mlir::StringAttr padding) {
  return llvm::StringSwitch<mlir::TFL::MirrorPaddingType>(padding.getValue())
      .Case("REFLECT", mlir::TFL::MirrorPaddingType::REFLECT)
      .Case("SYMMETRIC", mlir::TFL::MirrorPaddingType::SYMMETRIC);
}

#include "tensorflow/compiler/mlir/lite/transforms/generated_legalize_tf.inc"

#define DECL_CONVERT_OP(tf_op)                                               \

	for _, a := range sumZZ {
		arg := a
		testFunZZ(t, "AddZZ", AddZZ, arg)

		arg = argZZ{a.z, a.y, a.x}
		testFunZZ(t, "AddZZ symmetric", AddZZ, arg)

		arg = argZZ{a.x, a.z, a.y}
		testFunZZ(t, "SubZZ", SubZZ, arg)

		arg = argZZ{a.y, a.z, a.x}
		testFunZZ(t, "SubZZ symmetric", SubZZ, arg)
	}
}

func TestProdZZ(t *testing.T) {
	MulZZ := func(z, x, y *Int) *Int { return z.Mul(x, y) }

		}
		blockSize *= 2
	}
}

// symMerge_func merges the two sorted subsequences data[a:m] and data[m:b] using
// the SymMerge algorithm from Pok-Son Kim and Arne Kutzner, "Stable Minimum
// Storage Merging by Symmetric Comparisons", in Susanne Albers and Tomasz
// Radzik, editors, Algorithms - ESA 2004, volume 3221 of Lecture Notes in
// Computer Science, pages 714-723. Springer, 2004.
//
// Let M = m-a and N = b-n. Wolog M < N.

		}
		blockSize *= 2
	}
}

// symMergeOrdered merges the two sorted subsequences data[a:m] and data[m:b] using
// the SymMerge algorithm from Pok-Son Kim and Arne Kutzner, "Stable Minimum
// Storage Merging by Symmetric Comparisons", in Susanne Albers and Tomasz
// Radzik, editors, Algorithms - ESA 2004, volume 3221 of Lecture Notes in
// Computer Science, pages 714-723. Springer, 2004.
//
// Let M = m-a and N = b-n. Wolog M < N.

			return z
		}

		// x & y == x & y
		z.abs = z.abs.and(x.abs, y.abs)
		z.neg = false
		return z
	}

	// x.neg != y.neg
	if x.neg {
		x, y = y, x // & is symmetric
	}

	// x & (-y) == x & ^(y-1) == x &^ (y-1)
	y1 := nat(nil).sub(y.abs, natOne)
	z.abs = z.abs.andNot(x.abs, y1)
	z.neg = false
	return z
}

// AndNot sets z = x &^ y and returns z.

		}
		blockSize *= 2
	}
}

// symMergeCmpFunc merges the two sorted subsequences data[a:m] and data[m:b] using
// the SymMerge algorithm from Pok-Son Kim and Arne Kutzner, "Stable Minimum
// Storage Merging by Symmetric Comparisons", in Susanne Albers and Tomasz
// Radzik, editors, Algorithms - ESA 2004, volume 3221 of Lecture Notes in
// Computer Science, pages 714-723. Springer, 2004.
//
// Let M = m-a and N = b-n. Wolog M < N.

   *   <li>With finite tolerance, {@code Double.POSITIVE_INFINITY} and {@code
   *       Double.NEGATIVE_INFINITY} are fuzzily equal only to themselves.
   * </ul>
   *
   * <p>This is reflexive and symmetric, but not transitive, so it is not an
   * equivalence relation and not suitable for use in {@link Object#equals}
   * implementations.
   *

   *   <li>With finite tolerance, {@code Double.POSITIVE_INFINITY} and {@code
   *       Double.NEGATIVE_INFINITY} are fuzzily equal only to themselves.
   * </ul>
   *
   * <p>This is reflexive and symmetric, but not transitive, so it is not an
   * equivalence relation and not suitable for use in {@link Object#equals}
   * implementations.
   *

		blockSize *= 2
	}
}

// symMerge{{.FuncSuffix}} merges the two sorted subsequences data[a:m] and data[m:b] using
// the SymMerge algorithm from Pok-Son Kim and Arne Kutzner, "Stable Minimum
// Storage Merging by Symmetric Comparisons", in Susanne Albers and Tomasz
// Radzik, editors, Algorithms - ESA 2004, volume 3221 of Lecture Notes in
// Computer Science, pages 714-723. Springer, 2004.
//
// Let M = m-a and N = b-n. Wolog M < N.

}

table LeakyReluOptions {
  alpha:float;
}

table SquaredDifferenceOptions {
}

enum MirrorPadMode : byte {
  // Doesn't include borders.
  REFLECT = 0,
  // Includes borders.
  SYMMETRIC = 1,
}

table MirrorPadOptions {
  mode:MirrorPadMode;
}

table UniqueOptions {
  idx_out_type:TensorType = INT32;
}

table ReverseV2Options {
}

table AddNOptions {
}