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Text is tokenized as raw UTF-8 bytes, so any string is accepted. What the model
*understands* is whatever this world teaches it: many colours and shapes, single-
object events (moving, falling, jumping, orbiting, fading, changing colour ...)
and two-object interactions (merging with colour mixing, splitting, colliding,
chasing, orbiting, swapping places), each described with many paraphrases.
Every clip comes with per-frame, per-object ground truth in `meta` for scoring.
"""
from __future__ import annotations
import math
import re
import zlib
from dataclasses import dataclass
import numpy as np
import torch
# ---------------------------------------------------------------- tokenizer
PAD, NULL, BOS = 256, 257, 258
BYTE_VOCAB = 259
MAX_BYTES = 256
class ByteTokenizer:
"""UTF-8 bytes -> ids. No vocabulary: every string is representable."""
vocab_size = BYTE_VOCAB
def __init__(self, max_len: int = MAX_BYTES):
self.max_len = max_len
def encode(self, caption: str) -> list[int]:
return [BOS] + list(caption.encode("utf-8"))[: self.max_len - 1]
def __call__(self, captions: list[str], pad_to_longest: bool = True) -> torch.Tensor:
"""[B, L] ids; L = longest caption in the batch (dynamic padding) or max_len."""
encoded = [self.encode(c) for c in captions]
L = max(map(len, encoded)) if pad_to_longest else self.max_len
out = torch.full((len(captions), L), PAD, dtype=torch.long)
for i, ids in enumerate(encoded):
out[i, : len(ids)] = torch.tensor(ids)
return out
def null(self, n: int, length: int = 1) -> torch.Tensor:
out = torch.full((n, length), PAD, dtype=torch.long)
out[:, 0] = NULL
return out
SEP = 259
HASH_OFFSET, HASH_BUCKETS = 260, 16384
HYBRID_VOCAB = HASH_OFFSET + HASH_BUCKETS
MAX_HYBRID = 320
_WORD = re.compile(r"[^\W_]+", re.UNICODE)
def word_bucket(word: str) -> int:
"""Stable hash of a case-folded word into one of HASH_BUCKETS ids (no vocabulary; any word maps somewhere)."""
return HASH_OFFSET + zlib.crc32(word.casefold().encode("utf-8")) % HASH_BUCKETS
class HybridTokenizer(ByteTokenizer):
"""[BOS] utf-8 bytes [SEP] hashed words. Bytes keep spelling; hashed words give the encoder word identity
from the first step. Still no vocabulary: every string encodes, nothing is UNK."""
vocab_size = HYBRID_VOCAB
def __init__(self, max_len: int = MAX_HYBRID, max_bytes: int = MAX_BYTES):
super().__init__(max_len)
self.max_bytes = max_bytes
def encode(self, caption: str) -> list[int]:
words = [word_bucket(w) for w in _WORD.findall(caption)]
byte_ids = list(caption.encode("utf-8"))[: self.max_bytes - 1]
room = self.max_len - 2 - len(byte_ids)
return [BOS] + byte_ids + [SEP] + words[: max(0, room)]
# ---------------------------------------------------------------- the world's nouns
COLORS = {
"red": (225, 35, 35), "orange": (250, 140, 20), "yellow": (245, 220, 40), "green": (40, 190, 60),
"cyan": (40, 215, 230), "blue": (45, 85, 240), "purple": (145, 55, 215), "pink": (250, 125, 190),
"brown": (135, 80, 35), "white": (245, 245, 245), "gray": (140, 140, 140), "black": (12, 12, 12),
}
COLOR_WORDS = {
"red": ["red", "red", "red", "crimson", "scarlet"], "orange": ["orange"], "yellow": ["yellow", "yellow", "golden"],
"green": ["green", "green", "lime"], "cyan": ["cyan", "cyan", "turquoise", "light blue"],
"blue": ["blue", "blue", "dark blue"], "purple": ["purple", "purple", "violet"], "pink": ["pink"],
"brown": ["brown"], "white": ["white"], "gray": ["gray", "grey", "silver"], "black": ["black"],
