"tf_device.launch"() ({
          "tf.opA"() : () -> ()
          tf_device.return
        }) {device = "CORE_0"} : () -> ()
        tf_device.return
      }
      tf_executor.yield
    }
    tf_executor.fetch
  }
  func.return
}

// CHECK: "tf_device.launch"
// CHECK: device = "CORE_0"
// CHECK: "tf.opA"
// CHECK: "tf_device.launch"
// CHECK: device = "CORE_0"

// CHECK-LABEL: does_basic_reordering
func.func @does_basic_reordering() -> () {
   // CHECK: _TPUCompileMlir
   // CHECK-SAME: X
   // CHECK: _TPUCompileMlir
   // CHECK-SAME: Y
   // CHECK: OpA
   // CHECK: OpB
   // CHECK: OpC
   "tf.OpA"() : () -> ()
   %status_x, %program_x = "tf._TPUCompileMlir"() { metadata = "X", mlir_module = "..." } : () -> (tensor<!tf_type.string>, tensor<!tf_type.string>)
   "tf.OpB"() : () -> ()

package opa

import "github.com/minio/minio/internal/config"

// Help template for OPA policy feature.
var (
	defaultHelpPostfix = func(key string) string {
		return config.DefaultHelpPostfix(DefaultKVS, key)
	}

	Help = config.HelpKVS{
		config.HelpKV{
			Key:         URL,

};

// Clustering policy for `test.OpA` and `test.OpB` operations;
class TestOpsClusteringPolicy : public ClusteringPolicy {
  LogicalResult MatchAndUpdateConstraints(
      Operation* op, const ValuesConstraintSet& results,
      ValuesConstraintSet& operands) const final {
    // Check if operation is `test.OpA` or `test.OpB`.
    bool is_op_a = op->getName().getStringRef() == "test.OpA";

	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

    tf_executor.graph {
      // expected-error@+1 {{functions must be of a single Graph with single op Islands: tf_executor.island must perfectly wrap a single op}}
      %island = tf_executor.island {
        "tf.OpA"() : () -> ()
        "tf.OpB"() : () -> ()
        tf_executor.yield
      }
      tf_executor.fetch
    }
    func.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>) -> ()