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import matplotlib.pyplot as plt | |
from matplotlib import colors | |
import os | |
import json | |
import numpy as np | |
#Notes | |
" directory_path:str keeps the path containing the tasks" | |
"tasks:list of tuples containing the the task filename and the task data " | |
"task_idx:index of the current task in the current iteration" | |
"task_file name:str name of the task file being processed" | |
"task_data: dictionary containing the task data basically the input and the output grids" | |
"input_output_pairs: list of tuples containing the input and the output grids" | |
def load_tasks_from_directory(directory_path): | |
tasks = [] | |
for filename in os.listdir(directory_path): | |
if filename.endswith(".json"): | |
filepath = os.path.join(directory_path, filename) | |
with open(filepath, 'r') as file: | |
task_data = json.load(file) | |
tasks.append((filename, task_data)) | |
return tasks | |
def prepare_input_output_pairs(task_data): | |
input_output_pairs = [] | |
for example in task_data["train"]: | |
input_grid = np.array(example["input"], dtype=int) | |
output_grid = np.array(example["output"], dtype=int) | |
input_output_pairs.append((input_grid, output_grid)) | |
return input_output_pairs | |