}
  },
  "info": {
    "title": "Kubernetes",
    "version": "unversioned"
  },
  "openapi": "3.0.0",
  "paths": {
    "/apis/rbac.authorization.k8s.io/v1/": {
      "get": {
        "description": "get available resources",
        "operationId": "getRbacAuthorizationV1APIResources",
        "responses": {
          "200": {
            "content": {
              "application/json": {

      }
    }
  },
  "info": {
    "title": "Kubernetes",
    "version": "unversioned"
  },
  "openapi": "3.0.0",
  "paths": {
    "/apis/storage.k8s.io/v1/": {
      "get": {
        "description": "get available resources",
        "operationId": "getStorageV1APIResources",
        "responses": {
          "200": {
            "content": {
              "application/json": {

    }
  },
  "info": {
    "title": "Kubernetes",
    "version": "unversioned"
  },
  "openapi": "3.0.0",
  "paths": {
    "/apis/admissionregistration.k8s.io/v1/": {
      "get": {
        "description": "get available resources",
        "operationId": "getAdmissionregistrationV1APIResources",
        "responses": {
          "200": {
            "content": {
              "application/json": {

    }
  },
  "info": {
    "title": "Kubernetes",
    "version": "unversioned"
  },
  "openapi": "3.0.0",
  "paths": {
    "/apis/networking.k8s.io/v1/": {
      "get": {
        "description": "get available resources",
        "operationId": "getNetworkingV1APIResources",
        "responses": {
          "200": {
            "content": {
              "application/json": {

    if (static_cast<int>(it.index() % shape[1]) == column) {
      values.push_back(it.value().getSExtValue());
    }
  }

  auto element_type = IntegerType::get(input.getContext(), 64);
  return DenseIntElementsAttr::get(
      tensorflow::GetTypeFromTFTensorShape({shape[0]}, element_type), values);
}

// Returns interior padding to use in HLO Pad op based on the TensorFlow padding

is.plugins=this.processor.plugins.map(a=>typeof a=="object"&&a.prepare?{...a,...a.prepare(this.result)}:a)}get[Symbol.toStringTag](){return"LazyResult"}get processor(){return this.result.processor}get opts(){return this.result.opts}get css(){return this.stringify().css}get content(){return this.stringify().content}get map(){return this.stringify().map}get root(){return this.sync().root}get messages(){return this.sync().messages}warnings(){return this.sync().warnings()}toString(){return this.css}then(e,t){return...

	case size <= 1<<10:
		return http2dataChunkPools[0].Get().(*[1 << 10]byte)[:]
	case size <= 2<<10:
		return http2dataChunkPools[1].Get().(*[2 << 10]byte)[:]
	case size <= 4<<10:
		return http2dataChunkPools[2].Get().(*[4 << 10]byte)[:]
	case size <= 8<<10:
		return http2dataChunkPools[3].Get().(*[8 << 10]byte)[:]
	default:
		return http2dataChunkPools[4].Get().(*[16 << 10]byte)[:]
	}
}

      }
    }
  },
  "info": {
    "title": "Kubernetes",
    "version": "unversioned"
  },
  "openapi": "3.0.0",
  "paths": {
    "/apis/batch/v1/": {
      "get": {
        "description": "get available resources",
        "operationId": "getBatchV1APIResources",
        "responses": {
          "200": {
            "content": {
              "application/json": {

			// It doesn't actually make sense to short-circuit here, since if
			// you connect directly to a NodePort from outside the cluster,
			// you only get the local endpoints. But it's simpler for us and
			// slightly more convenient for users to have this case get
			// short-circuited too.
			output: "10.180.0.2:80, 10.180.1.2:80",
			masq:   false,
		},
		{
			name:     "pod to LB with eTP:Local",

* Better **extensibility**.
* etc.

...all this while keeping the **same Python API**. In most of the cases, for simple models, you can simply upgrade the Pydantic version and get all the benefits. 🚀

In some cases, for pure data validation and processing, you can get performance improvements of **20x** or more. This means 2,000% or more. 🤯