| import json |
| import os |
|
|
| import matplotlib.pyplot as plt |
|
|
|
|
| def function_1(name: str, age: int) -> bool: |
| return (age >= 18) and name != "Marina" |
|
|
|
|
| def plot_metrics(metrics_file="outputs/training_metrics.json"): |
| if not os.path.exists(metrics_file): |
| print(f"Metrics file not found: {metrics_file}") |
| return |
|
|
| with open(metrics_file, "r") as f: |
| metrics_data = json.load(f) |
|
|
| loss_history = metrics_data.get("loss", []) |
| validity_history = metrics_data.get("validity", []) |
| uniqueness_history = metrics_data.get("uniqueness", []) |
| novelty_history = metrics_data.get("novelty", []) |
|
|
| output_dir = os.path.dirname(metrics_file) |
|
|
| if loss_history: |
| print("Saving loss curve...") |
| plt.figure(figsize=(10, 6)) |
| iterations, losses = zip(*loss_history) |
| plt.plot(iterations, losses) |
| plt.xlabel("Iteration") |
| plt.ylabel("Loss") |
| plt.title("Training Loss Curve") |
| plt.grid(True) |
| plt.savefig( |
| os.path.join(output_dir, "loss_curve.png"), dpi=300, bbox_inches="tight" |
| ) |
| plt.close() |
| print(f"Saved loss curve to {os.path.join(output_dir, 'loss_curve_1000.png')}") |
|
|
| if validity_history or uniqueness_history or novelty_history: |
| print("Saving metrics plot...") |
| plt.figure(figsize=(12, 6)) |
| if validity_history: |
| iterations_v, validity_vals = zip(*validity_history) |
| plt.plot( |
| iterations_v, validity_vals, label="Validity", marker="o", markersize=3 |
| ) |
| if uniqueness_history: |
| iterations_u, uniqueness_vals = zip(*uniqueness_history) |
| plt.plot( |
| iterations_u, |
| uniqueness_vals, |
| label="Uniqueness", |
| marker="s", |
| markersize=3, |
| ) |
| if novelty_history: |
| iterations_n, novelty_vals = zip(*novelty_history) |
| plt.plot( |
| iterations_n, novelty_vals, label="Novelty", marker="^", markersize=3 |
| ) |
| plt.xlabel("Iteration") |
| plt.ylabel("Score (%)") |
| plt.title("Training Metrics: Validity, Uniqueness, and Novelty") |
| plt.legend() |
| plt.grid(True) |
| plt.savefig( |
| os.path.join(output_dir, "metrics_curve.png"), dpi=300, bbox_inches="tight" |
| ) |
| plt.close() |
| print(f"Saved metrics plot to {os.path.join(output_dir, 'metrics_curve.png')}") |
|
|
|
|
| if __name__ == "__main__": |
| plot_metrics() |
|
|