}
# Two colours that merge make this one (order-free). Pairs not listed blend to the nearest named colour.
MIX = {
frozenset(["red", "blue"]): "purple", frozenset(["red", "yellow"]): "orange",
frozenset(["blue", "yellow"]): "green", frozenset(["red", "white"]): "pink",
frozenset(["black", "white"]): "gray", frozenset(["blue", "green"]): "cyan",
frozenset(["red", "green"]): "brown", frozenset(["blue", "white"]): "cyan",
frozenset(["purple", "white"]): "pink", frozenset(["orange", "blue"]): "brown",
}
SHAPES = ["circle", "square", "triangle", "star", "ring", "cross", "heart", "diamond", "hexagon"]
SHAPE_WORDS = {
"circle": ["circle", "circle", "circle", "ball", "dot", "disc"], "square": ["square", "square", "box", "block"],
"triangle": ["triangle"], "star": ["star"], "ring": ["ring", "ring", "donut"], "cross": ["cross", "plus sign"],
"heart": ["heart"], "diamond": ["diamond"], "hexagon": ["hexagon"],
}
ROTATION_INVARIANT = {"circle", "ring"}
SIZES = {"tiny": 0.085, "small": 0.115, "medium": 0.155, "big": 0.205, "huge": 0.26}
SIZE_WORDS = {"tiny": ["tiny"], "small": ["small", "little"], "medium": [""], "big": ["big", "large"],
"huge": ["huge", "giant"]}
BACKGROUNDS = { # name -> (top rgb, bottom rgb)
"black": ((0, 0, 0), (0, 0, 0)), "white": ((250, 250, 250), (250, 250, 250)),
"gray": ((120, 120, 120), (120, 120, 120)), "navy": ((10, 15, 70), (10, 15, 70)),
"sky": ((110, 170, 240), (200, 230, 255)), "sunset": ((90, 40, 130), (250, 150, 60)),
"grass": ((120, 190, 250), (40, 140, 40)),
}
BG_PHRASES = {
"black": ["on a black background", "against a black background", "on black", "in the dark", "in darkness"],
"white": ["on a white background", "against a white background", "on white", "on a blank white page"],
"gray": ["on a gray background", "on a grey background", "against a gray wall"],
"navy": ["at night", "in the night sky", "on a dark blue background", "on a navy background"],
"sky": ["in the sky", "in a blue sky", "against the sky", "in the daytime sky"],
"sunset": ["at sunset", "in a sunset sky", "against a sunset", "at dusk"],
"grass": ["over a field of grass", "above green grass", "over a meadow", "in a grassy field"],
}
DIRS = {
"left": (-1, 0), "right": (1, 0), "up": (0, -1), "down": (0, 1),
"up-left": (-1, -1), "up-right": (1, -1), "down-left": (-1, 1), "down-right": (1, 1),
}
DIR_PHRASES = {
"left": ["left", "to the left", "leftward", "toward the left", "from right to left"],
"right": ["right", "to the right", "rightward", "toward the right", "from left to right"],
"up": ["up", "upward", "upwards", "toward the top", "from bottom to top"],
"down": ["down", "downward", "downwards", "toward the bottom", "from top to bottom"],
"up-left": ["up and to the left", "diagonally up left", "toward the top left", "up-left"],
"up-right": ["up and to the right", "diagonally up right", "toward the top right", "up-right"],
"down-left": ["down and to the left", "diagonally down left", "toward the bottom left", "down-left"],
"down-right": ["down and to the right", "diagonally down right", "toward the bottom right", "down-right"],
}
MOVE_VERBS = ["moves", "moves", "slides", "drifts", "travels", "goes", "glides", "floats", "heads"]
MOVE_VERBS_ING = ["moving", "sliding", "drifting", "traveling", "going", "gliding", "floating", "heading"]
SINGLE_EVENTS = {"move": 4, "fall": 1, "rise": 1, "jump": 1, "bounce": 1, "zigzag": 1, "circle": 1, "grow": 1,
"shrink": 1, "spin": 1, "still": 1, "fade_in": 1, "fade_out": 1, "blink": 1, "recolor": 1.5,
"teleport": 0.7}
PAIR_EVENTS = {"merge": 9, "split": 1.2, "collide": 1, "chase": 1, "orbit": 1, "swap": 1, "independent": 1.8}
