Copyright (c) 2013-2020, Frank Schroeder

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searchSourceJSON":"{\"query\":{\"query\":\"\",\"language\":\"kuery\"},\"filter\":[],\"indexRefName\":\"kibanaSavedObjectMeta.searchSourceJSON.index\"}"},"title":"search-term-rank","uiStateJSON":"{\"vis\":{\"params\":{\"sort\":{\"columnIndex\":null,\"direction\":null}}}}","version":1,"visState":"{\"title\":\"search-term-rank\",\"type\":\"table\",\"params\":{\"perPage\":10,\"showPartialRows\":false,\"showMetricsAtAllLevels\":false,\"sort\":{\"columnIndex\":null,\"direction\":null},\"showTotal\":fa...

        as `tf.tpu.experimental.embedding.serving_embedding_lookup` which can
        take arbitrary rank of dense and sparse tensor. For ragged tensor,
        though the input tensor remains to be rank 2, the activations now can be
        rank 2 or above by specifying the output shape in the feature config or
        via the build method.

*   Add