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import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap, Normalize
from random import choice, randint, sample, shuffle, uniform
from dsl import *
global rng
rng = []
def unifint(
diff_lb: float,
diff_ub: float,
bounds: Tuple[int, int]
) -> int:
"""
diff_lb: lower bound for difficulty, must be in range [0, diff_ub]
diff_ub: upper bound for difficulty, must be in range [diff_lb, 1]
bounds: interval [a, b] determining the integer values that can be sampled
"""
a, b = bounds
d = uniform(diff_lb, diff_ub)
global rng
rng.append(d)
return min(max(a, round(a + (b - a) * d)), b)
def is_grid(
grid: Any
) -> bool:
"""
returns True if and only if argument is a valid grid
"""
if not isinstance(grid, tuple):
return False
if not len(grid) > 0:
return False
if not all(isinstance(r, tuple) for r in grid):
return False
if not all(0 < len(r) <= 30 for r in grid):
return False
if not len(set(len(r) for r in grid)) == 1:
return False
if not all(all(isinstance(x, int) for x in r) for r in grid):
return False
if not all(all(0 <= x <= 9 for x in r) for r in grid):
return False
return True
def strip_prefix(
string: str,
prefix: str
) -> str:
"""
removes prefix
"""
return string[len(prefix):]
def format_grid(
grid: List[List[int]]
) -> Grid:
"""
grid type casting
"""
return tuple(tuple(row) for row in grid)
def format_example(
example: dict
) -> dict:
"""
example data type
"""
return {
'input': format_grid(example['input']),
'output': format_grid(example['output'])
}
def format_task(
task: dict
) -> dict:
"""
task data type
"""
return {
'train': [format_example(example) for example in task['train']],
'test': [format_example(example) for example in task['test']]
}
def plot_task(
task: List[dict],
title: str = None
) -> None:
"""
displays a task
"""
cmap = ListedColormap([
'#000', '#0074D9', '#FF4136', '#2ECC40', '#FFDC00',
'#AAAAAA', '#F012BE', '#FF851B', '#7FDBFF', '#870C25'
])
norm = Normalize(vmin=0, vmax=9)
args = {'cmap': cmap, 'norm': norm}
height = 2
width = len(task)
figure_size = (width * 3, height * 3)
figure, axes = plt.subplots(height, width, figsize=figure_size)
for column, example in enumerate(task):
axes[0, column].imshow(example['input'], **args)
axes[1, column].imshow(example['output'], **args)
axes[0, column].axis('off')
axes[1, column].axis('off')
if title is not None:
figure.suptitle(title, fontsize=20)
plt.subplots_adjust(wspace=0.1, hspace=0.1)
plt.show()
def fix_bugs(
dataset: dict
) -> None:
"""
fixes bugs in the original ARC training dataset
"""
dataset['a8d7556c']['train'][2]['output'] = fill(dataset['a8d7556c']['train'][2]['output'], 2, {(8, 12), (9, 12)})
dataset['6cf79266']['train'][2]['output'] = fill(dataset['6cf79266']['train'][2]['output'], 1, {(6, 17), (7, 17), (8, 15), (8, 16), (8, 17)})
dataset['469497ad']['train'][1]['output'] = fill(dataset['469497ad']['train'][1]['output'], 7, {(5, 12), (5, 13), (5, 14)})
dataset['9edfc990']['train'][1]['output'] = fill(dataset['9edfc990']['train'][1]['output'], 1, {(6, 13)})
dataset['e5062a87']['train'][1]['output'] = fill(dataset['e5062a87']['train'][1]['output'], 2, {(1, 3), (1, 4), (1, 5), (1, 6)})
dataset['e5062a87']['train'][0]['output'] = fill(dataset['e5062a87']['train'][0]['output'], 2, {(5, 2), (6, 3), (3, 6), (4, 7)}) |