import os
import sys
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..', '..')))
import utils3d
import numpy as np
import torch

def run():
    for i in range(100):
        if i == 0:
            spatial = []
            L = 1
            N = 5
            faces = np.array([[0, 1, 2, 3, 4]])
            expected = np.array([[0, 1, 2], [0, 2, 3], [0, 3, 4]])
        else:
            dim = np.random.randint(4)
            spatial = [np.random.randint(1, 10) for _ in range(dim)]
            L = np.random.randint(1, 1000)
            N = np.random.randint(3, 10)
            faces = np.random.randint(0, 10000, size=(*spatial, L, N))

        expected = utils3d.numpy.triangulate(faces)

        device = [torch.device('cpu'), torch.device('cuda')][np.random.randint(2)]
        faces = torch.tensor(faces, device=device)
        
        actual = utils3d.torch.triangulate(faces).cpu().numpy()
        
        assert np.allclose(expected, actual), '\n' + \
            'Input:\n' + \
            f'{faces}\n' + \
            'Actual:\n' + \
            f'{actual}\n' + \
            'Expected:\n' + \
            f'{expected}'