"@":                          "\u0040",
	"∁":                            "\u2201",
	"∘":                          "\u2218",
	"∁":                      "\u2201",
	"ℂ":                       "\u2102",
	"≅":                            "\u2245",
	"⩭":                         "\u2a6d",
	"∮":                          "\u222e",

		"commat;":                          '\U00000040',
		"comp;":                            '\U00002201',
		"compfn;":                          '\U00002218',
		"complement;":                      '\U00002201',
		"complexes;":                       '\U00002102',
		"cong;":                            '\U00002245',
		"congdot;":                         '\U00002A6D',
		"conint;":                          '\U0000222E',

  func.return %0 : tensor<?x?x?x?x?xf32>
}

// -----

// CHECK-LABEL: testComplexAbs
func.func @testComplexAbs(%arg0: tensor<? x complex<f32>>) -> tensor<?xf32> {
  // CHECK: "tfl.complex_abs"(%arg0)
  %0 = "tfl.complex_abs"(%arg0): (tensor<? x complex<f32>>) -> tensor<?xf32>
  func.return %0 : tensor<?xf32>
}

// -----

func.func @testComplexAbsUnsupportedType(%arg0: tensor<?xf32>) -> tensor<?xf32> {

	{"%#+-6d", [3]byte{1, 11, 111}, "[+1     +11    +111  ]"},

	// floates with %v
	{"%v", 1.2345678, "1.2345678"},
	{"%v", float32(1.2345678), "1.2345678"},

	// complexes with %v
	{"%v", 1 + 2i, "(1+2i)"},
	{"%v", complex64(1 + 2i), "(1+2i)"},

	// structs
	{"%v", A{1, 2, "a", []int{1, 2}}, `{1 2 a [1 2]}`},
	{"%+v", A{1, 2, "a", []int{1, 2}}, `{i:1 j:2 s:a x:[1 2]}`},

    I32Attr:$stride_w
  );

  let results = (outs TFL_TensorOf<[F32]>:$output);

  let hasOptions = 1;

  let customOption = "Conv3DOptions";
}

def TFL_ComplexAbsOp : TFL_Op<"complex_abs", [
  Pure,
  SameOperandsAndResultShape]> {
  let summary = "Computes the complex absolute value of a tensor.";

  let description = [{

    "BATCH_MATMUL",
    "PLACEHOLDER_FOR_GREATER_OP_CODES",
    "CUMSUM",
    "CALL_ONCE",
    "BROADCAST_TO",
    "RFFT2D",
    "CONV_3D",
    "IMAG",
    "REAL",
    "COMPLEX_ABS",
    "HASHTABLE",
    "HASHTABLE_FIND",
    "HASHTABLE_IMPORT",
    "HASHTABLE_SIZE",
    "REDUCE_ALL",
    "CONV_3D_TRANSPOSE",
    "VAR_HANDLE",
    "READ_VARIABLE",

`tf.image.decode_jpeg` by default uses the faster DCT method, sacrificing a
little fidelity for improved speed. One can revert to the old behavior by
specifying the attribute `dct_method='INTEGER_ACCURATE'`. * `tf.complex_abs` has
been removed from the Python interface. `tf.abs` supports complex tensors and
should be used instead. * In the C++ API (in tensorflow/cc), Input, Output, etc.