%arg16: tensor<4x4xf32>, %arg17: tensor<4xf32>,
  %arg18: tensor<4x4xf32>, %arg19: tensor<4x4xf32>, %arg20: tensor<4x4xf32>, %arg21: tensor<4x4xf32>):
  %0 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<4x4xf32>} : () -> tensor<4x4xf32> loc("Const")
  %1 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<4x4xf32>} : () -> tensor<4x4xf32> loc("Const")
  %2 = "tfl.unidirectional_sequence_lstm"(%arg0,
    %arg1, %arg2, %arg3, %arg4,

  // CHECK-NEXT:   metadata: [ {
  // CHECK-NEXT:   name: "min_runtime_version",
  // CHECK-NEXT:   buffer: 8
  // CHECK-NEXT:   } ]
  // CHECK-NEXT:   signature_defs: [ ]
  // CHECK-NEXT: }

  %0 = "tfl.pseudo_const" () {value = dense<1.0> : tensor<4xf32>} : () -> tensor<4xf32> loc("Const")
  %1 = "tfl.squared_difference"(%arg0, %0) {fused_activation_function = "NONE"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("squared_difference")

  %0 = "quantfork.stats"(%arg0) {
    layerStats = dense<[0.0, 1.0]> : tensor<2xf32>
  } : (tensor<?x5x5x2xf32>) -> tensor<?x5x5x2xf32>
  %1 = "tfl.pseudo_const"() {value = dense<1.000000e+00> : tensor<3x5x5x2xf32>} : () -> tensor<3x5x5x2xf32>
  %2 = "tfl.pseudo_const"() {value = dense<0.000000e+00> : tensor<3xf32>} : () -> tensor<3xf32>
  %3 = "tfl.conv_2d"(%0, %1, %2) {
    dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32,

  %0 = "quantfork.stats"(%arg0) {layerStats = dense<[-1.0, 1.0]> : tensor<2xf32>} : (tensor<1x2x3xf32>) -> tensor<1x2x3xf32>

  %1 = "tfl.pseudo_const"() {value = dense<0> : tensor<3xi32>} : () -> tensor<3xi32>
  %2 = "tfl.pseudo_const"() {value = dense<[0, 2, 0]> : tensor<3xi32>} : () -> tensor<3xi32>
  %3 = "tfl.pseudo_const"() {value = dense<1> : tensor<3xi32>} : () -> tensor<3xi32>

  // CHECK-SAME:      <[-1.000000e+00, 1.000000e+00]> : tensor<2xf32>}>
  // CHECK-SAME:      : (tensor<40x37xf32>) -> tensor<40x37xf32>
  // CHECK-NEXT:    %[[cst:.*]] = "tfl.pseudo_const"() <{value = dense<
  // CHECK-SAME:      1.000000e+00> : tensor<40xf32>}> : () -> tensor<40xf32>
  // CHECK-NEXT:    %[[fc:.*]]:2 = "tfl.fully_connected"(%[[stat]], %arg1,

  %cst0 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<4xf32>} : () -> tensor<4xf32> loc("Const")
  %cst1 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<4xf32>} : () -> tensor<4xf32> loc("Const")
  // expected-error @+1 {{'tfl.lstm' op failed to verify that operand 2 is 2-D}}

// Checks that the `tfl.pseudo_qconst` corresponding to the `stablehlo.constant`
// has the same shape.
// CHECK: %[[QCONST_0:.+]] = "tfl.pseudo_qconst"() <{qtype = tensor<2x3x!quant.uniform<i8:f32:0, {3.000000e+00,3.000000e+00}>>, value = dense<1> : tensor<2x3xi8>}> : () -> tensor<2x3x!quant.uniform<i8:f32:0, {3.000000e+00,3.000000e+00}>>

                               %arg1: tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32:3, {1.0,2.0,3.0}>>) -> tensor<1x112x112x32xf32> {
  %bias = "tfl.pseudo_const"() {value = dense<1.000000e+00> : tensor<32xf32>} : () -> tensor<32xf32>
  %input = "tfl.dequantize"(%arg0) : (tensor<1x224x224x3x!quant.uniform<u8:f32, 1.5>>) -> tensor<1x224x224x3xf32>

// NoSideEffect: %[[q_w:.*]] = "tfl.pseudo_qconst"() <{qtype = tensor<1024x1x1x1x!quant.uniform<i8<-127:127>:f32, 1.000000e+00>>
// NoSideEffect: %[[custom:.*]] = "tfl.custom"(%arg0, %[[q_w:.*]]) <{custom_code = "CustomTestOp", custom_option = #tfl<const_bytes : "0x">}
// NoSideEffect: return %[[custom:.*]]

    %cst_7 = "tfl.pseudo_qconst"() {qtype = tensor<20x!quant.uniform<i8:f32, 0.006:-34>>, value = dense<1> : tensor<20xi8>} : () -> tensor<20x!quant.uniform<i8:f32, 0.006:-34>>
    %cst_11 = "tfl.pseudo_qconst"() {qtype = tensor<20x28x!quant.uniform<i8:f32, 0.006:-34>>, value = dense<1> : tensor<20x28xi8>} : () -> tensor<20x28x!quant.uniform<i8:f32, 0.006:-34>>