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Large Language Models
LLM Evaluation
Sequential Reasoning
Scaling Laws
Synthetic Benchmarks
Commonsense Reasoning
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File size: 6,207 Bytes
fb0015f | 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 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 | from dataclasses import dataclass
from typing import Any, List, Tuple
import random
@dataclass
class CompositeTool:
name: str # name of the composite tool
tools: List[Tool] # tools that make up the composite tool
compatible_keys: List[str] # keys that the composite tool can fix
who_can_build: List[
Tuple[str, int]
] # expertise and count of people in each expertise needed to build the composite tool
def __str__(self):
return f"CompositeTool {self.name}"
def get_description(self):
return f"CompositeTool {self.name} can fix keys: {self.compatible_keys} but consists of tools: {self.tools}"
@dataclass
class Tool:
name: str # name of the tool
compatible_keys: List[str] # keys that the tool can fix
who_can_use: List[str] # expertise needed to use the tool
def __str__(self):
return f"Tool {self.name}"
def get_description(self):
return f"Tool {self.name} can fix keys: {self.compatible_keys}"
@dataclass
class Key:
name: str # name of the key
color: str # color of the key
broken: bool # whether the key is broken
fixable: bool # whether the key is fixable
tools: List[str] # tools or composite tools that are needed to fix the key
who_can_fix: List[
Tuple[str, int]
] # expertise and count of people in each expertise needed to fix the key
def __str__(self):
return f"Key {self.name}"
def description(self):
return f"""Key {self.name} is {self.color}
{'but it is broken and cannot be used' if self.broken else ' and it works'}"""
@dataclass
class Object:
name: str # name of the object
description: str # description of the object
def __str__(self):
return f"item {self.name} ({self.description})"
def get_description(self):
return f"item {self.name} is described as {self.description}"
@dataclass
class Box:
name: str # name of the box
contents: List[
str
] # contents of the box - list of box names or key names or tool names
locked: bool # whether the box is locked
def __str__(self):
return f"Box {self.name}"
def get_description(self):
return f"Box {self.name} contains: {self.contents}"
@dataclass
class Person:
name: str # name of the person
room: None | Any # room that the person is in
boxes: List[Box] # boxes that the person has
keys: List[Key] # keys that the person has
cooperates_with: List[str] # names of people
can_build: List[str] # names of composite tools that the person can build
can_fix: List[str] # names of keys that the person can fix
can_use: List[str] # names of keys that the person can use
def __str__(self):
return f"Person {self.name}"
def get_description(self):
return f"Person {self.name} is in room {self.room.name}"
@dataclass
class Door:
name: str # name of the door
locked: bool # whether the door is locked
key: None | Key # key that can unlock the door
two_way: bool # whether the door is two way
key_hole_outward_facing: bool # whether the key hole is outward facing
def __str__(self):
return f"Door {self.name}"
def get_description(self):
return f"Door {self.name} is {'locked' if self.locked else 'unlocked'}"
@dataclass
class Room:
name: str # name of the room
west: None | Door # door to the west
east: None | Door # door to the east
north: None | Door # door to the north
south: None | Door # door to the south
occupants: list[str] # names of people in the room
west_neighbor: None | Any # room to the west
east_neighbor: None | Any # room to the east
north_neighbor: None | Any # room to the north
south_neighbor: None | Any # room to the south
def __str__(self):
return f"""Room {self.name}"""
def get_description(self):
return f"""Room {self.name} is adjacent to {self.west_neighbor.name
if self.west_neighbor else 'none'} on the west side,
{self.east_neighbor.name if self.east_neighbor else 'none'} on the east side,
{self.north_neighbor.name if self.north_neighbor else 'none'} on the north side,
{self.south_neighbor.name if self.south_neighbor else 'none'} on the south side
{self.occupants} are in the room and there are doors on these sides
{self.west.name if self.west else 'none'} on the west side,
{self.east.name if self.east else 'none'} on the east side,
{self.north.name if self.north else 'none'} on the north side,
{self.south.name if self.south else 'none'} on the south side"""
@dataclass
class World:
rooms: List[Room] # rooms in the world
people: List[Person] # people in the world
boxes: List[Box] # boxes in the world
keys: List[Key] # keys in the world
tools: List[Tool] # tools in the world
def __str__(self):
return f"World"
def get_description(self):
return f"This is the world: {self.rooms} {self.people} {self.boxes} {self.keys} {self.tools}"
def generate_configuration(N_x: int, N_y: int, n_people: int):
# generate a random configuration of people in rooms
# sample larger than population with replacement
walls = [True] + random.choices([True, False], k=3)
random.shuffle(walls)
rooms = [
Room(
name=f"Room {i}",
west=walls[0],
east=walls[1],
north=walls[2],
south=walls[3],
occupants=[],
lattice_position=(i, j),
)
for i in range(N_y)
for j in range(N_x)
]
# generate a random configuration of people in rooms
people = [Person(name=f"Person {i}") for i in range(n_people)]
for person in people:
room = random.choice(rooms)
room.occupants.append(person)
return rooms
def print_walls():
for i in range(10):
print(generate_configuration(10, 10))
if __name__ == "__main__":
print_walls()
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