removing MLIR or XLA specific attributes that are not legal in TensorFlow
graph.
### `-tf-batch-matmul-to-tf-einsum`

_Replace TF BatchMatMul op by TF Einsum op._

### `-tf-broadcast-fold`

_Fold explicit broadcasts into the following operations if they support implicit broadcasting on their operand._

### `-tf-canonicalize-compile-and-replicate-attributes`

_Canonicalize compilation and replication attributes._

  // CHECK-NEXT: %[[CAST_ZERO:.*]] = "tf.Cast"(%[[ZERO_SCALAR]]) : (tensor<i32>) -> tensor<f32>
  // CHECK-NEXT: %[[CONST10:.*]] = "tf.Const"() <{value = dense<10> : tensor<1xi32>}> : () -> tensor<1xi32>
  // CHECK-NEXT: %[[BROADCAST:.*]] = "tf.BroadcastTo"(%[[CAST_ZERO]], %[[CONST10]]) : (tensor<f32>, tensor<1xi32>) -> tensor<10xf32>
  // CHECK-NEXT: %[[ZERO:.*]] = "tf.Const"() <{value = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>

        def action2 = Mock(Action)
        broadcast.add(action1)

        when:
        broadcast.execute('value')

        then:
        1 * action1.execute('value') >> { broadcast.add(action2) }
        0 * _._
    }

    def canDiscardActions() {
        def action = Mock(Action)
        broadcast.add(action)

        when:
        broadcast.clear()
        broadcast.execute('value')

        then:

## More info

To learn more about the options, check Starlette's documentation for:

* <a href="https://www.starlette.io/websockets/" class="external-link" target="_blank">The `WebSocket` class</a>.

        expect:
        broadcast.empty
        broadcast.size() == 0

        when:
        broadcast.add(listener1)

        then:
        !broadcast.empty
        broadcast.size() == 1

        when:
        broadcast.add(listener2)
        broadcast.add(listener3)

        then:
        !broadcast.empty
        broadcast.size() == 3

        when:

        LOGGER.debug("Memory status broadcaster started");
        if (osMemoryStatusSupported) {
            addListener(osMemoryStatusListener);
        } else {
            LOGGER.info("This JVM does not support getting OS memory, so no OS memory status updates will be broadcast");
        }
    }

    @Override
    public void stop() {
        scheduler.stop();

        def messages = []
        endpoint.take(messages)

        then:
        messages == [message]
    }

    def "forwards queued broadcast messages to all endpoints"() {
        given:
        def message1 = unicast()
        def message2 = broadcast()
        def message3 = unicast()
        def endpoint1 = queue.newEndpoint()
        def endpoint2 = queue.newEndpoint()

        and:

    private final AnonymousListenerBroadcast<ScriptFileResolvedListener> broadcast;

    public DefaultScriptFileResolverListeners(ListenerManager listenerManager) {
        this.broadcast = listenerManager.createAnonymousBroadcaster(ScriptFileResolvedListener.class);
    }

    @Override
    public void addListener(ScriptFileResolvedListener scriptFileResolvedListener) {
        broadcast.add(scriptFileResolvedListener);
    }

    @Override

//
// T z = x / y
// return (z * y != x && (x < 0) != (y < 0)) ? z - 1 : z
//
// BroadcastToDimensions is used to compute the broadcast attr to higher
// dimensions. This computes the broadcast of 'l' to broadcast('l', 'r')
// without returning the broadcast of 'r' to broadcast('l', 'r').
def : Pat<(TF_FloorDivOp AnyTensor:$l, AnyTensor:$r),
      (MHLO_SelectOp
       (CHLO_BroadcastAndOp
        (CHLO_BroadcastCompareOp

    private final AnonymousListenerBroadcast<FileChangeListener> broadcaster;

    public DefaultFileChangeListeners(ListenerManager listenerManager) {
        this.broadcaster = listenerManager.createAnonymousBroadcaster(FileChangeListener.class);
    }

    @Override
    public void addListener(FileChangeListener listener) {
        broadcaster.add(listener);
    }

    @Override