Update ML Service mojoms to match latest API in Chrome OS

This syncs Chrome's version of the ML Service Mojo interface with
Chrome OS's version in src/platform2/ml/mojom.

The incorporated mojom changes introduce error/status responses from
most of the mojom methods.

No clients depend on this yet so the only required C++ change is an
update to the LoadModel helper in the client library.

Bug: 836095
Change-Id: I15a7ba831792290c7b68db889332efd356163d28
Reviewed-on: https://chromium-review.googlesource.com/1226650
Commit-Queue: Andrew Moylan <amoylan@chromium.org>
Reviewed-by: Sam McNally <sammc@chromium.org>
Reviewed-by: Michael Martis <martis@chromium.org>
Cr-Commit-Position: refs/heads/master@{#591274}

chromeos/services/machine_learning/public/cpp/service_connection.cc

@@ -21,11 +21,14 @@ ServiceConnection* ServiceConnection::GetInstance() {
   return service_connection.get();
 }
 
-void ServiceConnection::LoadModel(mojom::ModelSpecPtr spec,
-                                  mojom::ModelRequest request) {
+void ServiceConnection::LoadModel(
+    mojom::ModelSpecPtr spec,
+    mojom::ModelRequest request,
+    mojom::MachineLearningService::LoadModelCallback result_callback) {
   DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker_);
   BindMachineLearningServiceIfNeeded();
-  machine_learning_service_->LoadModel(std::move(spec), std::move(request));
+  machine_learning_service_->LoadModel(std::move(spec), std::move(request),
+                                       std::move(result_callback));
 }
 
 void ServiceConnection::BindMachineLearningServiceIfNeeded() {

chromeos/services/machine_learning/public/cpp/service_connection.h

@@ -17,10 +17,11 @@ namespace machine_learning {
 // interface.
 // Usage:
 //   chromeos::machine_learning::mojom::ModelPtr model;
-//   chromeos::machine_learning::mojom::ModelSpec spec;
+//   chromeos::machine_learning::mojom::ModelSpec spec = ...;
 //   chromeos::machine_learning::ServiceConnection::GetInstance()
-//       ->LoadModel(spec, mojom::MakeRequest(&model));
-//   // Use model ...
+//       ->LoadModel(spec, mojom::MakeRequest(&model),
+//                   base::BindOnce(&MyCallBack));
+//   // Use |model| or wait for |MyCallBack|.
 // Sequencing: Must be used on a single sequence (may be created on another).
 class ServiceConnection {
  public:
@@ -29,7 +30,10 @@ class ServiceConnection {
   // Instruct ML daemon to load the model specified in |spec|, binding a Model
   // implementation to |request|.
   // Bootstraps the initial Mojo connection to the daemon if necessary.
-  void LoadModel(mojom::ModelSpecPtr spec, mojom::ModelRequest request);
+  void LoadModel(
+      mojom::ModelSpecPtr spec,
+      mojom::ModelRequest request,
+      mojom::MachineLearningService::LoadModelCallback result_callback);
 
  private:
   friend class base::NoDestructor<ServiceConnection>;

chromeos/services/machine_learning/public/cpp/service_connection_unittest.cc

@@ -43,9 +43,10 @@ class ServiceConnectionTest : public testing::Test {
 // Tests that BindModelProvider runs OK (no crash) in a basic Mojo environment.
 TEST_F(ServiceConnectionTest, BindModelProvider) {
   mojom::ModelPtr model;
-  mojom::ModelSpecPtr spec = mojom::ModelSpec::New(mojom::ModelId::UNKNOWN);
-  ServiceConnection::GetInstance()->LoadModel(std::move(spec),
-                                              mojo::MakeRequest(&model));
+  mojom::ModelSpecPtr spec = mojom::ModelSpec::New(mojom::ModelId::TEST_MODEL);
+  ServiceConnection::GetInstance()->LoadModel(
+      std::move(spec), mojo::MakeRequest(&model),
+      base::BindOnce([](mojom::LoadModelResult result) {}));
 }
 
