testServices.expressionMarkerProvider.getElementsOfTypeAtCarets<KtDeclaration>(testServices).single().first

        val restoreAt =
            testServices.expressionMarkerProvider.getElementsOfTypeAtCarets<KtElement>(
                testServices,
                caretTag = "restoreAt"
            ).single().first

        val project = declaration.project

    Arg<TF_StrTensor, [{shape {N}.  The names of the tensors to be restored. This is tensor name in the model.}]>:$tensor_names,
    Arg<TF_StrTensor, [{shape {N}.  The slice specs of the tensors to be restored.
Empty strings indicate that they are non-partitioned tensors.}]>:$shape_and_slices,
    // VarHandles for restored tensors.
    Variadic<TF_Tensor>:$var_handles,
    // Data types for restored tensor.
    TypeArrayAttr: $restored_dtypes,

    %cst_1 = "tf.Const"() <{value = dense<["y", "z"]> : tensor<2x!tf_type.string>}> : () -> tensor<2x!tf_type.string>
    //expected-error@below {{'tf.RestoreV2' op expects 2 valid users, but got 1}}
    %0:2 = "tf.RestoreV2"(%cst, %cst_1, %cst_0): (tensor<!tf_type.string>, tensor<2x!tf_type.string>, tensor<2x!tf_type.string>) -> (tensor<3x1xf32>, tensor<1x3xf32>)

  // CHECK-NOT: tf.RestoreV2
  %0 = "tf.RestoreV2"(%cst, %cst_1, %cst_0): (tensor<!tf_type.string>, tensor<1x!tf_type.string>, tensor<1x!tf_type.string>) -> tensor<3x1xf32>
  %1 = "tf.VarHandleOp"() <{container = "", shared_name = "y"}> : () -> tensor<!tf_type.resource<tensor<3x1xf32>>>
  return
}


// CHECK-LABEL: func.func @used_restore_remains
func.func @used_restore_remains() {

  // CHECK: %[[FOO_NAME:.*]] = "tf.Const"() <{value = dense<"foo"> : tensor<1x!tf_type.string>}>
  // CHECK: %[[FOO:.*]] = "tf.RestoreV2"(%[[ARG0]], %[[FOO_NAME]], {{.*}})

  // CHECK: %[[BAR_NAME:.*]] = "tf.Const"() <{value = dense<"bar"> : tensor<1x!tf_type.string>}>
  // CHECK: %[[BAR:.*]] = "tf.RestoreV2"(%[[ARG0]], %[[BAR_NAME]], {{.*}})

  // CHECK: return %[[FOO]], %[[BAR]]
  func.return %2#0, %2#1 : tensor<*xf32>, tensor<*xi32>

// CHECK-LABEL: func @single_restore_group
// CHECK-SAME:    (%[[ARG0:.*]]: {{.*}})
func.func @single_restore_group(%arg0: tensor<!tf_type.string>) -> (tensor<*xf32>, tensor<*xi32>) {
  %0 = "tf.Const"() {value = dense<"foo"> : tensor<1x!tf_type.string>} : () -> tensor<1x!tf_type.string>
  %1 = "tf.Const"() {value = dense<""> : tensor<1x!tf_type.string>} : () -> tensor<1x!tf_type.string>

        override fun toTracking(): Tracking {
            throw IllegalStateException("Cannot track state because it was restored")
        }

        override fun toRestoring(): Restoring {
            throw IllegalStateException("Cannot restore state because it was already restored")
        }

        fun loadFrom(storedState: CachedEnvironmentState) {
            if (storedState.cleared) {

        assertTrue(enabledOnOtherThread)
    }

    @Test
    fun `input tracking is restored to the state when it was disabled`() {
        val state = InputTrackingState()
        state.disableForCurrentThread() // <1>
        state.disableForCurrentThread() // <2>

        state.restoreForCurrentThread() // Revert call at <2>, restore to "disabled" state set by call at <1>
        assertFalse(state.isEnabledForCurrentThread())

/**
 * [KaSymbol] is valid only during read action it was created in
 * To pass the symbol from one read action to another the KtSymbolPointer should be used
 *
 * We can restore the symbol
 *  * for symbol which came from Kotlin source it will be restored based on [com.intellij.psi.SmartPsiElementPointer]
 *  * restoring symbols which came from Java source is not supported yet
 *  * for library symbols:

# CHECK-SAME: min_consumer
# CHECK-SAME: producer

# CHECK: tf_saved_model.session_initializer
# CHECK-SAME: initializers = [@[[restore:.*]]]

# CHECK: "tf_saved_model.asset"()
# CHECK-SAME: <{filename = [[filename:.*]], sym_name = "[[sym_name:.*]]"}> : () -> ()

# CHECK:      func @[[restore]](
# CHECK-SAME:   [[variable_path:%.*]]: tensor<!tf_type.string> {tf_saved_model.bound_input = @[[sym_name]]}