%0 = "tfl.pseudo_const" () {value = dense<0.0> : tensor<4xf32>} : () -> tensor<4xf32> loc("Const")
  %1 = "tfl.svdf"(%arg0, %arg1, %arg2, %arg3, %0) {fused_activation_function = "RELU", rank = 2 : i32} : (tensor<4xf32>, tensor<4xi8>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32>
  func.return %1 : tensor<4xf32>

    // CHECK-DAG: %[[SIGN:.*]] = "tf.Sign"(%[[PROX]]) : (tensor<4xf32>) -> tensor<4xf32>
    // CHECK-DAG: %[[ABS:.*]] = "tf.Abs"(%[[PROX]]) : (tensor<4xf32>) -> tensor<4xf32>
    // CHECK-DAG: %[[SCALED_L1:.*]] = "tf.Mul"(%[[ADAGRAD_LR]], %[[L1]]) : (tensor<4xf32>, tensor<f32>) -> tensor<4xf32>
    // CHECK-DAG: %[[PROX_NEW:.*]] = "tf.Sub"(%[[ABS]], %[[SCALED_L1]]) : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32>

// CHECK-NEXT:  } ]
// CHECK-NEXT:  signature_defs: [ ]
// CHECK-NEXT:}

func.func @main(%arg0: tensor<4xf32>, %arg1: tensor<4x!quant.uniform<u8:f32, 0.1>>) -> tensor<4xf32> {
  "tfl.NumericVerify"(%arg1, %arg0) {tolerance = 0.1 : f32} : (tensor<4x!quant.uniform<u8:f32, 0.1>>, tensor<4xf32>) -> (tensor<4xf32>)
  func.return %arg0 : tensor<4xf32>

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate -tflite-flatbuffer-to-mlir - -o - | FileCheck --check-prefix=IMPORT %s

func.func @main(tensor<4xf32>) -> tensor<4xf32> {
^bb0(%arg0: tensor<4xf32>):
// CHECK: {
// CHECK-NEXT:   version: 3,
// CHECK-NEXT:     operator_codes: [ {
// CHECK-NEXT:       deprecated_builtin_code: 80,
// CHECK-NEXT:       version: 1,

func.func @func(%arg0: tensor<4xf32>) -> tensor<4xf32> {
  %cst = "tf.Const"() {value = dense<23.0> : tensor<4xf32>} : () -> tensor<4xf32>
  %0 = "tf.XlaSharding"(%arg0) { _XlaSharding = "\01\02\03"} : (tensor<4xf32>) -> tensor<4xf32>
  %1 = "tf.AddV2"(%0, %cst) : (tensor<4xf32>, tensor<4xf32>) -> (tensor<4xf32>)
  %2 = "tf.AddV2"(%cst, %1) : (tensor<4xf32>, tensor<4xf32>) -> (tensor<4xf32>)

# CHECK: mlir_module = "\0Afunc @main(%arg0 : tensor<10xf32>, %arg1 : tensor<10xf32>) -> tensor<10x10xf32> {\0A %add = \22tf.Add\22(%arg0, %arg1) : (tensor<10xf32>, tensor<10xf32>) -> tensor<10xf32>\0A %ret = \22magic.op\22(%add, %add) : (tensor<10xf32>, tensor<10xf32>) -> tensor<10x10xf32>\0A return %ret : tensor<10x10xf32>\0A}\0A"}> {device = ""} : (tensor<10xf32>, tensor<10xf32>) -> tensor<*xf32>

node {
  name: "x"
  op: "Placeholder"
  attr {

  %cst = arith.constant dense<1.0> : tensor<4xf32>
  %cst_3 = arith.constant dense<2.0> : tensor<4x3x3x3xf32>
  %0 = "tfl.conv_2d"(%arg0, %cst_3, %cst) {dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "RELU6", padding = "VALID", stride_h = 2 : i32, stride_w = 2 : i32} : (tensor<?x19x19x3xf32>, tensor<4x3x3x3xf32>, tensor<4xf32>) -> tensor<?x9x9x4xf32>
  func.return %0 : tensor<?x9x9x4xf32>

// CHECK-NEXT:      %12 = "tfl.shape"(%arg1) : (tensor<2x4x?x3xf32>) -> tensor<4xi32>
// CHECK-NEXT:      %13 = "tfl.pseudo_const"() <{value = dense<[-1, 0, 0, -1]> : tensor<4xi32>}> : () -> tensor<4xi32>
// CHECK-NEXT:      %14 = "tfl.pseudo_const"() <{value = dense<[-1, -1, -1, 0]> : tensor<4xi32>}> : () -> tensor<4xi32>

// CHECK-LABEL: func @main
func.func @main(%arg0 : tensor<10xf32>, %arg1 : tensor<10xf32>) -> tensor<10x10xf32> {
// CHECK-SAME: (%[[ARG0:.*]]: tensor<10xf32>, %[[ARG1:.*]]: tensor<10xf32>)
// CHECK-NEXT:    %[[ADD:.*]] = "tf.Add"(%[[ARG0]], %[[ARG1]]) : (tensor<10xf32>, tensor<10xf32>) -> tensor<10xf32>
// CHECK-NEXT:    %[[MAGIC:.*]] = "magic.op"(%[[ADD]], %[[ADD]]) : (tensor<10xf32>, tensor<10xf32>) -> tensor<10x10xf32>
// CHECK-NEXT:    return %[[MAGIC]]

  %result = tf_executor.graph {

// CHECK: tf_executor.Merge{{.*}}(tensor<*xf32>, tensor<4xf32>) -> (tensor<4xf32>, tensor<i32>, !tf_executor.control)
    %value, %idx, %ctlMerge = tf_executor.Merge %arg0, %arg1  : (tensor<*xf32>, tensor<4xf32>) -> (tensor<4xf32>, tensor<i32>, !tf_executor.control)
    tf_executor.fetch %value : tensor<4xf32>
  }