# (event kind, shape) combinations never rendered in the training split: a generalisation test.
HELDOUT = {("merge", "star"), ("jump", "heart"), ("orbit", "hexagon"), ("fall", "diamond"), ("spin", "cross"),
("recolor", "triangle")}
@dataclass
class WorldConfig:
frames: int = 16
size: int = 32
supersample: int = 2
p_pair: float = 0.5 # with PAIR_EVENTS weights -> ~30% of clips are merges
p_featured: float = 0.04 # the user's own example: a red and a blue circle merge into a purple circle
merge_weight: float = 9.0 # relative weight of "merge" among PAIR_EVENTS (phase 3 lowers it: merges took over)
p_mention_bg: float = 0.5
p_default_black: float = 0.7 # background when the caption does not mention one
def _choice(rng, seq):
return seq[rng.integers(len(seq))]
def _weighted(rng, weights: dict):
keys = list(weights)
p = np.array([weights[k] for k in keys], float)
return keys[rng.choice(len(keys), p=p / p.sum())]
def _contrast_ok(rgb, bg: str) -> bool:
top, bottom = (np.array(c, float) for c in BACKGROUNDS[bg])
c = np.array(rgb, float)
return min(np.linalg.norm(c - top), np.linalg.norm(c - bottom)) > 110
def nearest_color(rgb) -> str:
c = np.array(rgb, float)
return min(COLORS, key=lambda k: np.linalg.norm(c - np.array(COLORS[k], float)))
def mix_colors(a: str, b: str) -> str:
if a == b:
return a
return MIX.get(frozenset([a, b])) or nearest_color((np.array(COLORS[a]) + np.array(COLORS[b])) / 2)
# ---------------------------------------------------------------- phrasing
def noun_phrase(rng, obj: dict, article: str | None = None) -> str:
size = _choice(rng, SIZE_WORDS[obj["size"]])
color = _choice(rng, COLOR_WORDS[obj["color"]])
shape = _choice(rng, SHAPE_WORDS[obj["shape"]])
if article is None:
article = _choice(rng, ["a", "a", "a", "the", "one", ""])
if article.endswith("bigger"):
size = ""
if article == "a" and (size or color)[:1] in "aeiou":
article = "an"
return " ".join(w for w in (article, size, color, shape) if w)
def _move_phrase(rng, d: str) -> str:
dp = _choice(rng, DIR_PHRASES[d])
if d == "up" and rng.random() < 0.25:
return _choice(rng, ["rises", "floats up", "goes up"])
return f"{_choice(rng, MOVE_VERBS)} {dp}"
def describe_single(rng, obj: dict, ev: dict) -> str:
np_ = noun_phrase(rng, obj)
k = ev["kind"]
if k == "move":
vp = _move_phrase(rng, ev["dir"])
if rng.random() < 0.2:
vp = f"{_choice(rng, MOVE_VERBS_ING)} {_choice(rng, DIR_PHRASES[ev['dir']])}"
return f"{np_} {vp}" if rng.random() < 0.5 else f"{np_}, {vp}"
return f"{np_} {vp}"
if k == "fall":
return f"{np_} {_choice(rng, ['falls', 'falls down', 'drops', 'drops down', 'falls from the top'])}"
if k == "rise":
return f"{np_} {_choice(rng, ['rises from the bottom', 'rises up', 'floats up from the bottom', 'launches upward'])}"
if k == "jump":
d = ev.get("dir")
tail = f" {_choice(rng, ['to the left', 'left'])}" if d == "left" else f" {_choice(rng, ['to the right', 'right'])}" if d == "right" else ""
return f"{np_} {_choice(rng, ['jumps', 'hops', 'leaps'])}{tail}"
if k == "bounce":
return f"{np_} {_choice(rng, ['bounces around', 'bounces', 'bounces off the walls', 'ricochets around'])}"
if k == "zigzag":
return f"{np_} {_choice(rng, ['zigzags', 'moves in a zigzag'])} {_choice(rng, DIR_PHRASES[ev['dir']][:3])}"
if k == "circle":
return f"{np_} {_choice(rng, ['moves in a circle', 'goes around in a circle', 'circles around', 'travels in a loop'])}"
if k == "grow":
return f"{np_} {_choice(rng, ['grows', 'gets bigger', 'expands', 'grows larger', 'inflates'])}"
if k == "shrink":
return f"{np_} {_choice(rng, ['shrinks', 'gets smaller', 'shrinks away', 'deflates'])}"
if k == "spin":
return f"{np_} {_choice(rng, ['spins', 'rotates', 'spins in place', 'twirls'])}"
if k == "still":
return f"{np_} {_choice(rng, ['stays still', 'sits still', 'does not move', 'stays in place', 'is resting'])}"
if k == "fade_in":
return f"{np_} {_choice(rng, ['fades in', 'appears', 'slowly appears', 'materializes'])}"
