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import os
import json
def create_graph(lora_path, lora_name):
try:
import matplotlib.pyplot as plt
from matplotlib.ticker import ScalarFormatter
peft_model_path = f'{lora_path}/training_graph.json'
image_model_path = f'{lora_path}/training_graph.png'
# Check if the JSON file exists
if os.path.exists(peft_model_path):
# Load data from JSON file
with open(peft_model_path, 'r') as file:
data = json.load(file)
# Extract x, y1, and y2 values
x = [item['epoch'] for item in data]
y1 = [item['learning_rate'] for item in data]
y2 = [item['loss'] for item in data]
# Create the line chart
fig, ax1 = plt.subplots(figsize=(10, 6))
# Plot y1 (learning rate) on the first y-axis
ax1.plot(x, y1, 'b-', label='Learning Rate')
ax1.set_xlabel('Epoch')
ax1.set_ylabel('Learning Rate', color='b')
ax1.tick_params('y', colors='b')
# Create a second y-axis
ax2 = ax1.twinx()
# Plot y2 (loss) on the second y-axis
ax2.plot(x, y2, 'r-', label='Loss')
ax2.set_ylabel('Loss', color='r')
ax2.tick_params('y', colors='r')
# Set the y-axis formatter to display numbers in scientific notation
ax1.yaxis.set_major_formatter(ScalarFormatter(useMathText=True))
ax1.ticklabel_format(style='sci', axis='y', scilimits=(0,0))
# Add grid
ax1.grid(True)
# Combine the legends for both plots
lines, labels = ax1.get_legend_handles_labels()
lines2, labels2 = ax2.get_legend_handles_labels()
ax2.legend(lines + lines2, labels + labels2, loc='best')
# Set the title
plt.title(f'{lora_name} LR and Loss vs Epoch')
# Save the chart as an image
plt.savefig(image_model_path)
print(f"Graph saved in {image_model_path}")
else:
print(f"File 'training_graph.json' does not exist in the {lora_path}")
except ImportError:
print("matplotlib is not installed. Please install matplotlib to create PNG graphs") |