File size: 2,391 Bytes
91c8e18 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 | import matplotlib.pyplot as plt
import numpy as np
# Set up the figure and axis
fig, ax = plt.subplots(figsize=(12, 7))
# Define categories and data
categories = ['v4.57.6\ndevice_map=auto\nThreadpool',
'v4.57.6\ndevice_map=auto\nNormal',
'v4.57.6\nTP',
'v5\ndevice_map=auto\nAsync',
'v5\ndevice_map=auto\nSync',
'v5\nTP\nAsync',
'v5\nTP\nSync']
times = [66.24, 67.29, np.nan, 20.71, 45.3, 10.1, 19.28]
colors = ['#3498db', '#2980b9', '#e74c3c', '#2ecc71', '#27ae60', '#f39c12', '#e67e22']
# Create bar positions
x_pos = np.arange(len(categories))
# Create bars
bars = ax.bar(x_pos, times, color=colors, alpha=0.8, edgecolor='black', linewidth=1.2)
# Add value labels on top of bars
for i, (bar, time) in enumerate(zip(bars, times)):
if np.isnan(time):
# Mark OOM with text
ax.text(bar.get_x() + bar.get_width()/2, 5, 'OOM',
ha='center', va='bottom', fontsize=12, fontweight='bold', color='red')
else:
ax.text(bar.get_x() + bar.get_width()/2, time + 1.5, f'{time}s',
ha='center', va='bottom', fontsize=10, fontweight='bold')
# Customize the plot
ax.set_xlabel('Configuration', fontsize=12, fontweight='bold')
ax.set_ylabel('Loading Time (seconds)', fontsize=12, fontweight='bold')
ax.set_title('Model Loading Benchmark: Qwen/Qwen1.5-110B-Chat\nGPU: 1x A100 (80 GB)',
fontsize=14, fontweight='bold', pad=20)
ax.set_xticks(x_pos)
ax.set_xticklabels(categories, fontsize=9, ha='center')
ax.set_ylim(0, max([t for t in times if not np.isnan(t)]) * 1.15)
# Add grid for better readability
ax.yaxis.grid(True, linestyle='--', alpha=0.3)
ax.set_axisbelow(True)
# Add a note about the versions
# note_text = ('Transformers v4.57.6:\n'
# ' • Threadpool: HF_ENABLE_PARALLEL_LOADING\n'
# ' • Normal: no threadpool\n'
# '\n'
# 'Transformers v5:\n'
# ' • Async: default behavior\n'
# ' • Sync: HF_DEACTIVATE_ASYNC_LOAD')
# ax.text(1.02, 0.5, note_text, transform=ax.transAxes,
# fontsize=9, verticalalignment='center',
# bbox=dict(boxstyle='round', facecolor='wheat', alpha=0.3))
plt.tight_layout()
plt.savefig('loading_benchmark.png', dpi=300, bbox_inches='tight')
plt.show()
print("Plot saved as 'loading_benchmark.png'")
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