%cst_0 = arith.constant dense<[2, -1]> : tensor<2xi64>
  %0 = "tf.FakeQuantWithMinMaxVars"(%arg0, %arg1, %arg2) {num_bits = 3, narrow_range = false} : (tensor<1x2xf32>, tensor<f32>, tensor<f32>) -> tensor<1x2xf32>
  %1 = "tf.Reshape"(%0, %cst_0) : (tensor<1x2xf32>, tensor<2xi64>) -> tensor<2x1xf32>
  func.return %1 : tensor<2x1xf32>

// CHECK:  %cst = arith.constant
// CHECK:  %0 = "tf.Reshape"(%arg0, %cst)

  %cst = "tf.Const"() {value = dense<[[[[-8.69931221, 6.44628429], [-9.18393421, 1.53671741], [8.68561744, -3.581774]]]]> : tensor<1x1x3x2xf32>} : () -> tensor<1x1x3x2xf32>
  %cst_0 = "tf.Const"() {value = dense<-1.000000e+00> : tensor<f32>} : () -> tensor<f32>
  %cst_1 = "tf.Const"() {value = dense<1.000000e+00> : tensor<f32>} : () -> tensor<f32>

    %cst = "tf.Const"() {device = "", value = dense<[7.11401462, 7.05456924]> : tensor<2xf32>} : () -> tensor<2xf32>
    // CHECK: %[[q_weight_per_channel:.*]] = "quantfork.qcast"
    // CHECK-SAME: -> tensor<2x3x3x2x!quant.uniform<i8<-127:127>:f32:3, {0.075123051020104109,0.072960192762960605}>>
    // CHECK: %[[dq_weight:.*]] = "quantfork.dcast"(%[[q_weight_per_channel]])

  %cst = "tf.Const"() {device = "/job:localhost/replica:0/task:0/device:CPU:0", value = dense<3> : tensor<i32>} : () -> tensor<i32>
  %0 = "tf.Less"(%arg0, %cst) {device = "/job:localhost/replica:0/task:0/device:CPU:0"} : (tensor<i32>, tensor<i32>) -> tensor<i1>
  %1 = "tf.Less"(%arg1, %cst) {device = "/job:localhost/replica:0/task:0/device:CPU:0"} : (tensor<i32>, tensor<i32>) -> tensor<i1>

    %cst_0 = "tf.Const"() {value = dense<[-2.000000e+00, 3.000000e+00]> : tensor<2xf32>} : () -> tensor<2xf32>

func.func @NotQuantizeNoneType() -> none {
  %cst = "tfl.no_value"() {value = unit} : () -> none
  func.return %cst : none

// CHECK-NEXT:  %[[cst:.*]] = "tfl.no_value"() <{value}> : () -> none
// CHECK-NEXT:  return %[[cst]]
}

// CHECK-LABEL: QuantizeZeroSplat
func.func @QuantizeZeroSplat() -> tensor<2x3xf32> {
  %cst = arith.constant dense<0.0> : tensor<2x3xf32>
  func.return %cst : tensor<2x3xf32>

// CHECK-LABEL: avg_pool2d_3
// CHECK: %cst = arith.constant dense<[0, 2, 3, 1]> : tensor<4xi32>
// CHECK: %0 = "tfl.transpose"(%arg0, %cst) : (tensor<1x1x1x8xf32>, tensor<4xi32>) -> tensor<1x1x8x1xf32>
// CHECK{LITERAL}: %cst_0 = arith.constant dense<[[0, 0], [0, 0], [1, 1], [0, 0]]> : tensor<4x2xi32>
// CHECK: %1 = "tfl.pad"(%0, %cst_0) : (tensor<1x1x8x1xf32>, tensor<4x2xi32>) -> tensor<1x1x10x1xf32>

    %cst = "tf.Const"() <{value = dense<[0, 1]> : tensor<2xi32>}> {device = ""} : () -> tensor<2xi32>
    %cst_0 = "tf.Const"() <{value = dense<1.000000e+01> : tensor<f32>}> {device = ""} : () -> tensor<f32>
    %0 = "tf.Sum"(%arg0, %cst) <{keep_dims = false}> {device = ""} : (tensor<1x4xf32>, tensor<2xi32>) -> tensor<f32>
    %1 = "tf.Greater"(%0, %cst_0) {device = ""} : (tensor<f32>, tensor<f32>) -> tensor<i1>

// CHECK-NOT: tf.ReadVariableOp
  %0 = "tf.ReadVariableOp"(%arg0) : (tensor<*x!tf_type.resource<tensor<1xf32>>>) -> tensor<1xf32>
  %cst = "tf.Const"() <{value = dense<0.000000e+00> : tensor<f32>}> : () -> tensor<f32>
  %cst_0 = "tf.Const"() <{value = dense<1> : tensor<1xi64>}> : () -> tensor<1xi64>
  %fill = "tf.Fill"(%cst_0, %cst) : (tensor<1xi64>, tensor<f32>) -> tensor<1xf32>
  tf_device.replicate([%0, %fill] as %arg_r0: tensor<1xf32>) {n = 2 : i32} {

    %cst = "tf.Const"() {value = dense<3.00000000e-1> : tensor<2x3xf32>} : () -> tensor<2x3xf32>
    %cst_0 = "tf.Const"() {value = dense<4.00000000e-1> : tensor<1x3xf32>} : () -> tensor<1x3xf32>
    %0 = "quantfork.stats"(%arg0) {layerStats = dense<[6.00000000e-6, 9.00000000e-1]> : tensor<2xf32>} : (tensor<1x2xf32>) -> tensor<1x2xf32>