if k == "fade_out":
return f"{np_} {_choice(rng, ['fades out', 'disappears', 'fades away', 'vanishes'])}"
if k == "blink":
return f"{np_} {_choice(rng, ['blinks', 'flashes', 'flickers', 'blinks on and off'])}"
if k == "recolor":
to = _choice(rng, COLOR_WORDS[ev["to"]])
return f"{np_} {_choice(rng, ['turns', 'changes to', 'becomes', 'changes color to', 'turns into a'])} {to}".replace(
"turns into a " + to, f"turns into a {to} {_choice(rng, SHAPE_WORDS[obj['shape']])}")
if k == "teleport":
return f"{np_} {_choice(rng, ['teleports', 'jumps to another spot', 'teleports across the screen'])}"
raise ValueError(k)
def describe_pair(rng, a: dict, b: dict, ev: dict) -> str:
k = ev["kind"]
A, B = noun_phrase(rng, a), noun_phrase(rng, b)
if k == "merge":
res = ev["result"]
verb = _choice(rng, ["merge into", "merge into", "combine into", "fuse into", "blend into", "join to form",
"come together to form", "melt together into"])
tail = f" {verb} {noun_phrase(rng, res, article=_choice(rng, ['a', 'one', 'a single', 'a bigger']))}"
if rng.random() < 0.25:
tail = f" {_choice(rng, ['merge', 'merge together', 'fuse together', 'combine'])}"
return f"{A} and {B}{tail}"
if k == "split":
src = ev["source"]
S = noun_phrase(rng, src)
if rng.random() < 0.25:
return f"{S} {_choice(rng, ['splits in two', 'splits into two', 'divides in half', 'breaks in two'])}"
return f"{S} {_choice(rng, ['splits into', 'breaks into', 'divides into', 'separates into'])} {noun_phrase(rng, a, 'a')} and {noun_phrase(rng, b, 'a')}"
if k == "collide":
return f"{A} and {B} {_choice(rng, ['collide and bounce apart', 'crash into each other', 'bump into each other', 'collide', 'smash together and bounce off'])}"
if k == "chase":
if rng.random() < 0.3:
return f"{B} is chased by {A}"
return f"{A} {_choice(rng, ['chases', 'follows', 'runs after', 'is chasing'])} {B}"
if k == "orbit":
return f"{A} {_choice(rng, ['orbits', 'circles around', 'revolves around', 'goes around'])} {B}"
if k == "swap":
return f"{A} and {B} {_choice(rng, ['swap places', 'trade places', 'switch places', 'swap positions'])}"
if k == "independent":
return f"{describe_single(rng, a, ev['a'])} {_choice(rng, ['and', 'and', 'while', ', and'])} {describe_single(rng, b, ev['b'])}".replace(" , and", ", and")
raise ValueError(k)
def _style(rng, caption: str, bg_phrase: str | None) -> str:
if bg_phrase:
caption = f"{bg_phrase}, {caption}" if rng.random() < 0.2 else f"{caption} {bg_phrase}"
if rng.random() < 0.08:
caption = _choice(rng, ["a video of ", "watch as ", "animation: ", "clip: "]) + caption
if rng.random() < 0.3:
caption = caption[0].upper() + caption[1:]
if rng.random() < 0.25:
caption += "."
return caption.strip()
# ---------------------------------------------------------------- dynamics (normalised coords, t in [0,1])
def _uni(rng, lo, hi, size=None):
"""rng.uniform that tolerates an empty range (big objects in a small frame): collapses to the midpoint."""
if hi < lo:
lo = hi = (lo + hi) / 2
return rng.uniform(lo, hi, size=size)
def _state(x, y, r, ang, rgb, alpha=1.0):
return [float(x), float(y), float(r), float(ang), tuple(float(c) for c in rgb), float(alpha)]
def _single_states(rng, obj: dict, ev: dict, T: int, center=None) -> list:
r = SIZES[obj["size"]] * _uni(rng, 0.92, 1.08)
ang0 = _uni(rng, 0, 2 * math.pi)
rgb = np.array(COLORS[obj["color"]], float)
ts = np.linspace(0, 1, T)
k = ev["kind"]
m = r + 0.03
def anywhere():
return _uni(rng, m, 1 - m, size=2)
if k == "move":
dx, dy = DIRS[ev["dir"]]
dist = _uni(rng, 0.4, 0.62) / (math.sqrt(2) if dx and dy else 1)
dist = min(dist, (1 - 2 * m) * 0.98)
def start(d):
if d > 0:
return _uni(rng, m, 1 - m - dist)
if d < 0:
return _uni(rng, m + dist, 1 - m)
return _uni(rng, m, 1 - m)
x0, y0 = start(dx), start(dy)
return [_state(x0 + dx * dist * t, y0 + dy * dist * t, r, ang0, rgb) for t in ts]
if k in ("fall", "rise"):
x0 = _uni(rng, m, 1 - m)
