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plot_metrics.py
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plot_metrics.py
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import json
import matplotlib.pyplot as plt
import argparse
import os
def plot_metric(data, metric_name, x_label, y_label, title, colors):
plt.figure(figsize=(7, 6))
plt.plot(data[f'train_epoch_{metric_name}'], label=f'Train Epoch {metric_name.capitalize()}', color=colors[0])
plt.plot(data[f'val_epoch_{metric_name}'], label=f'Validation Epoch {metric_name.capitalize()}', color=colors[1])
plt.xlabel(x_label)
plt.ylabel(y_label)
plt.title(f'Train and Validation Epoch {title}')
plt.legend()
plt.tight_layout()
def plot_single_metric_by_step(data, metric_name, x_label, y_label, title, color):
plt.plot(data[f'{metric_name}'], label=f'{title}', color=color)
plt.xlabel(x_label)
plt.ylabel(y_label)
plt.title(title)
plt.legend()
plt.tight_layout()
def plot_metrics_by_step(data, metric_name, x_label, y_label, colors):
plt.figure(figsize=(14, 6))
plt.subplot(1, 2, 1)
plot_single_metric_by_step(data, f'train_step_{metric_name}', x_label, y_label, f'Train Step {metric_name.capitalize()}', colors[0])
plt.subplot(1, 2, 2)
plot_single_metric_by_step(data, f'val_step_{metric_name}', x_label, y_label, f'Validation Step {metric_name.capitalize()}', colors[1])
plt.tight_layout()
def plot_metrics(file_path):
if not os.path.exists(file_path):
print(f"File {file_path} does not exist.")
return
with open(file_path, 'r') as f:
try:
data = json.load(f)
except json.JSONDecodeError:
print("Invalid JSON file.")
return
directory = os.path.dirname(file_path)
filename_prefix = os.path.basename(file_path).split('.')[0]
plot_metric(data, 'loss', 'Epoch', 'Loss', 'Loss', ['b', 'r'])
plt.savefig(os.path.join(directory, f"{filename_prefix}_train_and_validation_loss.png"))
plt.close()
plot_metric(data, 'perplexity', 'Epoch', 'Perplexity', 'Perplexity', ['g', 'm'])
plt.savefig(os.path.join(directory, f"{filename_prefix}_train_and_validation_perplexity.png"))
plt.close()
plot_metrics_by_step(data, 'loss', 'Step', 'Loss', ['b', 'r'])
plt.savefig(os.path.join(directory, f"{filename_prefix}_train_and_validation_loss_by_step.png"))
plt.close()
plot_metrics_by_step(data, 'perplexity', 'Step', 'Loss', ['g', 'm'])
plt.savefig(os.path.join(directory, f"{filename_prefix}_train_and_validation_perplexity_by_step.png"))
plt.close()
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Plot metrics from JSON file.')
parser.add_argument('--file_path', required=True, type=str, help='Path to the metrics JSON file.')
args = parser.parse_args()
plot_metrics(args.file_path)