// CHECK: %[[q1:.*]] = "quantfork.qcast"(%[[maxpool]])
// CHECK-SAME: quant.uniform<i8:f32, 5.000000e-02:-10>
// CHECK: %[[dq1:.*]] = "quantfork.dcast"(%[[q1]])
// CHECK-SAME: quant.uniform<i8:f32, 5.000000e-02:-10>
// CHECK: %[[reshape:.*]] = "tf.Reshape"(%[[dq1]]
// CHECK: %[[q2:.*]] = "quantfork.qcast"(%[[reshape]])
// CHECK-SAME: quant.uniform<i8:f32, 5.000000e-02:-10>
// CHECK: %[[dq2:.*]] = "quantfork.dcast"(%[[q2]])

// CHECK:           %[[VAL_3:.*]] = "tfl.reshape"(%[[VAL_2]], %[[VAL_1]]) : (tensor<?x1x1x2048x!quant.uniform<i8:f32, 6.000000e-01:-128>>, tensor<2xi32>) -> tensor<?x2048x!quant.uniform<i8:f32, 6.000000e-01:-128>>
// CHECK:           return %[[VAL_3]] : tensor<?x2048x!quant.uniform<i8:f32, 6.000000e-01:-128>>
// CHECK:         }

  %q2 = "quantfork.qcast"(%q1) {volatile} : (tensor<3x2x!quant.uniform<i8:f32, 6.000000e-03:-128>>) -> tensor<3x2x!quant.uniform<i8:f32, 0.013075299590241675:-64>>
  %dq1 = "quantfork.dcast"(%q2) : (tensor<3x2x!quant.uniform<i8:f32, 0.013075299590241675:-64>>) -> tensor<3x2xf32>

// CHECK-NEXT: %[[dq2:.*]] = "tfl.dequantize"(%[[q2]]) : (tensor<1x3x!quant.uniform<i8<-127:127>:f32:0, {{.*}}>>) -> tensor<1x3xf32>
// CHECK-NEXT: %[[q3:.*]] = "tfl.quantize"(%arg0) <{qtype = tensor<1x3x!quant.uniform<i16:f32, {{.*}}>>}> {volatile} : (tensor<1x3xf32>) -> tensor<1x3x!quant.uniform<i16:f32, {{.*}}>>

tensor<2048x!quant.uniform<i32:f32, 1.523437447303877E-7>>, %arg13: tensor<640x2048x!quant.uniform<i8<-127:127>:f32, 0.021174000576138496>>, %arg14: tensor<640x!quant.uniform<i32:f32, 1.601389680352559E-4>>, %arg15: tensor<2048x!quant.uniform<i16:f32, 4.3700000969693065E-4>>, %arg16: tensor<2048x!quant.uniform<i16:f32, 1.1000000085914508E-4>>, %arg17: tensor<2048x!quant.uniform<i16:f32, 1.6799999866634607E-4>>, %arg18: tensor<2048x!quant.uniform<i16:f32, 1.55999994603917E-4>>, %arg19: tensor<1x640x!quant.uniform<i8:f32,...

// CHECK-NEXT:  return %[[q]] : tensor<1x2x1x3x!quant.uniform<i8:f32, 1.000000e+00>>
}

// CHECK-LABEL: QuantizeAssignVariableWithDequantAndEqualType
func.func @QuantizeAssignVariableWithDequantAndEqualType(%arg0 : tensor<1x2x1x3x!quant.uniform<i8:f32, 1.0>>) -> tensor<1x2x1x3x!quant.uniform<i8:f32, 1.0>> {

  %4 = "tfl.reshape"(%3, %cst) : (tensor<1x112x112x32x!quant.uniform<u8:f32, 0.023528476789885875>>, tensor<2xi32>) -> tensor<1x401408x!quant.uniform<u8:f32, 0.023528476789885875>>
  %5 = "tfl.softmax"(%4) {beta = 1.000000e+00 : f32} : (tensor<1x401408x!quant.uniform<u8:f32, 0.023528476789885875>>) -> tensor<1x401408x!quant.uniform<u8:f32, 3.906250e-03>>

  %2 = func.call @quantization_test(%arg0, %0, %1) {tac.interface_name = "func1"} : (tensor<384x512x!quant.uniform<i8:f32, 0.1>>, tensor<128x512x!quant.uniform<i8<-127:127>:f32, 0.01>>, tensor<128x!quant.uniform<i32:f32, 0.7>>) -> tensor<384x128x!quant.uniform<i8:f32, 0.09:-4>>
  func.return %2 : tensor<384x128x!quant.uniform<i8:f32, 0.09:-4>>
}

// PARTIAL-LABEL: @quantization_test

  func.return %6 : tensor<1x112x112x32x!quant.uniform<u8:f32, 0.023528476789885875>>
}

// DEBUG-LABEL: QuantizeSplit
func.func @QuantizeSplit(%arg: tensor<4x!quant.uniform<u8:f32, 1.0>>, %cst: tensor<i32>) -> (tensor<2x!quant.uniform<u8:f32, 1.0>>,tensor<2x!quant.uniform<u8:f32, 1.0>>) {
  %0 = "tfl.dequantize"(%arg) : (tensor<4x!quant.uniform<u8:f32, 1.0>>) -> tensor<4xf32>

// CHECK-SAME: {_quantization_method = "static_range_ptq { }"}
// CHECK-SAME: : (tensor<1x4x!quant.uniform<i8:f32, 6.000000e-03:-128>>, tensor<4x3x!quant.uniform<i8<-127:127>:f32:1, {5.000000e-03,5.000000e-03,5.000000e-03}>>) -> tensor<1x3x!quant.uniform<i8:f32, 1.000000e-03:-3>>
// CHECK: %[[DCAST_0:.+]] = "quantfork.dcast"(%[[CALL_0]]) :  (tensor<1x3x!quant.uniform<i8:f32, 1.000000e-03:-3>>) -> tensor<1x3xf32>
// CHECK: return