34 lines
1.3 KiB
Python
34 lines
1.3 KiB
Python
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from pathlib import Path
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from architectures.Model import Model
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def _log_to_csv(model:Model, mode, accuracy, report_dict, strategy):
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"""Handles directory structures, file setups, and distinct CSV column formatting."""
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arch_name = model.__class__.__name__.lower()
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save_dir = Path(f"reports/{strategy}")
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save_dir.mkdir(parents=True, exist_ok=True)
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csv_path = save_dir / f"{arch_name}-{mode}.csv"
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file_exists = csv_path.exists()
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headers = [
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"accuracy",
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"macro_precision", "macro_recall", "macro_f1",
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"weighted_precision", "weighted_recall", "weighted_f1"
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]
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row = [
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f"{accuracy / 100.0:.4f}",
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f"{report_dict['macro avg']['precision']:.4f}",
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f"{report_dict['macro avg']['recall']:.4f}",
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f"{report_dict['macro avg']['f1-score']:.4f}",
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f"{report_dict['weighted avg']['precision']:.4f}",
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f"{report_dict['weighted avg']['recall']:.4f}",
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f"{report_dict['weighted avg']['f1-score']:.4f}"
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]
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with open(csv_path, "a") as f:
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if not file_exists:
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f.write(",".join(headers) + "\n")
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f.write(",".join(row) + "\n")
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print(f">> Direct CSV metrics appended to {csv_path}") |