000002e0  85 7b 30 92 78 a2 da a5  1d 1c 1c 54 63 4b 66 b2  |.{0.x......TcKf.|
000002f0  f1 a7 c4 43 57 97 7f 28  37 e7 15 62 9b 1c f5 90  |...CW..(7..b....|
00000300  0c 19 36 1a c1 48 48 e5  7d 56 93 3c 13 e3 cd 6a  |..6..HH.}V.<...j|
00000310  aa aa ba d5 24 95 c7 df  9c a9 76 6c 07 bf 09 2d  |....$.....vl...-|
00000320  4b 7b 55 94 37 ec d4 69  ce ab 0f 48 37 74 37 99  |K{U.7..i...H7t7.|
00000330  83 0d 60 8a 73 56 fb e2  9e 0c 39 0e 23 bf 68 b2  |..`.sV....9.#.h.|

// CHECK: %[[q:.*]] = "tfl.quantize"(%cst) <{qtype = tensor<4x12x!quant.uniform<i8<-127:127>:f32:0, {1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00}>>}> {volatile}
// CHECK: %[[dq:.*]] = "tfl.dequantize"(%0) : (tensor<4x12x!quant.uniform<i8<-127:127>:f32:0, {1.000000e+00,1.000000e+00,1.000000e+00,1.000000e+00}>>) -> tensor<4x12xf32>
// CHECK: "tfl.fully_connected"(%arg0, %[[dq]]

  // 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>

    %cst = "tf.Const"() {value = dense<[[[[1.600000e-01, 1.000000e-01], [5.100000e-01, 5.400000e-01], [-5.000000e-01, 4.100000e-01]], [[-3.500000e-01, 5.000000e-02], [-0.00999999977, 1.600000e-01], [-4.800000e-01, -2.400000e-01]]], [[[-3.500000e-01, -2.100000e-01], [-1.400000e-01, -2.000000e-02], [4.800000e-01, 3.500000e-01]], [[-1.900000e-01, 3.200000e-01], [0.00999999977, -7.000000e-02], [2.000000e-01, -4.000000e-02]]]]> : tensor<2x2x3x2xf32>} : () -> tensor<2x2x3x2xf32>

  %1 = mhlo.constant...

// CHECK: func @not_fuse_conv2d_with_bias_and_mul
// CHECK-DAG: %[[CONST:.*]] = "tf.Const"() <{value = dense<2.000000e+00> : tensor<2x3x3x2xf32>}> : () -> tensor<2x3x3x2xf32>
// CHECK-DAG: %[[CONST_0:.*]] = "tf.Const"() <{value = dense<4.000000e-01> : tensor<2xf32>}> : () -> tensor<2xf32>
// CHECK-DAG: %[[CONST_1:.*]] = "tf.Const"() <{value = dense<8.000000e-01> : tensor<2xf32>}> : () -> tensor<2xf32>

  %q_w = "tfl.pseudo_qconst"() {qtype = tensor<1024x1x1x1x!quant.uniform<i8<-127:127>:f32, 1.000000e+00>>, value = dense<127> : tensor<1024x1x1x1xi8>} : () -> tensor<1024x1x1x1x!quant.uniform<i8<-127:127>:f32, 1.000000e+00>>
  %dq_w = "tfl.dequantize"(%q_w) : (tensor<1024x1x1x1x!quant.uniform<i8<-127:127>:f32, 1.000000e+00>>) -> tensor<1024x1x1x1xf32>

  %cst_0 = "tf.Const"() {value = dense<[-1.000000e+00, -3.000000e+00]> : tensor<2xf32>} : () -> tensor<2xf32>
  %cst_1 = "tf.Const"() {value = dense<[1.000000e+00, 3.000000e+00]> : tensor<2xf32>} : () -> tensor<2xf32>

CHECK:   func private @quantize_ops_CPU_QUANTIZED_INT8(%[[VAL_0:.*]]: tensor<384x512x!quant.uniform<i8:f32, 1.000000e-01>>, %[[VAL_1:.*]]: tensor<128x512x!quant.uniform<i8<-127:127>:f32, 1.000000e-01>>, %[[VAL_2:.*]]: tensor<128x!quant.uniform<i8:f32, 2.000000e-01:-128>>, %[[VAL_3:.*]]: tensor<128x!quant.uniform<i8:f32, 2.000000e-01:-4>>) -> tensor<1x384x128x!quant.uniform<i8:f32, 3.000000e-01:-3>> attributes {tac.device = "CPU", tac.inference_type = "QUANTIZED_INT8", tac.interface_name = "quantize_ops"}...

// CHECK-NEXT:  %[[q2:.*]] = "tfl.quantize"(%arg0) <{qtype = tensor<1x2x1x3x!quant.uniform<i8:f32, 1.000000e+00>>}> : (tensor<1x2x1x3x!quant.uniform<i8:f64, 1.000000e+00>>) -> tensor<1x2x1x3x!quant.uniform<i8:f32, 1.000000e+00>>