can1357
08a941a14e
- Added a new @oh-my-pi/snapcompact package and redirected compaction call sites to it. - Added provider-aware snapcompact shape resolution for model-specific mixed-frame behavior. - Added optional image detail support by extending ImageContent and passing hints through OpenAI providers. - Added native snapcompact render options, including 5x8/8x8 font loading and palette/geometry controls.
172 lines
8.1 KiB
Python
172 lines
8.1 KiB
Python
# /// script
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# requires-python = ">=3.10"
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# dependencies = ["pillow", "numpy"]
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# ///
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"""Render the materialization sweep: rendering choices vs logit-lens confidence."""
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from __future__ import annotations
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import argparse
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import json
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from pathlib import Path
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from typing import Any
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from PIL import Image, ImageDraw, ImageFilter, ImageFont
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HERE = Path(__file__).resolve().parent
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PALETTE = {
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"bg": (5, 7, 10),
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"panel": (12, 17, 23),
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"panel2": (8, 12, 17),
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"ink": (241, 239, 224),
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"muted": (143, 154, 160),
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"grid": (38, 49, 58),
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}
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SERIES = [
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("base-8x13", (143, 154, 160)),
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("repeat2-color", (255, 196, 68)),
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("align-7x14", (148, 255, 117)),
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("align-14x28", (75, 220, 255)),
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("align-28x28", (255, 112, 72)),
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("repeat2-align-14x28", (188, 112, 255)),
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]
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def ui_font(size: int, bold: bool = False) -> ImageFont.ImageFont:
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for path in [
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"/System/Library/Fonts/Supplemental/Arial Bold.ttf" if bold else "/System/Library/Fonts/Supplemental/Arial.ttf",
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"/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf" if bold else "/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf",
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]:
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if Path(path).exists():
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return ImageFont.truetype(path, size)
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return ImageFont.load_default()
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def mono_font(size: int) -> ImageFont.ImageFont:
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for path in ["/System/Library/Fonts/Monaco.ttf", "/usr/share/fonts/truetype/dejavu/DejaVuSansMono.ttf"]:
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if Path(path).exists():
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return ImageFont.truetype(path, size)
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return ImageFont.load_default()
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def crop_answer_region(img_path: Path, cond: dict[str, Any], answer_start: int, answer_end: int, image_size: int = 1568) -> Image.Image:
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img = Image.open(img_path).convert("RGB")
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cols = cond["cols"]
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adv = cond["adv"]
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pitch = cond["pitch"]
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repeat = cond["repeat"]
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row = answer_start // cols
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c0 = answer_start % cols
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c1 = min(cols - 1, (answer_end - 1) % cols)
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y0 = max(0, row * repeat * pitch - pitch)
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y1 = min(image_size, (row * repeat + repeat) * pitch + pitch)
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x0 = max(0, c0 * adv - 10 * adv)
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x1 = min(image_size, (c1 + 1) * adv + 10 * adv)
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crop = img.crop((x0, y0, x1, y1))
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d = ImageDraw.Draw(crop)
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d.rectangle((c0 * adv - x0 - 2, row * repeat * pitch - y0 - 1, (c1 + 1) * adv - x0 + 2, (row * repeat + repeat) * pitch - y0 + 1), outline=(255, 112, 72), width=3)
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return crop
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def main() -> None:
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ap = argparse.ArgumentParser()
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ap.add_argument("--result-dir", default=str(HERE / "results" / "qwen-materialize-sweep-q3"))
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ap.add_argument("--out", default=str(HERE / "results" / "qwen-materialize-sweep-q3" / "materialize-sweep.png"))
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args = ap.parse_args()
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result_dir = Path(args.result_dir)
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summary = json.loads((result_dir / "summary.json").read_text())
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conditions = {c["name"]: c for c in summary["conditions"]}
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q = summary["question"]
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w, h = 2200, 1380
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canvas = Image.new("RGB", (w, h), PALETTE["bg"])
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draw = ImageDraw.Draw(canvas)
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for y in range(0, h, 16):
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draw.line((0, y, w, y), fill=(7, 10 + y % 9, 15 + y % 11))
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glow = Image.new("RGBA", (w, h), (0, 0, 0, 0))
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gd = ImageDraw.Draw(glow)
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gd.ellipse((-240, -200, 900, 700), fill=(75, 220, 255, 25))
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gd.ellipse((1240, 540, 2460, 1480), fill=(255, 112, 72, 24))
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canvas = Image.alpha_composite(canvas.convert("RGBA"), glow.filter(ImageFilter.GaussianBlur(86))).convert("RGB")
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draw = ImageDraw.Draw(canvas)
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draw.text((64, 42), "QWEN MATERIALIZATION SWEEP — CAN RENDERING MOVE THE LAYER?", fill=(255, 196, 68), font=ui_font(24, True))
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draw.text((64, 84), "The depth is the model's; the clarity is yours", fill=PALETTE["ink"], font=ui_font(58, True))
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draw.text(
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(66, 158),
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"Six renderings of the same passage. Logit-lens p(answer BPE) at the answer patch, by layer.\n"
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"Alignment and repetition barely move WHERE it materializes — they transform HOW HARD.",
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fill=PALETTE["muted"],
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font=ui_font(22),
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)
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# Main curve panel.
