%shape = arith.constant dense<[6, 4]> : tensor<2xi32>
  %0 = "tfl.reshape"(%arg0, %shape) : (tensor<1x2x3x4x!quant.uniform<i8:f32, 3.0>>, tensor<2xi32>) -> tensor<6x4x!quant.uniform<i8:f32, 3.0>>

    %clip = "tf.ClipByValue"(%round, %i8_min, %i8_max) : (tensor<*xf32>, tensor<f32>, tensor<f32>) -> tensor<*xf32>
    %i8 = "tf.Cast"(%clip) : (tensor<*xf32>) -> tensor<*xi8>
    func.return %i8 : tensor<*xi8>
  }

  func.func private @internal_dequantize_i32(%input : tensor<*xi32>,
                                    %input_scale : tensor<*xf32>,

//
namespace mlir {
namespace TFL {

namespace {

#define GEN_PASS_DEF_REDUCETYPEPRECISIONPASS
#include "tensorflow/compiler/mlir/lite/transforms/passes.h.inc"

// This pattern checks if an i8 arith::ConstantOp tensor has all values within
// the INT4 range, i.e. [-8,7] and converts it into i4 if so. This assumes that
// the input is sign-extended two's complement.

	// int
	i0 = 1
	i1 int = i0
	i2 = +1
	i3 = +i0
	i4 int = +1
	i5 int = +i4
	i6 = -1
	i7 = -i0
	i8 int = -1
	i9 int = -i4
	i10 = !i0 /* ERROR "not defined" */
	i11 = ^1
	i12 = ^i0
	i13 int = ^1
	i14 int = ^i4
	i15 = *i0 /* ERROR "cannot indirect" */
	i16 = &i0
	i17 = *i16

func.func @CheckLegacyQuantizeAdd() -> tensor<1x2x!quant.uniform<i8:f32, 0.0078431372549019607:-128>> {
  %cst = arith.constant dense<[[1.000000e+00, 2.000000e+00]]> : tensor<1x2xf32>
  %0 = "tfl.quantize"(%cst) {qtype = tensor<1x2x!quant.uniform<i8:f32, 0.0078431372549019607:-128>>, volatile} : (tensor<1x2xf32>) -> tensor<1x2x!quant.uniform<i8:f32, 0.0078431372549019607:-128>>
  func.return %0 : tensor<1x2x!quant.uniform<i8:f32, 0.0078431372549019607:-128>>

  %0 = "tf.AddV2"(%input, %input) : (tensor<?x?xf32>, tensor<?x?xf32>) -> tensor<?x?xf32>

  // CHECK: "mhlo.dot"
  // CHECK-SAME: (tensor<?x?xf32>, tensor<2x2x!quant.uniform<i8:f32, 1.000000e+00:3>>) -> tensor<?x?xf32>

  module {
    func.func @main(%arg0: tensor<1x2xf32>, %arg1: tensor<2x3x!quant.uniform<i8:f32, 6.000000e-03:0>> {tf_saved_model.index_path = ["input_tensor"]}) -> (tensor<1x3xf32>) {
      %0 = stablehlo.dot_general %arg0, %arg1, contracting_dims = [1] x [0] : (tensor<1x2xf32>, tensor<2x3x!quant.uniform<i8:f32, 6.000000e-03:0>>) -> tensor<1x3xf32>
      return %0 : tensor<1x3xf32>
    }
  }
)mlir";

00000030  84 7d 30 9e 2f 9d 4d 0e  59 b4 28 fd 17 10 cd 1e  |.}0./.M.Y.(.....|
00000040  1c d3 2c 5e d9 dc db 26  d0 b9 00 4b 0a 13 54 90  |..,^...&...K..T.|
00000050  f2 7b 68 75 6b 00 34 66  9e 43 29 06 16 49 38 16  |.{huk.4f.C)..I8.|
00000060  7e 51 5c e5 15 c0 58 7d  52 0b 16 21 d8 2c e8 c8  |~Q\...X}R..!.,..|
00000070  8e 3a f6 aa fa 21 45 4a  17 02 67 7d 93 1c 95 88  |.:...!EJ..g}....|

00000030  7a 66 76 26 4f 73 12 14  ef a1 f4 8c c2 08 03 42  |zfv&Os.........B|
00000040  4d d5 f9 d7 ab 31 78 51  f3 f4 94 49 5f 9d bf 23  |M....1xQ...I_..#|
00000050  b2 11 7b ac 42 df 71 1a  37 db 64 99 a0 49 38 16  |..{.B.q.7.d..I8.|
00000060  7e 51 5c e5 15 c0 58 7d  2d 89 ac 0d 05 31 27 ae  |~Q\...X}-....1'.|
00000070  85 ff 27 56 24 4c 26 b3  bc 6c f6 20 80 dd bd ba  |..'V$L&..l. ....|

  auto elemType = getElementTypeOrSelf(type);
  // F16, F32, F64, BF16 types are allowed.
  if (elemType.isBF16() || elemType.isF16() || elemType.isF32() ||
      elemType.isF64())
    return true;

  // I1, I4, I8, I16, I32, I64 types are allowed.
  if (elemType.isInteger(1) || elemType.isInteger(4) || elemType.isInteger(8) ||
      elemType.isInteger(16) || elemType.isInteger(32) ||
      elemType.isInteger(64))
    return true;