hape `(batch_size,)`, *optional*):
            Labels for computing the optical flow loss. Indices should be in `[0, ..., config.num_labels - 1]`.

        Returns:

        Examples:

        ```python
        >>> from transformers import PerceiverForOpticalFlow
        >>> import torch

        >>> model = PerceiverForOpticalFlow.from_pretrained("deepmind/optical-flow-perceiver")

        >>> # in the Perceiver IO paper, the authors extract a 3 x 3 patch around each pixel,
        >>> # leading to 3 x 3 x 3 = 27 values for each pixel (as each pixel also has 3 color channels)
        >>> # patches have shape (batch_size, num_frames, num_channels, height, width)
        >>> # the authors train on resolutions of 368 x 496
        >>> patches = torch.randn(1, 2, 27, 368, 496)
        >>> outputs = model(inputs=patches)
        >>> logits = outputs.logits
        >>> list(logits.shape)
        [1, 368, 496, 2]
        ```Nr