}

    // Many strategies for hashing are possible. This might suffice for now.
    int coercedHash = Hashing.murmur3_32_fixed().hashLong(addressAsLong).asInt();

    // Squash into 224/4 Multicast and 240/4 Reserved space (i.e. 224/3).
    coercedHash |= 0xe0000000;

    // Fixup to avoid some "illegal" values. Currently the only potential

    }

    // Many strategies for hashing are possible. This might suffice for now.
    int coercedHash = Hashing.murmur3_32_fixed().hashLong(addressAsLong).asInt();

    // Squash into 224/4 Multicast and 240/4 Reserved space (i.e. 224/3).
    coercedHash |= 0xe0000000;

    // Fixup to avoid some "illegal" values. Currently the only potential

func.func @_UnaryOpsComposition(%arg0: tensor<4xf32>) -> tensor<4xf32> {

  // CHECK: %[[RESULT0:.*]] = "tf.Asin"(%[[ARG0]])
  // CHECK: %[[RESULT1:.*]] = "tf.Abs"(%[[RESULT0]])
  // CHECK: %[[RESULT2:.*]] = "tf.Log"(%[[RESULT1]])
  // CHECK: return %[[RESULT2]]

  %0 = "tf._UnaryOpsComposition"(%arg0) {op_names = ["Asin", "Abs", "Log"]} : (tensor<4xf32>) -> tensor<4xf32>
  func.return %0 : tensor<4xf32>
}

                t1.propertyAssignment(null, "languageVersion",
                    new MethodInvocationExpression(null, "JavaLanguageVersion.of", singletonList(new LiteralValue(languageVersion.asInt()))),
                    true);
            });
        });
    }

    /**
     * Adds a method invocation statement to the configuration of a particular task.
     */

}  // namespace

INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(AbsOp);
INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(AcosOp);
INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(AcoshOp);
INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(AsinOp);
INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(AsinhOp);
INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(AtanOp);
INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(AtanhOp);
INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(BesselI0eOp);

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		{"DeleteFunc", Func, 21},
		{"Equal", Func, 21},
		{"EqualFunc", Func, 21},
	},
	"math": {
		{"Abs", Func, 0},
		{"Acos", Func, 0},
		{"Acosh", Func, 0},
		{"Asin", Func, 0},
		{"Asinh", Func, 0},
		{"Atan", Func, 0},
		{"Atan2", Func, 0},
		{"Atanh", Func, 0},
		{"Cbrt", Func, 0},
		{"Ceil", Func, 0},
		{"Copysign", Func, 0},
		{"Cos", Func, 0},
		{"Cosh", Func, 0},

}

def TF_AsinOp : TF_Op<"Asin", [Pure, TF_SameOperandsAndResultTypeResolveRef]> {
  let summary = "Computes the trignometric inverse sine of x element-wise.";

  let description = [{
The `tf.math.asin` operation returns the inverse of `tf.math.sin`, such that
if `y = tf.math.sin(x)` then, `x = tf.math.asin(y)`.

**Note**: The output of `tf.math.asin` will lie within the invertible range

*   Enable JIT-compiled i64-indexed kernels on GPU for large tensors with more than 2**32 elements.
    *   Unary GPU kernels: Abs, Atanh, Acos, Acosh, Asin, Asinh, Atan, Cos, Cosh, Sin, Sinh, Tan, Tanh.
    *   Binary GPU kernels: AddV2, Sub, Div, DivNoNan, Mul, MulNoNan, FloorDiv, Equal, NotEqual, Greater, GreaterEqual, LessEqual, Less.

* `tf.lite`