description: The Maglev load balancer implements
                                    consistent hashing to backend hosts.
                                  properties:
                                    tableSize:
                                      description: The table size for Maglev hashing.
                                      minimum: 0
                                      type: integer

                                  description: The Maglev load balancer implements
                                    consistent hashing to backend hosts.
                                  properties:
                                    tableSize:
                                      description: The table size for Maglev hashing.
                                      minimum: 0
                                      type: integer

                                  description: The Maglev load balancer implements
                                    consistent hashing to backend hosts.
                                  properties:
                                    tableSize:
                                      description: The table size for Maglev hashing.
                                      type: integer
                                  type: object

        multi-hot, or tf-idf encoded representations
    *   `CategoryCrossing`: create new categorical features representing
        co-occurrences of previous categorical feature values
    *   `Hashing`: the hashing trick, for large-vocabulary categorical features
    *   `Discretization`: turn continuous numerical features into categorical
        features by binning their values

Class <org.gradle.internal.resolve.caching.CrossBuildCachingRuleExecutor$AnySerializer> is not annotated (directly or via its package) with @org.gradle.api.NonNullApi in (CrossBuildCachingRuleExecutor.java:0)

endian orderings will give different results. A copy from input buffer to output
buffer is made on BE machines when types are of different sizes in order to get
the same casting results as on LE machines.
  }];

  let arguments = (ins
    TF_NumberTensor:$input
  );

  let results = (outs
    TF_NumberTensor:$output
  );

        "properties": {
          "minReadySeconds": {
            "description": "The minimum number of seconds for which a newly created DaemonSet pod should be ready without any of its container crashing, for it to be considered available. Defaults to 0 (pod will be considered available as soon as it is ready).",
            "format": "int32",
            "type": "integer"
          },
          "revisionHistoryLimit": {