def test_make_grid(self): arr = np.random.randn(16,3,10,10) check_equal(torchvision.utils.make_grid(torch.Tensor(arr)), jt.make_grid(jt.array(arr))) check_equal(torchvision.utils.make_grid(torch.Tensor(arr), nrow=2), jt.make_grid(jt.array(arr), nrow=2)) check_equal(torchvision.utils.make_grid(torch.Tensor(arr), nrow=3), jt.make_grid(jt.array(arr), nrow=3)) check_equal(torchvision.utils.make_grid(torch.Tensor(arr), nrow=3, padding=4), jt.make_grid(jt.array(arr), nrow=3, padding=4)) check_equal(torchvision.utils.make_grid(torch.Tensor(arr), nrow=3, padding=4, pad_value=-1), jt.make_grid(jt.array(arr), nrow=3, padding=4, pad_value=-1)) check_equal(torchvision.utils.make_grid(torch.Tensor(arr), nrow=3, normalize=True, padding=4, pad_value=-1), jt.make_grid(jt.array(arr), nrow=3, normalize=True, padding=4, pad_value=-1)) print('pass make_grid test ...')
def check(shape): arr = np.random.randn(*shape) check_equal(torchvision.utils.make_grid(torch.Tensor(arr)), jt.make_grid(jt.array(arr)))