},
          "namespaces": {

  }];

  let arguments = (ins
    Arg<TF_VariantTensor, [{A Tensor with type=DT_VARIANT containing the deduplication
data. The tensor is an XLA nested tuple containing N elements (where N is
the ratio of the number of embedding to tensor cores per TPU chip). Each
element of the nested tuple is a tuple of rank 1 tensors. Each tensor either
contains indices (DT_UINT32) for embedding lookup on the TensorCore or

                        unique across all servers.
                      type: string
                    port:
                      description: The Port on which the proxy should listen for incoming
                        connections.
                      properties:
                        name:
                          description: Label assigned to the port.

                        unique across all servers.
                      type: string
                    port:
                      description: The Port on which the proxy should listen for incoming
                        connections.
                      properties:
                        name:
                          description: Label assigned to the port.

    *   Added `CompositeTensor` as a baseclass to `ResourceVariable`. This
        allows `tf.Variable`s to be nested in `tf.experimental.ExtensionType`s.
    *   Added a new constructor argument `experimental_enable_variable_lifting`
        to `tf.Variable`, defaulting to True. When it's `False`, the variable
        won't be lifted out of `tf.function`, thus it can be used as a
        `tf.function`-local variable: during each execution of the

Phænomenon thereof. These things being thus ordered, I found that if the
refracting Angle of the Prism be turned upwards, so that the Paper may
seem to be lifted upwards by the Refraction, its blue half will be
lifted higher by the Refraction than its red half. But if the refracting
Angle of the Prism be turned downward, so that the Paper may seem to be