import torch


def torch_acc_score(
        y_pred: torch.Tensor,
        y_true: torch.Tensor
) -> float:
    """
    Evaluate performance between predictions and ground truth labels.

    Parameters
    ----------
    y_pred: torch.Tensor
        Model predictions.
    y_true: numpy.ndarray
        Ground truth labels.
    Returns
    -------
    float: Accuracy score of model's predictions.
    """
    if not isinstance(y_pred, torch.Tensor):
        y_pred = torch.from_numpy(y_pred)
    if not isinstance(y_true, torch.Tensor):
        y_true = torch.from_numpy(y_true)
    return (y_pred.argmax(1) == y_true.argmax(1)).sum().item() / len(y_true)