added gitignore

.gitignore

@@ -24,3 +24,9 @@ data/
 checkpoints/
 logs/
 /data
+artifacts/
+artifacts/*
+*png
+*jpg
+*jpeg
+artifacts/image_prediction.png

src/create_artifacts.py

@@ -0,0 +1,27 @@
+from typing import List
+import os
+from src.utils.multirun_op import multirun_artifact_producer
+import hydra
+from omegaconf import DictConfig
+from loguru import logger
+from dotenv import load_dotenv, find_dotenv
+import rootutils
+
+# Load environment variables
+load_dotenv(find_dotenv(".env"))
+
+# Setup root directory
+root = rootutils.setup_root(__file__, indicator=".project-root")
+
+
+@hydra.main(config_path="../configs", config_name="train", version_base="1.3")
+def create_artifacts(cfg: DictConfig):
+    base_path = os.path.join(cfg.paths.log_dir, "train", "runs")
+    logger.info(
+        f"Base path: {base_path} and artifact directory: {cfg.paths.artifact_dir}"
+    )
+    multirun_artifact_producer(base_path, cfg.paths.artifact_dir)
+
+
+if __name__ == "__main__":
+    create_artifacts()

src/utils/multirun_op.py

@@ -0,0 +1,81 @@
+import os
+import glob
+import yaml
+import pandas as pd
+import json
+from datetime import datetime
+from loguru import logger
+
+
+def multirun_artifact_producer(base_path: str, output_path: str):
+    """Aggregate data from the latest run's csv folder and save to a JSON file."""
+    # Find the latest top-level run folder
+    latest_folder = max(glob.glob(os.path.join(base_path, "*")), key=os.path.getmtime)
+    if not os.path.isdir(latest_folder):
+        logger.error("No valid run folders found!")
+        return
+
+    # Initialize JSON structure
+    output_data = {}
+    # Process each sub-run directory within the latest run folder
+    for run_dir in os.listdir(latest_folder):
+        run_path = os.path.join(latest_folder, run_dir)
+        if os.path.isdir(run_path):
+            # Look for the latest folder in the csv subdirectory
+            csv_base_path = os.path.join(run_path, "csv")
+            if not os.path.isdir(csv_base_path):
+                logger.warning(f"No csv directory found in {run_path}. Skipping.")
+                continue
+
+            # Find the latest version folder in csv
+            latest_csv_folder = max(
+                glob.glob(os.path.join(csv_base_path, "version_*")),
+                key=os.path.getmtime,
+            )
+            if not os.path.isdir(latest_csv_folder):
+                logger.warning(
+                    f"No valid version folder found in {csv_base_path}. Skipping."
+                )
+                continue
+
+            # Paths to files in the latest csv version folder
+            hparams_path = os.path.join(latest_csv_folder, "hparams.yaml")
+            metrics_path = os.path.join(latest_csv_folder, "metrics.csv")
+
+            # Check if necessary files exist
+            if not os.path.isfile(hparams_path) or not os.path.isfile(metrics_path):
+                logger.warning(
+                    f"Missing hparams.yaml or metrics.csv in {latest_csv_folder}. Skipping."
+                )
+                continue
+
+            # Read hparams.yaml
+            with open(hparams_path, "r") as file:
+                hparams = yaml.safe_load(file)
+
+            # Read metrics.csv and calculate averages
+            metrics_df = pd.read_csv(metrics_path)
+            avg_train_acc = metrics_df["train_acc"].dropna().mean()
+            avg_val_acc = metrics_df["val_acc"].dropna().mean()
+
+            # Create JSON structure for this run
+            output_data[f"run_{run_dir}"] = {
+                "hparams": hparams,
+                "metrics": {"avg_train_acc": avg_train_acc, "avg_val_acc": avg_val_acc},
+            }
+
+    # Save aggregated data to JSON
+    os.makedirs(output_path, exist_ok=True)
+    output_file = os.path.join(
+        output_path, f"aggregated_data_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json"
+    )
+    logger.info(f"Saving aggregated data to {output_file}")
+    with open(output_file, "w") as json_file:
+        json.dump(output_data, json_file, indent=4)
+
+
+if __name__ == "__main__":
+    # Paths
+    base_path = "./logs/train/runs"
+    output_path = "./artifacts"
+    multirun_artifact_producer(base_path, output_path)