%5, %6, %7, %8,
    %9, %9, %9,
    %10, %11,
    %10, %10,
    %9, %9,
    %recurrent_input, %cell_input,
    %9, %9, %9, %9) {
      cell_clip = 1.000000e+01 : f32,
      fused_activation_function = "TANH",
      proj_clip = 0.000000e+00 : f32,
      time_major = false} : (
        tensor<1x2x3xf32>,
        tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>,

                               builder.opts().WithName("A"));
    Node* tanh0 = ops::UnaryOp("Tanh", call, builder.opts().WithName("tanh0"));
    Node* tanh1 = ops::UnaryOp("Tanh", tanh0, builder.opts().WithName("tanh1"));
    ops::UnaryOp("Tanh", tanh1, builder.opts().WithName("tanh2"));
    TF_EXPECT_OK(GraphDefBuilderToGraph(builder, graph.get()));
  }

  // CHECK-NEXT: [[r2:%.*]] = tfrt_fallback_async.executeop {{.*}} "tf.Tanh"([[r1]]) {T = f32}
  %4 = "tf.Tanh"(%3) {T = f32, _output_shapes = ["tfshape$dim { size: 3 } dim { size: 3 }"], device = "/device:CPU:0"} : (tensor<3x3xf32>) -> tensor<3x3xf32>
  // CHECK-NOT: tf.Identity

    %9, %9, %9, %9) {
      asymmetric_quantize_inputs = false,
      cell_clip = 1.000000e+01 : f32,
      effective_hidden_scale_intermediate = tensor<0x!quant.calibrated<f32<0.0:1.0>>>,
      fused_activation_function = "TANH",
      input_to_cell_intermediate = tensor<0xf32>,
      input_to_forget_intermediate = tensor<0xf32>,
      input_to_input_intermediate = tensor<0xf32>,
      input_to_output_intermediate = tensor<0xf32>,

"tfl.lstm"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7, %arg8, %cst, %cst, %cst, %arg9, %arg10, %arg11, %arg12, %arg13, %arg14, %arg19, %arg20, %arg15, %arg16, %arg17, %arg18) ({}) {cell_clip = 1.000000e+01 : f32, fused_activation_function = "TANH", input_to_input_intermediate = tensor<0x!quant.uniform<i16:f32, 0.0049890000373125076>>, input_to_forget_intermediate = tensor<0x!quant.uniform<i16:f32, 0.0078849997371435165>>, input_to_cell_intermediate = tensor<0x!quant.uniform<i16:f32, 0.0087630003690719604>>,...

      %cst_2, %cst_2, %cst_2,
      %cst_7, %cst_7, %cst_7, %cst_7,
      %cst_2, %cst_2,
      %recurrent_stats, %cell_stats,
      %cst_2, %cst_2, %cst_2, %cst_2) {cell_clip = 1.000000e+01 : f32, fused_activation_function = "TANH", proj_clip = 0.000000e+00 : f32, time_major = false}
    : ( tensor<1x28x28xf32>,
        tensor<20x28xf32>, tensor<20x28xf32>, tensor<20x28xf32>, tensor<20x28xf32>,

          (variadic $inputs),
          ConstantStrAttr<StrAttr, "aten.gelu.default">, $attrs, $_, $_),
        (TFL_GeluOp $inputs, ConstBoolAttrTrue),

          "intermediates": [
            25, 26, 27, 28, 29
          ],
          "builtin_options_type": "UnidirectionalSequenceLSTMOptions",
          "builtin_options": {
            "fused_activation_function": "TANH",
            "cell_clip": 50.0
          },
          "mutating_variable_inputs": [
            false,
            false, false, false, false,
            false, false, false, false,

// CHECK-SAME:      <{cell_clip = 1.000000e+01 : f32, fused_activation_function = "TANH", kernel_type = #tfl<lstm_kernel_type_attr FULL>, proj_clip = 0.000000e+00 : f32}> ({

    // Populate attributes.
    SmallVector<NamedAttribute, 4> attributes;
    // Activation will always be tanh.
    attributes.push_back(rewriter.getNamedAttr("fused_activation_function",
                                               rewriter.getStringAttr("TANH")));
    // cell_clip.
    attributes.push_back(
        rewriter.getNamedAttr("cell_clip", rewriter.getF32FloatAttr(0.0)));
    // proj_clip.