tf_executor.yield
    }
    // CHECK: tf_executor.fetch
    tf_executor.fetch
  }
  func.return
}

func.func @then_function() {
  tf_executor.graph {
    tf_executor.island {
      "tf.OpA"() : () -> ()
      tf_executor.yield
    }
    tf_executor.fetch
  }
  func.return
}

func.func @else_function() {
  tf_executor.graph {
    tf_executor.island {
      "tf.OpB"() : () -> ()

  // Ops can return multiple outputs and a control token for control
  // dependencies.
  // We don’t mention the control token in the return type here, it is implicit.
  %0, %ctl0 = tf_executor.opA %feed#0, %feed#1 : tensor<*xf32>
  %1, %ctl1 = tf_executor.opB : tensor<*xf32>
  %2, %ctl2 = tf_executor.opC %1, %ctl0 : tensor<*xf32>
  %3, %ctl3 = tf_executor.opD %2 : tensor<*xf32>
  tf_executor.fetch %3 : tensor<*xf32>

    enableNamespacesByDefault: false
    # Mutations that occur after the sidecar injector are not handled by default, as the Istio sidecar injector is only run
    # once. For example, an OPA sidecar injected after the Istio sidecar will not have it's liveness/readiness probes rewritten.
    # Setting this to `IfNeeded` will result in the sidecar injector being run again if additional mutations occur.

  %0 = "tf.VarHandleOp"() {container = "c", shared_name = "v"} : () -> tensor<*x!tf_type.resource<tensor<2x8xi32>>>
  %1 = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
  "tf_device.cluster"() ({
    "tf.OpA"(%0, %1) {f = @reachable_function} : (tensor<*x!tf_type.resource<tensor<2x8xi32>>>, tensor<i32>) -> ()
    tf_device.return
  }) : () -> ()
  func.return
}

// CHECK-LABEL: func @reachable_function

        // a role as connection between `tf.TPUReplicatedInput` or
        // `tf.TPUPartitionedInput`. For example, we have the follow pseudocode:
        // %0 = tf_executor.island wraps "tf.OpA" (){_replication_info = 'c'}
        // %1 = tf_executor.island wraps "tf.Identity(%0)
        // %2 = tf_executor.island wraps "tf.TPUReplicatedInput"(%1)

        if (!isa<TF::TPUReplicatedInputOp, TF::TPUPartitionedInputOp,

    enableNamespacesByDefault: false

    # Mutations that occur after the sidecar injector are not handled by default, as the Istio sidecar injector is only run
    # once. For example, an OPA sidecar injected after the Istio sidecar will not have it's liveness/readiness probes rewritten.
    # Setting this to `IfNeeded` will result in the sidecar injector being run again if additional mutations occur.

  }

  // CHECK-LABEL: func @xla_host_compute_shape_inferred
  func.func @xla_host_compute_shape_inferred() -> (tensor<1x1120x8xi32>, tensor<1x1120x8xi32>, tensor<1120x8xi32>, tensor<2xi32>) {
    %2335 = "tf.OpA"() : () -> tensor<3360x8xi32>
    %cst_2 = "tf.Const"() <{value = dense<[3, 1120, -1]> : tensor<3xi32>}> : () -> tensor<3xi32>
    %cst_68 = "tf.Const"() <{value = dense<0> : tensor<i32>}> : () -> tensor<i32>

"istio-injection:disabled" annotation # Only one environment should have this enabled. enableNamespacesByDe: false # Mutations that occur after the sidecar injector are not handled by default, as the Istio sidecar injector is only run # once. For example, an OPA sidecar injected after the Istio sidecar will not have it's liveness/readiness probes rewritten. # Setting this to `IfNeeded` will result in the sidecar injector being run again if additional mutations occur. reinvocationPolicy: Never rewriteAppHTTPProbe:...

This operation holds a replicated input to a `tpu.replicate()` computation subgraph.
Each replicated input has the same shape and type alongside the output.

For example:
```
%a = "tf.opA"()
%b = "tf.opB"()
%replicated_input = "tf.TPUReplicatedInput"(%a, %b)
%computation = "tf.Computation"(%replicated_input)
```
The above computation has a replicated input of two replicas.
  }];