top, bot = m, 1 - m
prog = ts ** 2 if k == "fall" else 1 - (1 - ts) ** 2
return [_state(x0, top + (bot - top) * p if k == "fall" else bot - (bot - top) * p, r, ang0, rgb) for p in prog]
if k == "jump":
d = {"left": -1, "right": 1}.get(ev.get("dir"), 0)
span = min(_uni(rng, 0.3, 0.5), max(0.0, 1 - 2 * m - 0.02)) * d
x0 = _uni(rng, m + max(0, -span), 1 - m - max(0, span))
ground = 1 - m
height = _uni(rng, 0.35, min(0.6, 1 - 2 * m))
return [_state(x0 + span * t, ground - height * 4 * t * (1 - t), r, ang0, rgb) for t in ts]
if k == "bounce":
lo, hi = m, 1 - m
x, y = anywhere()
th = _uni(rng, 0, 2 * math.pi)
sp = _uni(rng, 1.6, 2.4)
vx, vy = sp * math.cos(th), sp * math.sin(th)
out, dt = [], 1 / (T - 1)
for _ in range(T):
out.append(_state(x, y, r, ang0, rgb))
x, y = x + vx * dt, y + vy * dt
if x < lo or x > hi:
vx, x = -vx, float(np.clip(2 * np.clip(x, lo, hi) - x, lo, hi))
if y < lo or y > hi:
vy, y = -vy, float(np.clip(2 * np.clip(y, lo, hi) - y, lo, hi))
return out
if k == "zigzag":
dx, dy = DIRS[ev["dir"]]
dist = min(_uni(rng, 0.45, 0.6), 1 - 2 * m - 0.1)
amp = _uni(rng, 0.08, 0.14)
along0 = _uni(rng, m, 1 - m - dist) if (dx + dy) > 0 else _uni(rng, m + dist, 1 - m)
across0 = _uni(rng, m + amp, 1 - m - amp)
out = []
for t in ts:
along = along0 + (dx + dy) * dist * t
zig = amp * (2 * abs((t * 3) % 1 - 0.5) * 2 - 1)
x, y = (along, across0 + zig) if dx else (across0 + zig, along)
out.append(_state(x, y, r, ang0, rgb))
return out
if k == "circle":
R = _uni(rng, 0.18, max(0.19, 0.5 - m - 0.02))
cx, cy = center if center is not None else (_uni(rng, m + R, 1 - m - R), _uni(rng, m + R, 1 - m - R))
ph = _uni(rng, 0, 2 * math.pi)
sgn = _choice(rng, [-1, 1])
turns = _uni(rng, 0.8, 1.0)
return [_state(cx + R * math.cos(ph + sgn * 2 * math.pi * turns * t), cy + R * math.sin(ph + sgn * 2 * math.pi * turns * t),
r, ang0, rgb) for t in ts]
if k in ("grow", "shrink"):
mm = r * 1.7 + 0.03
x0, y0 = _uni(rng, mm, 1 - mm, size=2)
f = (lambda t: 0.45 + 1.25 * t) if k == "grow" else (lambda t: 1.7 - 1.25 * t)
return [_state(x0, y0, r * f(t), ang0, rgb) for t in ts]
x0, y0 = anywhere()
if k == "spin":
sp = _choice(rng, [-1, 1]) * _uni(rng, 0.7, 1.1) * math.pi
return [_state(x0, y0, r, ang0 + sp * t, rgb) for t in ts]
if k == "still":
return [_state(x0, y0, r, ang0, rgb) for t in ts]
if k == "fade_in":
return [_state(x0, y0, r, ang0, rgb, min(1, max(0, (t - 0.1) / 0.6))) for t in ts]
if k == "fade_out":
return [_state(x0, y0, r, ang0, rgb, min(1, max(0, (0.9 - t) / 0.6))) for t in ts]
if k == "blink":
period = _choice(rng, [4, 4, 6])
return [_state(x0, y0, r, ang0, rgb, 1.0 if (i // (period // 2)) % 2 == 0 else 0.0) for i in range(T)]
if k == "recolor":
rgb2 = np.array(COLORS[ev["to"]], float)
out = []
for t in ts:
w = min(1, max(0, (t - 0.3) / 0.4))
out.append(_state(x0, y0, r, ang0, (1 - w) * rgb + w * rgb2))
return out
if k == "teleport":
x1, y1 = max((anywhere() for _ in range(8)), key=lambda p: math.hypot(p[0] - x0, p[1] - y0))
cut = rng.integers(T // 3, 2 * T // 3)
return [_state(x0, y0, r, ang0, rgb) if i < cut else _state(x1, y1, r, ang0, rgb) for i in range(T)]
raise ValueError(k)
def _pair_states(rng, a: dict, b: dict, ev: dict, T: int):
ra = SIZES[a["size"]] * _uni(rng, 0.92, 1.08)
rb = SIZES[b["size"]] * _uni(rng, 0.92, 1.08)
ca, cb = np.array(COLORS[a["color"]], float), np.array(COLORS[b["color"]], float)
angA, angB = _uni(rng, 0, 2 * math.pi, size=2)
ts = np.linspace(0, 1, T)
k = ev["kind"]
if k in ("merge", "split"):
res = ev["result"] if k == "merge" else ev["source"]
rr = SIZES[res["size"]]
cr = np.array(COLORS[res["color"]], float)
mid = _uni(rng, 0.32, 0.68, size=2)
th = _uni(rng, 0, math.pi)
sep = _uni(rng, 0.62, 0.8)
u = np.array([math.cos(th), math.sin(th)])
pa = np.clip(mid - u * sep / 2, ra + 0.02, 1 - ra - 0.02)
pb = np.clip(mid + u * sep / 2, rb + 0.02, 1 - rb - 0.02)
SA, SB, SR = [], [], []
for t in ts:
tm = t if k == "merge" else 1 - t
