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ea8c728 | 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 | import sys
import pathlib
BASE_DIR = pathlib.Path(__file__).parents[1]
sys.path.append(str(BASE_DIR))
# torch & related imports
import numpy as np
# local imports
from utils.utils import *
def generate_random_dataset(file_path: str, n: int, instances_number: int = 128) -> None:
np.save(file_path, np.random.uniform(0, 1, size=(instances_number, n, 2)))
def _load_points(file_path: str) -> np.ndarray:
return np.load(file_path)
def load_points(output_dir: str, n: int, instances_count: int = 128) -> np.ndarray:
file_path = pathlib.Path(output_dir) / f"points/{n}.npy"
if not is_file_exist(str(file_path)):
create_dir(str(file_path.parent))
# generating a new dataset
generate_random_dataset(str(file_path), n, instances_number=instances_count)
return _load_points(str(file_path))[:instances_count]
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