variance_analysis / plot_all_variance.py
guanning's picture
Add files using upload-large-folder tool
26f2cbf verified
Raw
History Blame Contribute Delete
3.4 kB
"""Plot variance analysis results for SmolLM (Math), Qwen3 (Math), Maze."""
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import numpy as np
import os
SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
OUTPUT_DIR = os.path.join(SCRIPT_DIR, "outputs")
os.makedirs(OUTPUT_DIR, exist_ok=True)
# ── Data ──────────────────────────────────────────────────────────────────────
rollout_nums = [4, 8, 16, 32, 64, 128]
smollm_math = {
"blTrue": [3.461569e-01, 3.488942e-01, 2.763410e-01, 2.600237e-01, 2.039304e-01, 1.596079e-01],
"blFalse": [5.613685e-01, 4.680250e-01, 3.457040e-01, 2.965937e-01, 2.275286e-01, 1.723276e-01],
}
qwen3_math = {
"blTrue": [1.544762e-01, 1.679264e-01, 2.075920e-01, 1.788574e-01, 1.592376e-01, 1.314381e-01],
"blFalse": [2.140592e-01, 2.190761e-01, 2.448343e-01, 2.002312e-01, 1.702958e-01, 1.390878e-01],
}
maze = {
"blTrue": [9.343412e-02, 7.531368e-02, 5.179188e-02, 4.027390e-02, 2.930888e-02, 2.354821e-02],
"blFalse": [1.171640e-01, 8.123477e-02, 5.614680e-02, 4.236686e-02, 3.015591e-02, 2.521931e-02],
}
datasets = [
("SmolLM-360M (GSM8k)", smollm_math),
("Qwen3-1.7B (Polaris-53K)", qwen3_math),
("Qwen2-3M (Maze)", maze),
]
# ── Style ─────────────────────────────────────────────────────────────────────
plt.rcParams.update({
"font.size": 15,
"axes.titlesize": 18,
"axes.labelsize": 16,
"legend.fontsize": 14,
"xtick.labelsize": 14,
"ytick.labelsize": 14,
"figure.dpi": 150,
"savefig.dpi": 300,
"font.family": "sans-serif",
})
RED = "#D32F2F"
AMBER = "#F9A825"
# ── Plot ──────────────────────────────────────────────────────────────────────
fig, axes = plt.subplots(1, 3, figsize=(21, 6))
for ax, (title, data) in zip(axes, datasets):
xs = np.array(rollout_nums)
bl_true = np.array([v if v is not None else np.nan for v in data["blTrue"]])
bl_false = np.array([v if v is not None else np.nan for v in data["blFalse"]])
ax.plot(xs, bl_true, color=RED, marker="*", markersize=18, linewidth=4,
label="MaxRL", zorder=5)
ax.plot(xs, bl_false, color=AMBER, marker="o", markersize=11, linewidth=4,
label="MaxRL (w/o baseline)", zorder=4)
ax.set_xscale("log", base=2)
ax.set_xticks(rollout_nums)
ax.set_xticklabels([str(n) for n in rollout_nums])
ax.set_xlabel("Number of Rollouts", fontsize=16)
ax.set_ylabel("Gradient Variance", fontsize=16)
ax.set_title(title, fontsize=18, fontweight="bold", pad=12)
ax.legend(loc="upper right", framealpha=0.9, edgecolor="gray")
ax.grid(True, alpha=0.3, linestyle="--")
ax.spines["top"].set_visible(False)
ax.spines["right"].set_visible(False)
plt.tight_layout(w_pad=3)
out_path = os.path.join(OUTPUT_DIR, "variance_comparison_all.png")
plt.savefig(out_path, bbox_inches="tight")
plt.savefig(out_path.replace(".png", ".pdf"), bbox_inches="tight")
print(f"Saved to {out_path}")