p = min(1, tm / 0.6) # approach
f = min(1, max(0, (tm - 0.5) / 0.25)) # fuse
xa = pa + (mid - pa) * p
xb = pb + (mid - pb) * p
SA.append(_state(*xa, ra * (1 - f) + rr * f, angA, ca * (1 - f) + cr * f, 1 - f))
SB.append(_state(*xb, rb * (1 - f) + rr * f, angB, cb * (1 - f) + cr * f, 1 - f))
SR.append(_state(*mid, rr * (0.6 + 0.4 * f), angA, cr, f))
return [SA, SB, SR]
if k == "collide":
y = _uni(rng, 0.3, 0.7)
vert = rng.random() < 0.3
hit = _uni(rng, 0.4, 0.6)
xa0, xb0 = _uni(rng, 0.05, 0.2) + ra, 1 - _uni(rng, 0.05, 0.2) - rb
contact = (xa0 * rb + xb0 * ra) / (ra + rb) # where they touch if both move at equal speed
SA, SB = [], []
for t in ts:
if t <= hit:
s = t / hit
xa = xa0 + (contact - ra - xa0) * s
xb = xb0 + (contact + rb - xb0) * s
else:
s = (t - hit) / (1 - hit)
xa = contact - ra - (contact - ra - xa0) * s * 0.8
xb = contact + rb + (xb0 - contact - rb) * s * 0.8
pa, pb = (y, xa) if vert else (xa, y), (y, xb) if vert else (xb, y)
SA.append(_state(*pa, ra, angA, ca))
SB.append(_state(*pb, rb, angB, cb))
return [SA, SB]
if k == "chase":
lead = _single_states(rng, b, {"kind": _choice(rng, ["move", "circle", "zigzag"]), "dir": _choice(rng, ["left", "right", "up", "down"])}, T)
lag = 4
SA = []
for i in range(T):
j = i - lag
if j >= 0:
x, y = lead[j][0], lead[j][1]
else: # extrapolate backwards along the leader's initial velocity
vx, vy = lead[1][0] - lead[0][0], lead[1][1] - lead[0][1]
x, y = lead[0][0] + vx * j, lead[0][1] + vy * j
SA.append(_state(np.clip(x, ra, 1 - ra), np.clip(y, ra, 1 - ra), ra, angA, ca))
SB = [[s[0], s[1], rb, angB, tuple(cb), 1.0] for s in lead]
return [SA, SB]
if k == "orbit":
R = _uni(rng, 0.24, 0.32)
c = (_uni(rng, 0.5 - (0.5 - R - ra - 0.02), 0.5 + (0.5 - R - ra - 0.02)),
_uni(rng, 0.5 - (0.5 - R - ra - 0.02), 0.5 + (0.5 - R - ra - 0.02)))
SA = _single_states(rng, a, {"kind": "circle"}, T, center=c)
SA = [[s[0], s[1], ra, angA, tuple(ca), 1.0] for s in SA]
SB = [_state(*c, rb, angB, cb) for _ in ts]
return [SA, SB]
if k == "swap":
p0 = _uni(rng, 0.25, 0.75, size=2)
th = _uni(rng, 0, 2 * math.pi)
R = _uni(rng, 0.2, 0.28)
c = np.clip(p0, R + 0.12, 1 - R - 0.12)
SA, SB = [], []
for t in ts:
ph = th + math.pi * t
SA.append(_state(c[0] + R * math.cos(ph), c[1] + R * math.sin(ph), ra, angA, ca))
SB.append(_state(c[0] - R * math.cos(ph), c[1] - R * math.sin(ph), rb, angB, cb))
return [SA, SB]
if k == "independent":
return [_single_states(rng, a, ev["a"], T), _single_states(rng, b, ev["b"], T)]
raise ValueError(k)
# ---------------------------------------------------------------- sampling a scene
def _random_obj(rng, bg: str, shape=None, color=None, size=None) -> dict:
while True:
o = {"shape": shape or _choice(rng, SHAPES), "color": color or _choice(rng, list(COLORS)),
"size": size or _choice(rng, list(SIZES))}
if _contrast_ok(COLORS[o["color"]], bg):
return o
color = None
def _random_single_event(rng, obj: dict, bg: str) -> dict:
while True:
k = _weighted(rng, SINGLE_EVENTS)
if k == "spin" and obj["shape"] in ROTATION_INVARIANT:
continue
ev = {"kind": k}
if k in ("move", "zigzag"):
ev["dir"] = _choice(rng, list(DIRS) if k == "move" else ["left", "right", "up", "down"])
if k == "jump":
ev["dir"] = _choice(rng, ["left", "right", None])
if k == "recolor":
to = _choice(rng, [c for c in COLORS if c != obj["color"] and _contrast_ok(COLORS[c], bg)])
ev["to"] = to
return ev
def is_heldout(scene: dict) -> bool:
kinds = [scene["event"]["kind"]]
if kinds[0] == "independent":
kinds = [scene["event"]["a"]["kind"], scene["event"]["b"]["kind"]]
shapes = [o["shape"] for o in scene["objects"]]
res = scene["event"].get("result") or scene["event"].get("source")
if res:
shapes.append(res["shape"])
return any((k, sh) in HELDOUT for k in kinds for sh in shapes)
def featured_scene(rng, bg: str = "black", mention_bg: bool = False) -> dict:
"""The user's example: a red circle and a blue circle merge into a purple circle."""
