I’m calling resize_to_min_size_(tensorA, tensorB, *many_more_tensors, dim = -1)
def resize_to_min_size_(*tensors, dim = -1):
    tensor_dim_slice = lambda tensor, dim, dim_slice: tensor[(dim if dim >= 0 else dim + tensor.dim()) * (slice(None), ) + (dim_slice, )]
    size = min(t.shape[dim] for t in tensors)
    for t in tensors:
        if t.shape[dim] > size:
            reshaped = tensor_dim_slice(t, dim, slice(size))
            t.set_(t.storage(), 0, reshaped.size(), reshaped.stride())

This is to save for errors when adding tensors to the call line. This is a workaround for absence of SAME padding mode while doing some audio processing.
Basically this is some inplace slicing.