//
    // Furthermore, pi * abs(frac(x)) loses precision when abs(frac(x)) is close
    // to 1.  To remedy this, we can use the fact that sin(pi * x) in the domain
    // [0, 1] is symmetric across the line Y=0.5.
    Value abs_input = rewriter.create<AbsOp>(loc, input);
    Value abs_input_floor = rewriter.create<FloorOp>(loc, abs_input);
    Value abs_frac_input =

	// should be the same as rounding by SetInt64 after setting the
	// precision)
	g := new(Float).SetMode(mode).SetPrec(prec).SetInt64(x)
	if !alike(g, f) {
		t.Errorf("round %s (%d bits, %s) not symmetric: got %s and %s; want %s",
			toBinary(x), prec, mode,
			toBinary(g.int64()),
			toBinary(r1),
			toBinary(r),
		)
		return
	}

	// h and f should be the same

// but using the sign of z for rounding the result.
// x and y must have a non-empty mantissa and valid exponent.
func (z *Float) usub(x, y *Float) {
	// This code is symmetric to uadd.
	// We have not factored the common code out because
	// eventually uadd (and usub) should be optimized
	// by special-casing, and the code will diverge.

	if debugFloat {

^bb0(%arg0: tensor<2x1x3xf32>, %arg1: tensor<3x2xi32>):
  %0 = "tf.MirrorPad"(%arg0, %arg1) { mode = "SYMMETRIC" }: (tensor<2x1x3xf32>, tensor<3x2xi32>) -> tensor<? x f32>
  func.return %0#0 : tensor<? x f32>

  // CHECK-LABEL: mirror_pad
  // CHECK:  "tfl.mirror_pad"(%arg0, %arg1) <{mode = #tfl<mirror_pad_attr SYMMETRIC>}> : (tensor<2x1x3xf32>, tensor<3x2xi32>) -> tensor<?xf32>
  // CHECK:  return
}

      public boolean contains(@CheckForNull Object element) {
        return set1.contains(element) && !set2.contains(element);
      }
    };
  }

  /**
   * Returns an unmodifiable <b>view</b> of the symmetric difference of two sets. The returned set
   * contains all elements that are contained in either {@code set1} or {@code set2} but not in
   * both. The iteration order of the returned set is undefined.
   *

      public boolean contains(@CheckForNull Object element) {
        return set1.contains(element) && !set2.contains(element);
      }
    };
  }

  /**
   * Returns an unmodifiable <b>view</b> of the symmetric difference of two sets. The returned set
   * contains all elements that are contained in either {@code set1} or {@code set2} but not in
   * both. The iteration order of the returned set is undefined.
   *

  }];

  let description = [{
The input is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions
form square matrices.

The input has to be symmetric and positive definite. Only the lower-triangular
part of the input will be used for this operation. The upper-triangular part
will not be read.

The output is a tensor of the same shape as the input

			t.Errorf("Identical(%s, %s) = %t, want %t", X.Type(), Y.Type(), got, test.want)
		}
	}
}

func TestIdentical_issue15173(t *testing.T) {
	// Identical should allow nil arguments and be symmetric.
	for _, test := range []struct {
		x, y Type
		want bool
	}{
		{Typ[Int], Typ[Int], true},
		{Typ[Int], nil, false},
		{nil, Typ[Int], false},
		{nil, nil, true},
	} {

// -----

// Tests static range quantized dot_general with symmetric quantized input.

func.func @dot_general_upstream_srq_sym_input(%arg0: tensor<1x2x3x4x!quant.uniform<i8:f32, 1.000000e+0>>) -> tensor<1x2x3x5x!quant.uniform<i8:f32, 4.000000e+0>> {

			t.Errorf("Identical(%s, %s) = %t, want %t", X.Type(), Y.Type(), got, test.want)
		}
	}
}

func TestIdentical_issue15173(t *testing.T) {
	// Identical should allow nil arguments and be symmetric.
	for _, test := range []struct {
		x, y Type
		want bool
	}{
		{Typ[Int], Typ[Int], true},
		{Typ[Int], nil, false},
		{nil, Typ[Int], false},
		{nil, nil, true},
	} {