small = ["tiny", "small", "small", "medium"]
a = {"shape": "circle", "color": "red", "size": _choice(rng, small)}
b = {"shape": "circle", "color": "blue", "size": _choice(rng, small)}
if rng.random() < 0.5:
a, b = b, a
res = {"shape": "circle", "color": "purple", "size": _choice(rng, ["medium", "big"])}
return {"objects": [a, b], "event": {"kind": "merge", "result": res}, "bg": bg, "mention_bg": mention_bg}
def random_scene(rng, cfg: WorldConfig, split: str = "train") -> dict:
"""split: 'train' (never a HELDOUT combo), 'heldout' (always one), 'any'."""
while True:
scene = _random_scene(rng, cfg)
if split == "any" or (split == "heldout") == is_heldout(scene):
return scene
def _random_scene(rng, cfg: WorldConfig) -> dict:
if rng.random() < cfg.p_featured:
mention_bg = rng.random() < cfg.p_mention_bg
bg = _choice(rng, ["black", "white", "gray", "sky", "grass"]) if mention_bg else "black"
return featured_scene(rng, bg, mention_bg)
mention_bg = rng.random() < cfg.p_mention_bg
bg = _choice(rng, list(BACKGROUNDS)) if (mention_bg or rng.random() > cfg.p_default_black) else "black"
if rng.random() >= cfg.p_pair:
o = _random_obj(rng, bg, size=_choice(rng, ["small", "medium", "medium", "big", "big", "huge", "tiny"]))
return {"objects": [o], "event": _random_single_event(rng, o, bg), "bg": bg, "mention_bg": mention_bg}
k = _weighted(rng, {**PAIR_EVENTS, "merge": cfg.merge_weight})
small = ["tiny", "small", "small", "medium"]
if k in ("merge", "split"):
a = _random_obj(rng, bg, size=_choice(rng, small))
partners = [next(iter(pair - {a["color"]})) for pair in MIX if a["color"] in pair]
b_color = _choice(rng, partners) if partners and rng.random() < 0.8 else a["color"]
if not _contrast_ok(COLORS[b_color], bg):
return _random_scene(rng, cfg)
b = _random_obj(rng, bg, color=b_color, size=_choice(rng, small))
if rng.random() < 0.6: # same shape most of the time, so the result's shape is unambiguous
b["shape"] = a["shape"]
mixed = mix_colors(a["color"], b["color"])
if not _contrast_ok(COLORS[mixed], bg):
return _random_scene(rng, cfg)
res = {"shape": a["shape"] if a["shape"] == b["shape"] else "circle", "color": mixed,
"size": _choice(rng, ["medium", "big"])}
ev = {"kind": k, "result" if k == "merge" else "source": res}
return {"objects": [a, b], "event": ev, "bg": bg, "mention_bg": mention_bg}
a = _random_obj(rng, bg, size=_choice(rng, small))
b = _random_obj(rng, bg, size=_choice(rng, small + (["big"] if k == "orbit" else [])))
if a == b:
return _random_scene(rng, cfg)
ev = {"kind": k}
if k == "independent":
ev["a"], ev["b"] = _random_single_event(rng, a, bg), _random_single_event(rng, b, bg)
return {"objects": [a, b], "event": ev, "bg": bg, "mention_bg": mention_bg}
def caption_scene(rng, scene: dict) -> str:
objs, ev = scene["objects"], scene["event"]
cap = describe_single(rng, objs[0], ev) if len(objs) == 1 else describe_pair(rng, objs[0], objs[1], ev)
bgp = _choice(rng, BG_PHRASES[scene["bg"]]) if scene["mention_bg"] else None
return _style(rng, cap, bgp)
# ---------------------------------------------------------------- rendering
def _poly_mask(px, py, verts):
inside = np.zeros(px.shape, bool)
n = len(verts)
for i in range(n):
x1, y1 = verts[i]
x2, y2 = verts[(i + 1) % n]
crosses = (y1 > py) != (y2 > py)
xint = (x2 - x1) * (py - y1) / (y2 - y1 + 1e-12) + x1
inside ^= crosses & (px < xint)
return inside
def _regular(n, r, ang, cx, cy, inner=None):
k = 2 * n if inner else n
return [(cx + (inner if inner and i % 2 else r) * math.cos(ang - math.pi / 2 + 2 * math.pi * i / k),
cy + (inner if inner and i % 2 else r) * math.sin(ang - math.pi / 2 + 2 * math.pi * i / k)) for i in range(k)]
def shape_mask(shape, px, py, cx, cy, r, ang):
dx, dy = px - cx, py - cy
if shape == "circle":
return dx * dx + dy * dy <= r * r
if shape == "ring":
d2 = dx * dx + dy * dy
return (d2 <= r * r) & (d2 >= (0.55 * r) ** 2)
if shape == "square":
return _poly_mask(px, py, _regular(4, r * 1.15, ang + math.pi / 4, cx, cy))
if shape == "triangle":