 }  // namespace

chromeos/services/machine_learning/public/mojom/graph_executor.mojom

@@ -11,6 +11,19 @@ module chromeos.machine_learning.mojom;
 
 import "chromeos/services/machine_learning/public/mojom/tensor.mojom";
 
+enum ExecuteResult {
+  OK = 0,
+  INPUT_MISSING_ERROR,
+  UNKNOWN_INPUT_ERROR,
+  INPUT_TYPE_ERROR,
+  INPUT_SHAPE_ERROR,
+  INPUT_FORMAT_ERROR,
+  OUTPUT_MISSING_ERROR,
+  UNKNOWN_OUTPUT_ERROR,
+  DUPLICATE_OUTPUT_ERROR,
+  EXECUTION_ERROR,
+};
+
 // API for performing inference on a TensorFlow graph. A given graph can be
 // executed multiple times with a single instance of GraphExecutor.
 interface GraphExecutor {
@@ -18,5 +31,5 @@ interface GraphExecutor {
   // graph. The returned |outputs| are the values for the nodes specified in
   // |output_names|.
   Execute(map<string, Tensor> inputs, array<string> output_names)
-      => (array<Tensor> outputs);
+       => (ExecuteResult result, array<Tensor>? outputs);
 };

chromeos/services/machine_learning/public/mojom/machine_learning_service.mojom

@@ -13,8 +13,14 @@ module chromeos.machine_learning.mojom;
 
 import "chromeos/services/machine_learning/public/mojom/model.mojom";
 
+enum LoadModelResult {
+  OK = 0,
+  MODEL_SPEC_ERROR,
+  LOAD_MODEL_ERROR,
+};
+
 // Top-level interface between Chromium and the ML Service daemon.
 interface MachineLearningService {
   // The ModelId inside ModelSpec is used to specify the model to be loaded.
-  LoadModel(ModelSpec spec, Model& request);
+  LoadModel(ModelSpec spec, Model& request) => (LoadModelResult result);
 };

chromeos/services/machine_learning/public/mojom/model.mojom

@@ -15,8 +15,13 @@ import "chromeos/services/machine_learning/public/mojom/graph_executor.mojom";
 
 enum ModelId {
   UNKNOWN,
-  TAB_DISCARDER,
-  POWER_MANAGER
+  TEST_MODEL,  // Only available in tests.
+};
+
+enum CreateGraphExecutorResult {
+  OK = 0,
+  MODEL_INTERPRETATION_ERROR,
+  MEMORY_ALLOCATION_ERROR,
 };
 
 struct ModelSpec {
@@ -27,5 +32,6 @@ struct ModelSpec {
 // interface pipe. The Model interface pipe can be used to acquire multiple
 // separate GraphExecutor instances.
 interface Model {
-  CreateGraphExecutor(GraphExecutor& request);
+  CreateGraphExecutor(GraphExecutor& request) =>
+      (CreateGraphExecutorResult result);
 };

chromeos/services/machine_learning/public/mojom/tensor.mojom

@@ -13,22 +13,29 @@
 
 module chromeos.machine_learning.mojom;
 
-// Corresponds to tensorflow.BytesList protobuf:
 struct StringList {
   array<string> value;
 };
 
-// Corresponds to tensorflow.FloatList protobuf:
-struct FloatList  {
+struct FloatList {
   array<double> value;
 };
 
-// Corresponds to tensorflow.Int64List protobuf:
 struct Int64List {
   array<int64> value;
 };
 
-// Corresponds to tensorflow.Feature protobuf:
+// The union of all supported tensor types. Supporting a new type comprises the
+// following:
+//  - Adding a new struct above (e.g. BoolList),
+//  - Adding this new struct to the union below,
+//  - Adding template specializations for the new type to
+//    platform2/ml/tensor_view.{h,cc}.
+//  - Updating platform2/ml/graph_executor_impl.cc to use a TensorView of the
+//    new type.
+//
+// TODO(chromium:836098): add new types (e.g. uint8, bool) as they become
+//                        useful.
 union ValueList {
   StringList string_list;
   FloatList float_list;