let description = [{
This op first slices `input` along the dimension `batch_dim`, and for each
slice `i`, reverses the first `seq_lengths[i]` elements along
the dimension `seq_dim`.

The elements of `seq_lengths` must obey `seq_lengths[i] <= input.dims[seq_dim]`,
and `seq_lengths` must be a vector of length `input.dims[batch_dim]`.

The output slice `i` along dimension `batch_dim` is then given by input

                              type: object
                          type: object
                      type: object
                    patch:
                      description: The patch to apply along with the operation.
                      properties:
                        filterClass:
                          description: |-
                            Determines the filter insertion order.

                              type: object
                          type: object
                      type: object
                    patch:
                      description: The patch to apply along with the operation.
                      properties:
                        filterClass:
                          description: |-
                            Determines the filter insertion order.

## Highlights

*   TF 2.0 delivers Keras as the central high level API used to build and train
    models. Keras provides several model-building APIs such as Sequential,
    Functional, and Subclassing along with eager execution, for immediate
    iteration and intuitive debugging, and `tf.data`, for building scalable
    input pipelines. Checkout
    [guide](https://www.tensorflow.org/beta/guide/keras/overview) for additional