func.func private @simple_callee() -> tensor<2xi32>  {
  %cst = "tf.Const"() { value = dense<2> : tensor<2xi32> } : () -> tensor<2xi32>
  func.return %cst : tensor<2xi32>
}

func.func private @simple_callee_with_noinline() -> tensor<2xi32> attributes {tf._noinline = true} {
  %cst = "tf.Const"() { value = dense<2> : tensor<2xi32> } : () -> tensor<2xi32>
  func.return %cst : tensor<2xi32>
}

// Test that simple TF operations can be inlined.

func.func @conv2d_unmatching_loc_pattern(%arg0: tensor<1x3x4x3xf32>) -> (tensor<1x3x2x2xf32>) {
  %cst = "tf.Const"() {device = "", value = dense_resource<__elided__> : tensor<2x3x3x2xbf16>} : () -> tensor<2x3x3x2xbf16>
  %0 = "tf.Cast"(%arg0) {Truncate = false, device = ""} : (tensor<1x3x4x3xf32>) -> tensor<1x3x4x3xbf16>
  %1 = "tf.Conv2D"(%0, %cst) {data_format = "NHWC", dilations = [1, 1, 1, 1], padding = "SAME", strides = [1, 1, 2, 1]}

  "tf.InitializeTableFromTextFileV2"(%0, %cst) {delimiter = " ", device = "", key_index = -2 : i64, value_index = -1 : i64, vocab_size = -1 : i64} : (tensor<!tf_type.resource>, tensor<!tf_type.string>) -> ()
  func.return
}

// -----

// Tests that the tf.InitializeTableFromTextFileV2 op is not converted since
// unsupported key_index, -1.

func.func @init_all_tables() {

func.func @merge_requantization_followed_by_dequantization(%arg0: tensor<1x3x4x3xf32>) -> tensor<1x3x4x2xf32> {
  // CHECK: %[[CST:.*]] = stablehlo.constant dense<4.000000e-01> : tensor<2x3x3x2xf32>
  // CHECK: %[[QUANT_CST:.*]] = stablehlo.uniform_quantize %[[CST]]
  // CHECK: %[[QUANT_ARG_0:.*]] = stablehlo.uniform_quantize %[[ARG_0]]
  // CHECK: %[[CONV:.*]] = stablehlo.convolution(%[[QUANT_ARG_0]], %[[QUANT_CST]])

    %cst = arith.constant dense<"f"> : tensor<!tf_type.string>
    %0 = "tf.HashTableV2"() {container = "", device = "", key_dtype = i64, shared_name = "hash_table_dba2ccaa-f1b1-46d6-b276-98008f69da71", use_node_name_sharing = false, value_dtype = !tf_type.string} : () -> tensor<!tf_type.resource>

func.func @init_all_tables() {
  %cst = arith.constant dense<"tokens.txt"> : tensor<!tf_type.string>
  %0 = "tf.HashTableV2"() {container = "", device = "", key_dtype = !tf_type.string, shared_name = "hash_table_/tmp/vocab.txt_-2_-1", use_node_name_sharing = false, value_dtype = i64} : () -> tensor<!tf_type.resource>

    %cst = "tf.Const"() {value = dense<1024> : tensor<i32>} : () -> tensor<i32>
    %0:2 = "tf_device.launch"() ({
	  %1 = "tf.Cast"(%arg0) {Truncate = false} : (tensor<2048xi64>) -> tensor<2048xi32>
	  %2 = "tf.Cast"(%arg1) {Truncate = false} : (tensor<2048xi64>) -> tensor<2048xi32>

func.func @remove_volatile_qdq() -> tensor<3x2xf32> {
  // CHECK: %[[CST:.*]] = stablehlo.constant
  // CHECK-NOT: "quantfork.qcast"
  // CHECK-NOT: "quantfork.dcast"
  // CHECK: return %[[CST]]
  %cst = stablehlo.constant dense<[[-0.960978984, -0.390246302], [-0.790828585, -0.601039409], [-1.0280807, -1.02731466]]> : tensor<3x2xf32>

  func.return %98 : tensor<8x6x6x18xbf16>

  // CHECK-DAG: %[[CST:.*]] = "tf.Const"() <{value = dense<[8, 1, 1, 18]> : tensor<4xi64>}> : () -> tensor<4xi64>
  // CHECK-DAG: %[[CST1:.*]] =  "tf.Const"() <{value = dense<[8, 6, 6, 18]> : tensor<4xi64>}> : () -> tensor<4xi64>
  // CHECK: %[[RESHAPE:.*]] = "tf.Reshape"(%arg0, %[[CST]]) : (tensor<1x8x1x1x1x1x1x18xbf16>, tensor<4xi64>) -> tensor<8x1x1x18xbf16>

  // CHECK-SAME: tf_saved_model.initializer_type = "restore_op"
  // CHECK: %[[VAR:.*]] = "tf.VarHandleOp"
  // CHECK-SAME: "var1"
  // CHECK: %[[CST:.*]] = arith.constant dense<> : tensor<0xf32>
  // CHECK: "tf.AssignVariableOp"(%[[VAR]], %[[CST]])
}

// -----

// Test with an existing session init function.
module attributes {tf_saved_model.semantics, tf_saved_model.under_construction} {