def window_unpartition(windows: paddle.Tensor,
                       window_size: int,
                       pad_hw: Tuple[int, int],
                       hw: Tuple[int, int]) -> paddle.Tensor:
    """
    Window unpartition into original sequences and removing padding.
    Args:
        x (tensor): input tokens with [B * num_windows, window_size, window_size, C].
        window_size (int): window size.
        pad_hw (Tuple): padded height and width (Hp, Wp).
        hw (Tuple): original height and width (H, W) before padding.

    Returns:
        x: unpartitioned sequences with [B, H, W, C].
    """
    Hp, Wp = pad_hw
    H, W = hw
    B = windows.shape[0] // (Hp * Wp // window_size // window_size)
    x = windows.reshape([
        B, Hp // window_size, Wp // window_size, window_size, window_size, -1
    ])
    x = x.transpose([0, 1, 3, 2, 4, 5]).reshape([B, Hp, Wp, -1])

    if Hp > H or Wp > W:
        x = x[:, :H, :W, :]
    return x

    Window unpartition into original sequences and removing padding.
    Args:
        x (tensor): input tokens with [B * num_windows, window_size, window_size, C].
        window_size (int): window size.
        pad_hw (Tuple): padded height and width (Hp, Wp).
        hw (Tuple): original height and width (H, W) before padding.

    Returns:
        x: unpartitioned sequences with [B, H, W, C].
    
contrib/SegmentAnything/segment_anything/modeling/image_encoder.py