def bias_linspace_init_(param: torch.Tensor, start: float = 3.4, end: float = 6.0) -> torch.Tensor:
    """Linearly spaced bias init across dimensions."""
    assert param.dim() == 1, f"param must be 1-dimensional (typically a bias), got {param.dim()}"
    n_dims = param.shape[0]
    init_vals = torch.linspace(start, end, n_dims)
    with torch.no_grad():
        param.copy_(init_vals)
    return param
Linearly spaced bias init across dimensions.
xlstm/components/init.py