stats_dict = {}
-    parameters = parseConfig(config)
+    parameters = ConfigManager(config)
     problem_type = parameters.get("problem_type", None)
     problem_type = (
         find_problem_type_from_parameters(parameters)

GANDLF/cli/main_run.py

@@ -3,7 +3,7 @@
 
 from GANDLF.training_manager import TrainingManager, TrainingManager_split
 from GANDLF.inference_manager import InferenceManager
-from GANDLF.parseConfig import parseConfig
+from GANDLF.config_manager import ConfigManager
 from GANDLF.utils import (
     populate_header_in_parameters,
     parseTrainingCSV,
@@ -34,7 +34,7 @@ def main_run(
     file_data_full = data_csv
     model_parameters = config_file
     device = device
-    parameters = parseConfig(model_parameters)
+    parameters = ConfigManager(model_parameters)
     parameters["device_id"] = -1
 
     if train_mode:

GANDLF/cli/post_training_model_optimization.py

@@ -1,6 +1,6 @@
 import os
 from GANDLF.compute import create_pytorch_objects
-from GANDLF.parseConfig import parseConfig
+from GANDLF.config_manager import ConfigManager
 from GANDLF.utils import version_check, load_model, optimize_and_save_model
 
 
@@ -21,7 +21,7 @@ def post_training_model_optimization(model_path: str, config_path: str) -> bool:
 
     # If parameters are not available in the model file, parse them from the config file
     parameters = (
-        parseConfig(config_path, version_check_flag=False)
+        ConfigManager(config_path, version_check_flag=False)
         if parameters is None
         else parameters
     )

GANDLF/cli/preprocess_and_save.py

@@ -10,7 +10,7 @@
     get_dataframe,
     get_correct_padding_size,
 )
-from GANDLF.parseConfig import parseConfig
+from GANDLF.config_manager import ConfigManager
 from GANDLF.data.ImagesFromDataFrame import ImagesFromDataFrame
 from torch.utils.data import DataLoader
 from tqdm import tqdm
@@ -45,7 +45,7 @@ def preprocess_and_save(
     # read the csv
     # don't care if the dataframe gets shuffled or not
     dataframe, headers = parseTrainingCSV(data_csv, train=False)
-    parameters = parseConfig(config_file)
+    parameters = ConfigManager(config_file)
 
     # save the parameters so that the same compute doesn't happen once again
     parameter_file = os.path.join(output_dir, "parameters.pkl")

GANDLF/parseConfig.py → GANDLF/config_manager.py

@@ -98,7 +98,7 @@ def initialize_key(parameters, key, value=None):
     return parameters
 
 
-def parseConfig(config_file_path, version_check_flag=True):
+def _parseConfig(config_file_path, version_check_flag=True):
     """
     This function parses the configuration file and returns a dictionary of parameters.
 
@@ -714,3 +714,17 @@ def parseConfig(config_file_path, version_check_flag=True):
         params["inference_mechanism"] = inference_mechanism
 
     return params
+
+
+def ConfigManager(config_file_path, version_check_flag=True) -> None:
+    """
+    This function parses the configuration file and returns a dictionary of parameters.
+
+    Args:
+        config_file_path (Union[str, dict]): The filename of the configuration file.
+        version_check_flag (bool, optional): Whether to check the version in configuration file. Defaults to True.
+
+    Returns:
+        dict: The parameter dictionary.
+    """
+    return _parseConfig(config_file_path, version_check_flag)

docs/extending.md

@@ -16,7 +16,7 @@ Before starting to work on the code-level on GaNDLF, please follow the [instruct
 ## Overall Architecture
 
 - Command-line parsing: [gandlf_run](https://github.com/mlcommons/GaNDLF/blob/master/gandlf_run)
-- Parameters from [training configuration](https://github.com/mlcommons/GaNDLF/blob/master/samples/config_all_options.yaml) get passed as a `dict` via [parameter parser](https://github.com/mlcommons/GaNDLF/blob/master/GANDLF/parseConfig.py)
+- Parameters from [training configuration](https://github.com/mlcommons/GaNDLF/blob/master/samples/config_all_options.yaml) get passed as a `dict` via the [config manager](https://github.com/mlcommons/GaNDLF/blob/master/GANDLF/config_manager.py)
 - [Training Manager](https://github.com/mlcommons/GaNDLF/blob/master/GANDLF/training_manager.py): 
     - Handles k-fold training 
     - Main entry point from CLI