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panel = (64, 226, 1380, 900)
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draw.rounded_rectangle(panel, radius=26, fill=PALETTE["panel"], outline=(35, 49, 59), width=1)
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draw.text((96, 248), "p(answer BPE) at the best answer patch, per layer", fill=PALETTE["ink"], font=ui_font(26, True))
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gx0, gy0, gx1, gy1 = 150, 320, 1330, 800
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n_layers = len(conditions["base-8x13"]["layers"])
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for i in range(6):
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yy = gy0 + (gy1 - gy0) * i / 5
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draw.line((gx0, yy, gx1, yy), fill=PALETTE["grid"], width=1)
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draw.text((96, yy - 9), f"{1.0 - i / 5:.1f}", fill=PALETTE["muted"], font=ui_font(14))
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for name, color in SERIES:
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cond = conditions.get(name)
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if not cond:
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continue
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pts = []
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for e in cond["layers"]:
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x = gx0 + (gx1 - gx0) * e["layer"] / (n_layers - 1)
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y = gy1 - (gy1 - gy0) * min(1.0, e["best_answer_p"])
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pts.append((round(x), round(y)))
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draw.line(pts, fill=color, width=5 if name != "base-8x13" else 4, joint="curve")
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if cond["lock_on_layer"] is not None:
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lx = gx0 + (gx1 - gx0) * cond["lock_on_layer"] / (n_layers - 1)
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draw.ellipse((lx - 7, gy1 - (gy1 - gy0) * min(1.0, cond["layers"][cond["lock_on_layer"]]["best_answer_p"]) - 7, lx + 7, gy1 - (gy1 - gy0) * min(1.0, cond["layers"][cond["lock_on_layer"]]["best_answer_p"]) + 7), outline=color, width=3)
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draw.text((gx0, gy1 + 16), "layer 0", fill=PALETTE["muted"], font=ui_font(15))
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draw.text((gx1 - 76, gy1 + 16), f"layer {n_layers - 1}", fill=PALETTE["muted"], font=ui_font(15))
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draw.text((gx0 + 320, gy1 + 16), "rings mark lock-on (top-1 becomes an answer BPE)", fill=PALETTE["muted"], font=ui_font(15))
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legend_box = (1420, 226, 2136, 900)
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draw.rounded_rectangle(legend_box, radius=26, fill=PALETTE["panel"], outline=(35, 49, 59), width=1)
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draw.text((1452, 248), "conditions", fill=PALETTE["ink"], font=ui_font(26, True))
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ly = 304
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for name, color in SERIES:
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cond = conditions.get(name)
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if not cond:
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continue
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draw.rounded_rectangle((1452, ly, 1452 + 26, ly + 10), radius=4, fill=color)
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draw.text((1492, ly - 9), name, fill=PALETTE["ink"], font=ui_font(21, True))
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draw.text((1492, ly + 19), cond["note"], fill=PALETTE["muted"], font=ui_font(14))
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draw.text((1492, ly + 42), f"lock-on L{cond['lock_on_layer']} · peak p {cond['max_answer_p']:.2f} · {cond['chars_per_token']} chars/token", fill=color, font=mono_font(14))
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ly += 96
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# Condition cards with real crops.
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card_y = 938
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card_w = 660
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draw.text((64, card_y - 24), "what the model actually saw (answer region outlined)", fill=PALETTE["ink"], font=ui_font(22, True))
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positions = [(64, card_y + 10), (64 + card_w + 24, card_y + 10), (64 + 2 * (card_w + 24), card_y + 10)]
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featured = ["base-8x13", "align-28x28", "repeat2-align-14x28"]
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for (cx, cy), name in zip(positions, featured):
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cond = conditions.get(name)
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if not cond:
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continue
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color = dict(SERIES)[name]
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draw.rounded_rectangle((cx, cy, cx + card_w, cy + 350), radius=20, fill=PALETTE["panel2"], outline=(34, 48, 58), width=1)
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draw.text((cx + 22, cy + 14), name, fill=color, font=ui_font(23, True))
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draw.text((cx + 22, cy + 46), cond["note"], fill=PALETTE["muted"], font=ui_font(15))
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crop = crop_answer_region(result_dir / "images" / f"{name}.png", cond, q["answer_start"], q["answer_end"])
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scale = min((card_w - 44) / crop.width, 200 / crop.height)
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crop_r = crop.resize((round(crop.width * scale), round(crop.height * scale)), Image.Resampling.NEAREST)
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draw.rounded_rectangle((cx + 20, cy + 76, cx + card_w - 20, cy + 286), radius=12, fill=(244, 242, 230))
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canvas.paste(crop_r, (cx + 22 + (card_w - 44 - crop_r.width) // 2, cy + 78 + (206 - crop_r.height) // 2))
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draw.text((cx + 22, cy + 300), f"lock-on L{cond['lock_on_layer']} · peak p {cond['max_answer_p']:.2f} · {cond['chars_per_token']} chars/token · gen “{cond['generation']}”", fill=PALETTE["ink"], font=ui_font(16, True))
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out = Path(args.out)
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out.parent.mkdir(parents=True, exist_ok=True)
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canvas.save(out)
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print(out)
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if __name__ == "__main__":
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main()
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