// CHECK:      %[[READ:.*]] = "tf.ReadVariableOp"
  // CHECK-NEXT: tf_device.replicate
  // CHECK-NEXT:   "tf.OpA"(%[[READ]])
  tf_device.replicate {n = 2 : i32} {
    %0 = "tf.ReadVariableOp"(%arg0) : (tensor<*x!tf_type.resource<tensor<f32>>>) -> tensor<f32>
    "tf.OpA"(%0) : (tensor<f32>) -> ()
  }
  func.return
}

// -----

		*a = oa
		return nil
	}

	*a = oa
	return nil
}

// Opa - implements opa policy agent calls.
type Opa struct {
	args   Args
	client *http.Client
}

// Enabled returns if opa is enabled.
func Enabled(kvs config.KVS) bool {
	return kvs.Get(URL) != ""
}

// LookupConfig lookup Opa from config, override with any ENVs.

	Compression compress.Config `json:"compress"`

	// OpenID configuration
	OpenID openid.Config `json:"openid"`

	// External policy enforcements.
	Policy struct {
		// OPA configuration.
		OPA opa.Args `json:"opa"`

		// Add new external policy enforcements here.
	} `json:"policy"`

	LDAPServerConfig xldap.LegacyConfig `json:"ldapserverconfig"`

  func.return
}

// CHECK: [[CLUSTER:%.*]] = "tf_device.cluster"() ({
// CHECK:    [[OPA:%.*]] = "tf.opA"() {is_stateless = true} : () -> tensor<i32>
// CHECK:    "tf.opB"() ({
// CHECK:      "tf.opC"([[OPA]])
// CHECK:    tf_device.return [[OPA]]
// CHECK:    "tf.opD"([[CLUSTER]])

// Preceding user is using resource updated by a nested op.

    %out, %c1 = tf_executor.island wraps "tf.opA"(%ri) {_tpu_replicate="cluster"}: (tensor<i32>) -> tensor<i32>
    // expected-warning @+1 {{TF2XLA TPU bridge input check: cluster op = tf.opA with cluster = cluster has successor as non cluster op tf.opB}}
    %out2, %c2 = tf_executor.island wraps "tf.opB"(%out) : (tensor<i32>) -> tensor<i32>

	if err != nil {
		return false, err
	}

	// Handle large OPA responses when OPA URL is of
	// form http://localhost:8181/v1/data/httpapi/authz
	type opaResultAllow struct {
		Result struct {
			Allow bool `json:"allow"`
		} `json:"result"`
	}

	// Handle simpler OPA responses when OPA URL is of
	// form http://localhost:8181/v1/data/httpapi/authz/allow
	type opaResult struct {

  // CHECK-SAME: n = 2
  // CHECK:   tf_device.return
}

// -----

// CHECK-LABEL: func @replicate_with_multiple_operands
func.func @replicate_with_multiple_operands() {
  %0 = "tf.opA"() : () -> tensor<*xi1>
  %1 = "tf.opB"() : () -> tensor<*xi1>
  %2 = "tf.opC"() : () -> tensor<*xi1>
  %3 = "tf.opD"() : () -> tensor<*xi32>
  %4 = "tf.opE"() : () -> tensor<*xi32>
  %5 = "tf.opF"() : () -> tensor<*xi32>

		cfg.Compression.MimeTypes = strings.Split(compress.DefaultMimeTypes, config.ValueSeparator)
	case "30":
		// V30 -> V31
		cfg.OpenID = openid.Config{}
		cfg.Policy.OPA = opa.Args{
			URL:       &xnet.URL{},
			AuthToken: "",
		}
	case "31":
		// V31 -> V32
		cfg.Notify.NSQ = make(map[string]target.NSQArgs)
		cfg.Notify.NSQ["1"] = target.NSQArgs{}
	}

  // CHECK-NEXT:     "tf.OpA"(%[[REDUCED]]) : (tensor<f32>) -> ()
  tf_device.replicate {n = 4 : i32} {
    "tf_device.cluster"() ({
      "tf.OpA"(%arg0) : (tensor<f32>) -> ()
      tf_device.return

    during TPURewritePass.

    For example, the tf.OpA with the `mini_batch_splits` attribute will be
    moved after _TPUCompileMlir and the first input will use the
    _TPUCompileMlir program output:

    ```mlir
    "tf_device.launch"() ({
     %cst_0 = "tf.Const"() {value = dense<""> : tensor<1x!tf_type.string>} : () -> tensor<1x!tf_type.string>
     "tf.OpA"(%cst_0) { mini_batch_splits = ""} : (tensor<1x!tf_type.string>) -> ()