func (m *MockRuntimeCache) ForceUpdateIfOlder(arg0 context.Context, arg1 time.Time) error {
	m.ctrl.T.Helper()
	ret := m.ctrl.Call(m, "ForceUpdateIfOlder", arg0, arg1)
	ret0, _ := ret[0].(error)
	return ret0
}

// ForceUpdateIfOlder indicates an expected call of ForceUpdateIfOlder.
func (mr *MockRuntimeCacheMockRecorder) ForceUpdateIfOlder(arg0, arg1 any) *gomock.Call {
	mr.mock.ctrl.T.Helper()

		{name: "DIV", argLength: 2, reg: gp21, asm: "DIV", typ: "Int64"}, // arg0 / arg1
		{name: "DIVU", argLength: 2, reg: gp21, asm: "DIVU", typ: "UInt64"},
		{name: "DIVW", argLength: 2, reg: gp21, asm: "DIVW", typ: "Int32"},
		{name: "DIVUW", argLength: 2, reg: gp21, asm: "DIVUW", typ: "UInt32"},

// CHECK:         }
func.func @broadcast_add(%arg0: tensor<1x1xf32>, %arg1: tensor<1x1000xf32>) -> (tensor<1x1000xf32>, tensor<1x1000xf32>) {
  %0 = "mhlo.broadcast_in_dim"(%arg0) <{broadcast_dimensions = dense<[0, 1]> : tensor<2xi64>}> : (tensor<1x1xf32>) -> tensor<1x1000xf32>
  %1 = mhlo.add %0, %arg1 : tensor<1x1000xf32>
  %2 = mhlo.add %arg1, %0 : tensor<1x1000xf32>
  func.return %1, %2 : tensor<1x1000xf32>, tensor<1x1000xf32>
}

		{name: "FMUL", argLength: 2, reg: fp21, asm: "FMUL", commutative: true},   // arg0*arg1
		{name: "FMULS", argLength: 2, reg: fp21, asm: "FMULS", commutative: true}, // arg0*arg1

		{name: "FMADD", argLength: 3, reg: fp31, asm: "FMADD"},   // arg0*arg1 + arg2
		{name: "FMADDS", argLength: 3, reg: fp31, asm: "FMADDS"}, // arg0*arg1 + arg2
		{name: "FMSUB", argLength: 3, reg: fp31, asm: "FMSUB"},   // arg0*arg1 - arg2

// CHECK-LABEL: bias_add
func.func @bias_add(%arg0: tensor<1x10x10x32xf32>, %arg1: tensor<32xf32>) -> tensor<1x10x10x32xf32> {
  %0 = "tf.BiasAdd"(%arg0, %arg1) {T = "tfdtype$DT_FLOAT", data_format = "NHWC"} : (tensor<1x10x10x32xf32>, tensor<32xf32>) -> tensor<1x10x10x32xf32>
  func.return %0 : tensor<1x10x10x32xf32>

  // CHECK-NOT:   func.call
  func.func @while_test_remove_unused_results(%arg0: tensor<i32>, %arg1: tensor<i32>) -> (tensor<i32>, tensor<i32>) {
    %0:2 = "tf.While"(%arg0, %arg1) { cond = @while_cond_lt9, body = @while_body_add2, is_stateless = false, parallel_iterations = 1} : (tensor<i32>, tensor<i32>) -> (tensor<i32>, tensor<i32>)
    %1:2 = func.call @while_body_add2(%arg0, %arg1) : (tensor<i32>, tensor<i32>) -> (tensor<i32>, tensor<i32>)

func.func @num_replicas_replicated(%arg0: tensor<i32>, %arg1: tensor<i32>, %arg2: tensor<i32>, %arg3: tensor<i32>) -> (tensor<i32>, tensor<i32>) {
  %0:2 = tf_executor.graph {
    %control = tf_executor.island() wraps "tf.TPUReplicateMetadata"() {_tpu_replicate = "cluster", device = "/device:TPU:0", num_replicas = 2, topology = "topology"} : () -> ()

  }

  // CHECK-LABEL: func.func private @test_sdpa
  func.func private @test_sdpa(%arg0: tensor<1x100x32x4xf32>, %arg1: tensor<1x500x4x4xf32>, %arg2: tensor<1x500x4x4xf32>, %arg3: tensor<1x1x100x500xf32>, %arg4: tensor<f32>) -> tensor<1x100x32x4xf32> {

// RUN: odml-to-stablehlo-opt %s -tfl-parse-stablehlo-ops | FileCheck -dump-input always %s

module {
  func.func @main(%arg0: tensor<8x8x1x207xf32>, %arg1: tensor<3x3x16x207xf32>) -> tensor<16x8x8x1xf32> {

func.func @main(tensor<40x37xf32>, tensor<40x37xf32>) -> tensor<40x40xf32> {
^bb0(%arg0: tensor<40x37xf32>, %arg1: tensor<40x37xf32>):
  %cst = arith.constant dense<1.0> : tensor<40xf32>