// CHECK-LABEL: func private @quantized_conv2d_with_bias_and_relu6_fn_0
// CHECK-SAME: (%arg0: tensor<1x2x2x3xi8>, %arg1: tensor<2x2x3x2xi8>, %arg2: tensor<2xi32>, %arg3: tensor<f32>, %arg4: tensor<i32>, %arg5: tensor<2xf32>, %arg6: tensor<2xi32>, %arg7: tensor<2xf32>, %arg8: tensor<2xi32>, %arg9: tensor<f32>, %arg10: tensor<i32>) -> tensor<*xi8>
// CHECK:      %[[CONV2D_0:.*]] = "tf.Conv2D"

func.func @argmin(%arg0: tensor<3xi32>, %arg1: tensor<i32>) -> tensor<i32> {
  %0 = "tf.ArgMin"(%arg0, %arg1) : (tensor<3xi32>, tensor<i32>) -> tensor<i32>
  func.return %0 : tensor<i32>

// CHECK-LABEL: argmin
// CHECK:  "tfl.arg_min"(%arg0, %arg1) : (tensor<3xi32>, tensor<i32>) -> tensor<i32>
}

func.func @sigmoid(%arg0: tensor<?x88xf32>) -> tensor<?x88xf32> {
  %0 = "tf.Sigmoid"(%arg0) : (tensor<?x88xf32>) -> tensor<?x88xf32>

  %1 = "tf.Concat"(%0, %arg0, %arg1) {device = "/job:localhost/replica:0/task:0/device:GPU:0"} : (tensor<i32>, tensor<2x1xi32>, tensor<2x1xi32>) -> tensor<2x2xi32>
  func.return %1 : tensor<2x2xi32>
}

// CHECK-LABEL: testConcatCwiseUnary
func.func @testConcatCwiseUnary(%arg0: tensor<?x1xf32>, %arg1: tensor<?x1xf32>, %arg2: tensor<i32>) -> tensor<?x2xf32> {

    %cst = "tf.Const"() {value = dense<127> : tensor<i32>} : () -> tensor<i32>
    %cst_0 = "tf.Const"() {value = dense<-128> : tensor<i32>} : () -> tensor<i32>
    %0 = "tf.Cast"(%arg0) {Truncate = false} : (tensor<1x2240x2240x3xi8>) -> tensor<1x2240x2240x3xi32>

func.func @op_with_region_mixed_tfl_shlo_tfl(%arg0: tensor<7x5xf32>, %arg1 : tensor<5xf32>) -> tensor<5xf32> {
  %0 = "stablehlo.reduce"(%arg0, %arg1) ({
  ^bb0(%arg2: tensor<5xf32>, %arg3: tensor<5xf32>):
    // CHECK:      %1 = "tfl.abs"(%arg2) {fused_activation_function = "NONE"} : (tensor<5xf32>) -> tensor<5xf32>
    // CHECK-NEXT: %2 = "vhlo.add_v1"(%1, %arg2) : (tensor<5xf32>, tensor<5xf32>) -> tensor<5xf32>

// CHECK-LABEL: identity
// CHECK: %0 = "tf.Identity"(%arg0) : (tensor<10xi32>) -> tensor<*xi32>
// CHECK: return %arg0, %arg1, %arg2, %0
}

func.func @sharding(%arg0: tensor<10x10xi32>) -> (tensor<10x10xi32>) {
  %0 = "tf.MatMul"(%arg0, %arg0) {device = "", transpose_a = false, transpose_b = false} : (tensor<10x10xi32>, tensor<10x10xi32>) -> tensor<10x10xi32>

// CHECK: func private @tf.IfRegion_else(%arg0: tensor<i1>, %arg1: tensor<2xf32>, %arg2: tensor<2xf32>, %arg3: tensor<2xf32>) -> tensor<2xf32>
// CHECK-NEXT: "tf.Select"(%arg0, %arg2, %arg3)
// CHECK: func private @tf.IfRegion_then(%arg0: tensor<i1>, %arg1: tensor<2xf32>, %arg2: tensor<2xf32>, %arg3: tensor<2xf32>) -> tensor<2xf32>
// CHECK-NEXT: "tf.Select"(%arg0, %arg1, %arg2)
func.func @testIfCondition(%arg0: tensor<i1>, %arg1: tensor<2xf32>) -> tensor<2xf32> {

func.func @func_with_sharding_inside_while_body(%arg0: tensor<i32>, %arg1: tensor<128x1024xf32>) -> (tensor<128x1024xf32>) {
  %cst = "tf.Const"() <{value = dense<0> : tensor<i32>}> {device = ""} : () -> tensor<i32>
  %0:2 = "tf.WhileRegion"(%cst, %arg1) <{is_stateless = false, parallel_iterations = 1 : i64}> ({
    ^bb0(%arg2: tensor<i32>, %arg3: tensor<128x1024xf32>):
      %1 = "tf.Less"(%arg2, %arg0) : (tensor<i32>, tensor<i32>) -> tensor<i1>

func.func @unknown_resource_op_while_body(%arg0: !tf_res, %arg1: !tf_res, %arg2: tensor<f32>, %arg3: tensor<f32>) -> (!tf_res, !tf_res, tensor<f32>, tensor<f32>) {
  %graph:4 = tf_executor.graph {
    %assign_control_0 = tf_executor.island wraps "tf.AssignVariableOp"(%arg0, %arg2) : (tensor<!tf_type.resource<tensor<f32>>>, tensor<f32>) -> ()

		{name: "FNMSUBS", argLength: 3, reg: fp31, asm: "FNMSUBS"}, // -arg0 + (arg1 * arg2)
		{name: "FNMSUBD", argLength: 3, reg: fp31, asm: "FNMSUBD"}, // -arg0 + (arg1 * arg2)
		{name: "MADD", argLength: 3, reg: gp31, asm: "MADD"},       // +arg0 + (arg1 * arg2)
		{name: "MADDW", argLength: 3, reg: gp31, asm: "MADDW"},     // +arg0 + (arg1 * arg2), 32-bit
		{name: "MSUB", argLength: 3, reg: gp31, asm: "MSUB"},       // +arg0 - (arg1 * arg2)