%1 = stablehlo.uniform_quantize %0 : (tensor<1x3x!quant.uniform<i32:f32:1, {6.000000e+0,7.000000e+0,8.000000e+0}>>) -> tensor<1x3x!quant.uniform<i8:f32, 5.000000e+0>>
      return %1 : tensor<1x3x!quant.uniform<i8:f32, 5.000000e+0>>
    }
  )mlir";

00000220  fa 10 e2 59 ec 47 2d 7c  ac da 4e 97 0e 15 a0 6f  |...Y.G-|..N....o|
00000230  d0 02 42 01 4d fc be 67  13 9c 2d 05 0e bd 3f a3  |..B.M..g..-...?.|
00000240  8c 25 c1 33 13 83 0d 94  06 bb d4 37 7a f6 ec 7a  |.%.3.......7z..z|
00000250  c9 86 2e dd d7 11 69 7f  85 7c 56 de fb 31 78 2b  |......i..|V..1x+|
00000260  e4 c7 78 0d ae cb be 9e  4e 36 24 31 7b 6a 0f 39  |..x.....N6$1{j.9|
00000270  95 12 07 8f 2a 16 03 01  00 b4 0c 00 00 b0 03 00  |....*...........|

00000120  7e c4 b6 a2 5d fe 1e 52  45 88 7a 36 47 a5 08 0d  |~...]..RE.z6G...|
00000130  92 42 5b c2 81 c0 be 97  79 98 40 fb 4f 6d 14 fd  |.B[.....y.@.Om..|
00000140  2b 13 8b c2 a5 2e 67 d8  d4 09 9e d6 22 38 b7 4a  |+.....g....."8.J|
00000150  0b 74 73 2b c2 34 f1 d1  93 e5 96 d9 74 7b f3 58  |.ts+.4......t{.X|
00000160  9f 6c 61 3c c0 b0 41 d4  d9 2b 2b 24 23 77 5b 1c  |.la<..A..++$#w[.|
00000170  3b bd 75 5d ce 20 54 cf  a1 63 87 1d 1e 24 c4 f3  |;.u]. T..c...$..|

// CHECK-SAME:  1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,
// CHECK-SAME:  1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00}>>}

// CHECK-SAME:  1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,
// CHECK-SAME:  1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00}>>}

    // CHECK: %[[ARG1:.*]]: tensor<!quant.uniform<i8:f32, 3.000000e-01:1>>, %[[ARG2:.*]]: tensor<!quant.uniform<i8:f32, 3.000000e-01:1>>
    // CHECK: %[[MAX:.*]] = stablehlo.maximum %[[ARG1]], %[[ARG2]] : tensor<!quant.uniform<i8:f32, 3.000000e-01:1>>
    // CHECK: stablehlo.return %[[MAX]] : tensor<!quant.uniform<i8:f32, 3.000000e-01:1>>

00000220  fa 10 e2 59 ec 47 2d 7c  ac da 4e 97 0e 15 a0 6f  |...Y.G-|..N....o|
00000230  d0 02 42 01 4d fc be 67  13 9c 2d 05 0e bd 3f a3  |..B.M..g..-...?.|
00000240  8c 25 c1 33 13 83 0d 94  06 bb d4 37 7a f6 ec 7a  |.%.3.......7z..z|
00000250  c9 86 2e dd d7 11 69 7f  85 7c 56 de fb 31 78 2b  |......i..|V..1x+|
00000260  e4 c7 78 0d ae cb be 9e  4e 36 24 31 7b 6a 0f 39  |..x.....N6$1{j.9|
00000270  95 12 07 8f 2a 16 03 03  00 b6 0c 00 00 b2 03 00  |....*...........|

// PerChannelWeightOnly: %[[b:.*]] = arith.constant dense<0.000000e+00> : tensor<512xf32>
// PerChannelWeightOnly: %[[w:.*]] = "tfl.pseudo_qconst"() <{qtype = tensor<512x12x!quant.uniform<i8<-127:127>:f32:0, {1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00
// PerChannelWeightOnly: %[[dq_w:.*]] = "tfl.dequantize"(%[[w]]) : (tensor<512x12x!quant.uniform<i8<-127:127>:f32:0, {1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00

  // CHECK-LABEL: @f16
  // CHECK: value = dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00]> : tensor<4xf16>
  %0 = "tfl.pseudo_const"() { value = dense<[1.0, 2.0, 3.0, 4.0]> : tensor<4xf16> } : () -> tensor<4xf16>
  func.return %0 : tensor<4xf16>
}

func.func @f32() -> tensor<4xf32> {
  // CHECK-LABEL: @f32
  // CHECK: value = dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00]> : tensor<4xf32>

  %0 = stablehlo.convolution(%arg0, %arg1) dim_numbers = [b, f, 0, 1]x[o, i, 0, 1]->[b, f, 0, 1], window = {pad = [[1, 1], [1, 1]]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x4x3x3x!quant.uniform<i8:f32, 1.000000e+0:-100>>, tensor<2x4x3x3x!quant.uniform<i8:f32:0, {2.000000e+2,...