DynamicStitch 1
 FloorDiv 1
 MatMul 20
 Maximum 1
 Mul 74
 NoOp 13
 Reshape 86
 RsqrtGrad 1
 Select 36
 SigmoidGrad 24
 Slice 32
 StridedSlice 2
 Sub 1
 Sum 11
 TanhGrad 17
 Tile 2
 ZerosLike 1
cluster 16 size 22
 Add 2
 BiasAdd 1
 ConcatV2 1
 Const 3
 GreaterEqual 1
 MatMul 1
 Mul 3
 Select 3
 Shape 1
 Sigmoid 3
 Split 1
 Tanh 2

  (TF_SqrtGradOp $y, $dy),
  (TF_DivOp
    (TF_MulOp $dy, (TF_ConstOp (GetScalarOfFloatType<"0.5"> $dy))),
    $y
  )>;

//===----------------------------------------------------------------------===//
// TanhGrad op patterns.
//===----------------------------------------------------------------------===//

// grad = dy * (1 - y**2)

def LowerTanhGradOp :
  Pat<(TF_TanhGradOp $y, $dy),
      (TF_MulOp $dy,

  // evaluated.
  Scope grad_scope = scope.WithControlDependencies(grad);
  auto y = ConjugateHelper(grad_scope, op.output(0));
  grad_outputs->push_back(internal::TanhGrad(grad_scope, y, grad));
  return grad_scope.status();
}
REGISTER_GRADIENT_OP("Tanh", TanhGrad);

Status AsinhGrad(const Scope& scope, const Operation& op,
                 const std::vector<Output>& grad_inputs,

func.func @tanhgrad_complex(%y : tensor<*xcomplex<f32>>, %dy: tensor<*xcomplex<f32>>) -> tensor<*xcomplex<f32>> {
  // CHECK-NOT: tf.TanhGrad
  %0 = "tf.TanhGrad"(%y, %dy) : (tensor<*xcomplex<f32>>, tensor<*xcomplex<f32>>) -> tensor<*xcomplex<f32>>

  func.return %0 : tensor<*xcomplex<f32>>
}

// CHECK-LABEL: func @ZerosLike_unranked
func.func @ZerosLike_unranked(%arg0: tensor<*xi32>) -> tensor<*xi32> {

            "TruncateMod", "Equal", "NotEqual", "Greater", "GreaterEqual",
            "Less", "LessEqual", "SigmoidGrad", "SoftplusGrad", "SoftsignGrad",
            "TanhGrad", "Pow", "SquaredDifference", "ApproximateEqual",
            // Others
            "AddN", "Bitcast", "Cast", "ClipByValue", "Const", "Empty",
            "Identity", "IdentityN", "Relu", "Relu6", "ReluGrad", "Relu6Grad",

    static bool isCompatibleReturnTypes(TypeRange inferred, TypeRange actual) {
      return ArraysAreCastCompatible(inferred, actual);
    }
  }];
}

def TF_TanhGradOp : TF_Op<"TanhGrad", [Pure, TF_SameOperandsAndResultTypeResolveRef]> {
  let summary = "Computes the gradient for the tanh of `x` wrt its input.";

  let description = [{