}

// CHECK-LABEL: testAddInt16
func.func @testAddInt16(tensor<? x i16>, tensor<? x i16>) -> tensor<? x i16> {
^bb0(%arg0: tensor<? x i16>, %arg1: tensor<? x i16>):
  // CHECK: tfl.add %arg0, %arg1 {fused_activation_function = "RELU6"}
  %0 = tfl.add %arg0, %arg1 {fused_activation_function = "RELU6"} : tensor<? x i16>
  func.return %0#0 : tensor<? x i16>
}

// CHECK-LABEL: testSub

    Results are always sorted in the descending order.
  }];

  let arguments = (ins
    TFL_TensorOf<[F32, I8, I16, I32, I64, UI8, QI8, QUI8]>:$input,
    TFL_TensorOf<[I16, I32]>:$k);

  let results = (outs
    TFL_TensorOf<[F32, I8, I16, I32, I64, UI8, QI8, QUI8]>:$values,
    TFL_TensorOf<[I16, I32]>:$indices);

  let builders = [
    OpBuilder<(ins "Value":$input, "Value":$k),

  // is up to ~2x faster.
  const bool is_f16 = input_ty.getElementType().isF16();
  if (is_f16 && CanUseTensorCores(devices)) return "NHWC";

  // For f32/f16 data type decision depends on the filter size in spatial
  // dimensions, for other data types we keep current data format.
  if (!input_ty.getElementType().isF32() && !input_ty.getElementType().isF16())
    return getDataFormat();

    %if16 = "tf.IfRegion"(%arg0) ({"tf.Yield"(%if15) : (!tf_variant) -> ()},
                                  {"tf.Yield"(%if15) : (!tf_variant) -> ()})
        {is_stateless = true} : (tensor<i1>) -> !tf_variant
    %if17 = "tf.IfRegion"(%arg0) ({"tf.Yield"(%if16) : (!tf_variant) -> ()},
                                  {"tf.Yield"(%if16) : (!tf_variant) -> ()})

// writeStatusLine writes an HTTP/1.x Status-Line (RFC 7230 Section 3.1.2)
// to bw. is11 is whether the HTTP request is HTTP/1.1. false means HTTP/1.0.
// code is the response status code.
// scratch is an optional scratch buffer. If it has at least capacity 3, it's used.
func writeStatusLine(bw *bufio.Writer, is11 bool, code int, scratch []byte) {
	if is11 {
		bw.WriteString("HTTP/1.1 ")
	} else {
		bw.WriteString("HTTP/1.0 ")
	}

}

// CHECK-LABEL: @testAddV2WithRef
func.func @testAddV2WithRef(%arg0: tensor<!tf_type.int16ref>, %arg1: tensor<i16>) -> tensor<i16> {
  // CHECK: tf.AddV2
  %0 = "tf.AddV2"(%arg0, %arg1) : (tensor<!tf_type.int16ref>, tensor<i16>) -> tensor<i16>
  func.return %0 : tensor<i16>
}

// CHECK-LABEL: @testRealDivWithRef

MA0GCSqGSIb3DQEBCwUAA4IBAQCLW3JO8L7LKByjzj2RciPjCGH5XF87Wd20gYLq
sNKcFwCIeyZhnQy5aZ164a5G9AIk2HLvH6HevBFPhA9Ivmyv/wYEfnPd1VcFkpgP
hDt8MCFJ8eSjCyKdtZh1MPMLrLVymmJV+Rc9JUUYM9TIeERkpl0rskcO1YGewkYt
qKlWE+0S16+pzsWvKn831uylqwIb8ANBPsCX4aM4muFBHavSWAHgRO+P+yXVw8Q+
VQDnMHUe5PbZd1/+1KKVs1K/CkBCtoHNHp1d/JT+2zUQJphwja9CcgfFdVhSnHL4
oEEOFtqVMIuQfR2isi08qW/JGOHc4sFoLYB8hvdaxKWSE19A
-----END CERTIFICATE-----`

      return rewriter.notifyMatchFailure(
          loc, "output_rank or broadcast_to shape not supported");

    // Allow lowering when the input's elements type is F32, BFloat16, I32 or
    // I16.
    if (!(mlir::isa<BFloat16Type, Float32Type>(element_type) ||
          element_type.isInteger(32) || element_type.isInteger(16)))
      return rewriter.notifyMatchFailure(loc, "element_type_not_supported");

type S11 struct {
	S6
}

type S12 struct {
	S6
}

type S13 struct {
	S8
}

// The X in S15.S11.S1 and S16.S11.S1 annihilate.
type S14 struct {
	S15
	S16
}

type S15 struct {
	S11
}

type S16 struct {
	S11
}

var fieldTests = []FTest{
	{struct{}{}, "", nil, 0},
	{struct{}{}, "Foo", nil, 0},

                    "'isSigned' can only be set for 8/16-bits integer type");
    }
  }

  if (type.isF32()) {
    return tflite::TensorType_FLOAT32;
  } else if (type.isF16()) {
    return tflite::TensorType_FLOAT16;
  } else if (type.isBF16()) {
    return tflite::TensorType_BFLOAT16;
  } else if (type.isF64()) {
    return tflite::TensorType_FLOAT64;