return _poly_mask(px, py, _regular(3, r * 1.2, ang, cx, cy))
if shape == "star":
return _poly_mask(px, py, _regular(5, r * 1.25, ang, cx, cy, inner=r * 0.5))
if shape == "hexagon":
return _poly_mask(px, py, _regular(6, r * 1.05, ang, cx, cy))
c, s = math.cos(ang), math.sin(ang)
u, v = (c * dx + s * dy) / r, (-s * dx + c * dy) / r
if shape == "diamond":
return np.abs(u) / 0.75 + np.abs(v) / 1.15 <= 1
if shape == "cross":
arm = 0.33
return ((np.abs(u) <= 1) & (np.abs(v) <= arm)) | ((np.abs(v) <= 1) & (np.abs(u) <= arm))
if shape == "heart": # upright heart: small tilt only, so it stays recognisable
c, s = math.cos(0.3 * math.sin(ang)), math.sin(0.3 * math.sin(ang))
u, v = (c * dx + s * dy) / r, (-s * dx + c * dy) / r
x, y = u * 1.15, -v * 1.15 + 0.15
return (x * x + y * y - 1) ** 3 - x * x * y ** 3 <= 0
raise ValueError(shape)
def _background(bg, S):
top, bot = (np.array(c, np.float32) for c in BACKGROUNDS[bg])
w = np.linspace(0, 1, S, dtype=np.float32)[:, None, None]
return np.broadcast_to(top * (1 - w) + bot * w, (S, S, 3)).copy()
def render_scene(scene: dict, rng, cfg: WorldConfig) -> np.ndarray:
T, S, ss = cfg.frames, cfg.size, cfg.supersample
big = S * ss
co = (np.arange(big, dtype=np.float32) + 0.5) / big
px, py = np.meshgrid(co, co)
objs, ev = scene["objects"], scene["event"]
if len(objs) == 1:
tracks = [_single_states(rng, objs[0], ev, T)]
shapes = [objs[0]["shape"]]
else:
tracks = _pair_states(rng, objs[0], objs[1], ev, T)
shapes = [objs[0]["shape"], objs[1]["shape"]]
if ev["kind"] in ("merge", "split"):
shapes.append((ev.get("result") or ev.get("source"))["shape"])
scene["tracks"] = tracks
scene["track_shapes"] = shapes
first = [i for i, tr in enumerate(tracks) if tr[0][5] > 0.5 and tr[0][2] > 0.005]
last = [i for i, tr in enumerate(tracks) if tr[T - 1][5] > 0.5 and tr[T - 1][2] > 0.005]
scene["summary"] = {"initial_count": len(first), "final_count": len(last),
"initial_colors": [nearest_color(tracks[i][0][4]) for i in first],
"final_colors": [nearest_color(tracks[i][T - 1][4]) for i in last],
"final_shapes": [shapes[i] for i in last]}
base = _background(scene["bg"], big)
frames = np.empty((T, S, S, 3), np.uint8)
for f in range(T):
img = base.copy()
for shape, tr in zip(shapes, tracks):
x, y, r, ang, rgb, alpha = tr[f]
if alpha <= 0.01 or r <= 0.005:
continue
m = shape_mask(shape, px, py, x, y, r, ang)
img[m] = img[m] * (1 - alpha) + np.array(rgb, np.float32) * alpha
img = img.reshape(S, ss, S, ss, 3).mean(axis=(1, 3))
frames[f] = np.clip(img + 0.5, 0, 255).astype(np.uint8)
return frames
def make_clip(rng, cfg: WorldConfig | None = None, split: str = "train"):
cfg = cfg or WorldConfig()
scene = random_scene(rng, cfg, split)
caption = caption_scene(rng, scene)
video = render_scene(scene, rng, cfg)
scene["caption"] = caption
return video, caption, scene
def sample_prompts(n: int, split: str = "train", seed: int = 0, cfg: WorldConfig | None = None) -> list[tuple[str, dict]]:
"""Captions + scenes. Call render_scene(scene, rng, cfg) to get ground-truth tracks/summary for a scene."""
rng = np.random.default_rng(seed)
cfg = cfg or WorldConfig()
out = []
for _ in range(n):
scene = random_scene(rng, cfg, split)
out.append((caption_scene(rng, scene), scene))
return out
def to_tensor(video: np.ndarray) -> torch.Tensor:
return torch.from_numpy(video).permute(3, 0, 1, 2).float().div(127.5).sub(1)
class WorldDataset(torch.utils.data.IterableDataset):
"""Infinite stream of (video float [3,T,H,W] in [-1,1], caption)."""
def __init__(self, cfg: WorldConfig | None = None, seed: int = 0, split: str = "train"):
self.cfg = cfg or WorldConfig()
self.seed = seed
self.split = split
def __iter__(self):
info = torch.utils.data.get_worker_info()
rng = np.random.default_rng([self.seed, info.id if info else 0])
while True:
video, caption, _ = make_clip(rng, self.cfg, self.split)
yield to_tensor(video), caption
def collate(batch):
videos, captions = zip(*batch)
return torch.stack(videos), list(captions)
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