From 2f19e8b863c54d16c1eb855bc89391063def15ce Mon Sep 17 00:00:00 2001
From: Gustaf Rydholm <gustaf.rydholm@gmail.com>
Date: Sun, 2 Oct 2022 02:55:53 +0200
Subject: Add support for hydra 1.2, add metadata file

---
 training/artifacts.py | 16 ++++++++--------
 training/main.py      |  3 ++-
 training/metadata.py  |  6 ++++++
 3 files changed, 16 insertions(+), 9 deletions(-)
 create mode 100644 training/metadata.py

diff --git a/training/artifacts.py b/training/artifacts.py
index a059833..2cb8bda 100644
--- a/training/artifacts.py
+++ b/training/artifacts.py
@@ -3,23 +3,20 @@ from datetime import datetime
 from pathlib import Path
 import shutil
 import sys
-from typing import Optional, Union
+from typing import Optional
 
 import click
 from loguru import logger as log
+from training import metadata
 import wandb
 from wandb.apis.public import Run
 
-TRAINING_DIR = Path(__file__).parents[0].resolve()
-ARTIFACTS_DIR = TRAINING_DIR.parent / "text_recognizer" / "artifacts"
-RUNS_DIR = TRAINING_DIR / "logs" / "runs"
-
 
 def _get_run_dir(run: Run) -> Optional[Path]:
     created_at = datetime.fromisoformat(run.created_at).astimezone()
     date = created_at.date()
     hour = (created_at + created_at.utcoffset()).hour
-    runs = list((RUNS_DIR / f"{date}").glob(f"{hour}-*"))
+    runs = list((metadata.RUNS_DIR / f"{date}").glob(f"{hour}-*"))
     if not runs:
         return None
     return runs[0]
@@ -45,7 +42,7 @@ def _copy_checkpoint(checkpoint: Path, dst_dir: Path) -> None:
 
 def save_model(run: Run, tag: str) -> None:
     """Save model to artifacts."""
-    dst_dir = ARTIFACTS_DIR / f"{tag}_text_recognizer"
+    dst_dir = metadata.ARTIFACTS_DIR / f"{tag}_text_recognizer"
     dst_dir.mkdir(parents=True, exist_ok=True)
     run_dir = _get_run_dir(run)
     if not run_dir:
@@ -77,7 +74,10 @@ def find_best_run(entity: str, project: str, tag: str, metric: str, mode: str) -
     best_run = runs[0]
     summary = best_run.summary
     log.info(
-        f"Best run is ({best_run.name}, {best_run.id}) picked from {len(runs)} runs with the following metric"
+        (
+            f"Best run is ({best_run.name}, {best_run.id}) picked from {len(runs)} "
+            "runs with the following metric"
+        )
     )
     log.info(
         f"{metric}: {summary[metric]}"
diff --git a/training/main.py b/training/main.py
index 26d5aeb..6e54a23 100644
--- a/training/main.py
+++ b/training/main.py
@@ -1,9 +1,10 @@
 """Loads config with hydra and runs experiment."""
 import hydra
 from omegaconf import DictConfig
+from training.metadata import TRAINING_DIR
 
 
-@hydra.main(config_path="conf", config_name="config")
+@hydra.main(version_base="1.2", config_path=TRAINING_DIR / "conf", config_name="config")
 def main(config: DictConfig) -> None:
     """Loads config with hydra and runs the experiment."""
     import utils
diff --git a/training/metadata.py b/training/metadata.py
new file mode 100644
index 0000000..b5a868d
--- /dev/null
+++ b/training/metadata.py
@@ -0,0 +1,6 @@
+"""Training paths."""
+from pathlib import Path
+
+TRAINING_DIR = Path(__file__).parents[0].resolve()
+ARTIFACTS_DIR = TRAINING_DIR.parent / "text_recognizer" / "artifacts"
+RUNS_DIR = TRAINING_DIR / "logs" / "runs"
-- 
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