output[1, 0:2, :, ...] = input[1, 2:0:-1, :, ...]
output[2, 0:3, :, ...] = input[2, 3:0:-1, :, ...]
output[3, 0:5, :, ...] = input[3, 5:0:-1, :, ...]

# while entries past seq_lens are copied through:
output[0, 7:, :, ...] = input[0, 7:, :, ...]
output[1, 2:, :, ...] = input[1, 2:, :, ...]
output[2, 3:, :, ...] = input[2, 3:, :, ...]
output[3, 2:, :, ...] = input[3, 2:, :, ...]
```

          },
          "dataSourceRef": {
            "allOf": [
              {

                      items:
                        properties:
                          claim:
                            description: The name of the claim to be copied from.
                            minLength: 1
                            type: string
                          header:
                            description: The name of the header to be created.

                      items:
                        properties:
                          claim:
                            description: The name of the claim to be copied from.
                            minLength: 1
                            type: string
                          header:
                            description: The name of the header to be created.

*   TF Core:
    *   `tf.constant` always creates CPU tensors irrespective of the current
        device context.
    *   Eager `TensorHandles` maintain a list of mirrors for any copies to local
        or remote devices. This avoids any redundant copies due to op execution.
    *   For `tf.Tensor` & `tf.Variable`, `.experimental_ref()` is no longer
        experimental and is available as simply `.ref()`.

              }
            ],
            "default": {},
            "description": "ObjectMeta may contain labels and annotations that will be copied into the PVC when creating it. No other fields are allowed and will be rejected during validation."
          },
          "spec": {
            "allOf": [
              {