func.return
  }
})";

// MLIR which should not legalize at all
static constexpr char kBadMlirModuleStr[] = R"(
  module attributes {tf.versions = {bad_consumers = [], min_consumer = 0 : i32, producer = 268 : i32}} {
  func.func @main() -> () {
    %0 = tf.Unknown() -> ()
    func.return %0
  }
})";

// MLIR which should be filtered by the MLIR bridge but fully legalize with the
// combined bridge.

bool GetDummyParams(OpBuilder& builder, Value val_bcast, Attribute& zero,
                    DenseIntElementsAttr& shape) {
  Type type = val_bcast.getType();
  Type elem_type = getElementTypeOrSelf(type);
  // Xla's all_reduce legalizer bitcasts to 32 bits, so only
  // element types size <= 4 bytes are supported.
  if (elem_type.isBF16() || elem_type.isF16() || elem_type.isTF32() ||
      elem_type.isF32()) {
    zero = builder.getFloatAttr(elem_type, 0);

// (either defined in TensorArrayV3 or implied in the first write).
std::unique_ptr<OperationPass<ModuleOp>>
CreateTensorArrayOpsDecompositionPass();

// Create a pass that legalize TFG to TF dialect.
std::unique_ptr<Pass> CreateLegalizeTFGToTFEPass();

// Matches sequence of ops to TensorFlow fused kernels. This pass should not be