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plot_bench.py

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+#!/usr/bin/env python3
+import matplotlib.pyplot as plt
+import numpy as np
+
+batch_size_4 = {
+   "A100": [4.75, 3.26, 3.24, 3.10],  # those values are made up
+   "A10": [13.94, 9.81, 10.01, 9.35],
+   "T4": [38.81, 30.09, 29.74, 27.55],
+   "V100": [9.84, 8.16, 8.09, 7.65],
+   "3090": [10.04, 7.82, 7.89, 7.47],
+   "3090TI": [9.07, 7.14, 7.15, 6.81],
+}
+
+batch_size_16 = {
+   "A100": [18.95, 13.57, 13.67, 12.25],
+   "A10": [0, 37.55, 38.31, 36.81],
+   "T4": [0, 111.47, 113.26, 106.93],
+   "V100": [0, 30.29, 29.84, 28.22],
+   "3090": [0, 29.06, 29.06, 28.2],
+   "3090TI": [0, 26.1, 26.28, 25.46],
+}
+
+batch_sizes = batch_size_16
+
+methods = {
+    "Vanilla Attention": [x[0] for x in batch_sizes.values()],
+    "xFormers": [x[1] for x in batch_sizes.values()],
+    "PyTorch2.0 SDPA": [x[2] for x in batch_sizes.values()],
+    "SDPA + torch.compile": [x[3] for x in batch_sizes.values()],
+}
+
+x = np.arange(len(batch_size_4))  # the label locations
+width = 0.15  # the width of the bars
+multiplier = 0
+
+fig, ax = plt.subplots(constrained_layout=True)
+
+for attribute, measurement in methods.items():
+    offset = width * multiplier
+    rects = ax.bar(x + offset, measurement, width, label=attribute)
+    ax.bar_label(rects, padding=3)
+    multiplier += 1
+
+# Add some text for labels, title and custom x-axis tick labels, etc.
+ax.set_ylabel('Time (s)')
+ax.set_title('Inference Speed at Batch Size=4')
+ax.set_xticks(x + width, batch_size_4)
+ax.legend(loc='upper left')
+ax.set_ylim(0, 250)
+
+plt.show()