Merge commit for internal changes

WORKSPACE

@@ -1,19 +1,29 @@
 workspace(name = "tf_serving")
 
-local_repository(
+# To update TensorFlow to a new revision.
+# 1. Update the 'git_commit' args below to include the new git hash.
+# 2. Get the sha256 hash of the archive with a command such as...
+#    curl -L https://github.com/tensorflow/tensorflow/archive/<git hash>.tar.gz | sha256sum
+#    and update the 'sha256' arg with the result.
+# 3. Request the new archive to be mirrored on mirror.bazel.build for more
+#    reliable downloads.
+load("//tensorflow_serving:repo.bzl", "tensorflow_http_archive")
+
+tensorflow_http_archive(
     name = "org_tensorflow",
-    path = "tensorflow",
+    sha256 = "21d6ac553adcfc9d089925f6d6793fee6a67264a0ce717bc998636662df4ca7e",
+    git_commit = "bc69c4ceed6544c109be5693eb40ddcf3a4eb95d",
 )
 
 # TensorFlow depends on "io_bazel_rules_closure" so we need this here.
 # Needs to be kept in sync with the same target in TensorFlow's WORKSPACE file.
 http_archive(
     name = "io_bazel_rules_closure",
-    sha256 = "110fe68753413777944b473c25eed6368c4a0487cee23a7bac1b13cc49d3e257",
-    strip_prefix = "rules_closure-4af89ef1db659eb41f110df189b67d4cf14073e1",
+    sha256 = "dbe0da2cca88194d13dc5a7125a25dd7b80e1daec7839f33223de654d7a1bcc8",
+    strip_prefix = "rules_closure-ba3e07cb88be04a2d4af7009caa0ff3671a79d06",
     urls = [
-        "http://mirror.bazel.build/github.com/bazelbuild/rules_closure/archive/4af89ef1db659eb41f110df189b67d4cf14073e1.tar.gz",
-        "https://github.com/bazelbuild/rules_closure/archive/4af89ef1db659eb41f110df189b67d4cf14073e1.tar.gz",  # 2017-08-28
+        "https://mirror.bazel.build/github.com/bazelbuild/rules_closure/archive/ba3e07cb88be04a2d4af7009caa0ff3671a79d06.tar.gz",
+        "https://github.com/bazelbuild/rules_closure/archive/ba3e07cb88be04a2d4af7009caa0ff3671a79d06.tar.gz",  # 2017-10-31
     ],
 )
 

tensorflow_serving/apis/BUILD

@@ -156,6 +156,57 @@ serving_go_grpc_library(
     deps = [":prediction_service_go_proto"],
 )
 
+serving_proto_library(
+    name = "get_model_status_proto",
+    srcs = ["get_model_status.proto"],
+    cc_api_version = 2,
+    go_api_version = 2,
+    java_api_version = 2,
+    deps = [
+        ":model_proto",
+        "//tensorflow_serving/util:status_proto",
+    ],
+)
+
+serving_proto_library_py(
+    name = "get_model_status_proto_py_pb2",
+    srcs = ["get_model_status.proto"],
+    proto_library = "get_model_status_proto",
+    deps = [
+        ":model_proto_py_pb2",
+        "//tensorflow_serving/util:status_proto_py_pb2",
+    ],
+)
+
+serving_proto_library(
+    name = "model_service_proto",
+    srcs = ["model_service.proto"],
+    has_services = 1,
+    cc_api_version = 2,
+    cc_grpc_version = 1,
+    go_api_version = 2,
+    java_api_version = 2,
+    deps = [
+        ":get_model_status_proto",
+    ],
+)
+
+py_library(
+    name = "model_service_proto_py_pb2",
+    srcs = [
+        "model_service_pb2.py",
+        "model_service_pb2_grpc.py",
+    ],
+    srcs_version = "PY2AND3",
+    deps = [":get_model_status_proto_py_pb2"],
+)
+
+serving_go_grpc_library(
+    name = "model_service_grpc",
+    srcs = [":model_service_proto"],
+    deps = [":model_service_go_proto"],
+)
+
 serving_proto_library(
     name = "classification_proto",
     srcs = ["classification.proto"],

tensorflow_serving/apis/classification.proto

@@ -30,14 +30,18 @@ message ClassificationResult {
 // RPC Interfaces
 
 message ClassificationRequest {
-  // Model Specification.
+  // Model Specification. If version is not specified, will use the latest
+  // (numerical) version.
   ModelSpec model_spec = 1;
 
   // Input data.
   tensorflow.serving.Input input = 2;
 }
 
 message ClassificationResponse {
+  // Effective Model Specification used for classification.
+  ModelSpec model_spec = 2;
+
   // Result of the classification.
   ClassificationResult result = 1;
 }

tensorflow_serving/apis/get_model_metadata.proto

@@ -14,6 +14,7 @@ message SignatureDefMap {
 
 message GetModelMetadataRequest {
   // Model Specification indicating which model we are querying for metadata.
+  // If version is not specified, will use the latest (numerical) version.
   ModelSpec model_spec = 1;
   // Metadata fields to get. Currently supported: "signature_def".
   repeated string metadata_field = 2;

tensorflow_serving/apis/get_model_status.proto

@@ -0,0 +1,67 @@
+syntax = "proto3";
+
+option cc_enable_arenas = true;
+
+import "tensorflow_serving/apis/model.proto";
+import "tensorflow_serving/util/status.proto";
+
+package tensorflow.serving;
+
+// GetModelStatusRequest contains a ModelSpec indicating the model for which
+// to get status.
+message GetModelStatusRequest {
+  // Model Specification. If version is not specified, information about all
+  // versions of the model will be returned. If a version is specified, the
+  // status of only that version will be returned.
+  ModelSpec model_spec = 1;
+}
+
+// Version number, state, and status for a single version of a model.
+message ModelVersionStatus {
+  // Model version.
+  int64 version = 1;
+
+  // States that map to ManagerState enum in
+  // tensorflow_serving/core/servable_state.h
+  enum State {
+    // Default value.
+    UNKNOWN = 0;
+
+    // The manager is tracking this servable, but has not initiated any action
+    // pertaining to it.
+    START = 10;
+
+    // The manager has decided to load this servable. In particular, checks
+    // around resource availability and other aspects have passed, and the
+    // manager is about to invoke the loader's Load() method.
+    LOADING = 20;
+
+    // The manager has successfully loaded this servable and made it available
+    // for serving (i.e. GetServableHandle(id) will succeed). To avoid races,
+    // this state is not reported until *after* the servable is made
+    // available.
+    AVAILABLE = 30;
+
+    // The manager has decided to make this servable unavailable, and unload
+    // it. To avoid races, this state is reported *before* the servable is
+    // made unavailable.
+    UNLOADING = 40;
+
+    // This servable has reached the end of its journey in the manager. Either
+    // it loaded and ultimately unloaded successfully, or it hit an error at
+    // some point in its lifecycle.
+    END = 50;
+  }
+
+  // Model state.
+  State state = 2;
+
+  // Model status.
+  StatusProto status = 3;
+}
+
+// Response for ModelStatusRequest on successful run.
+message GetModelStatusResponse {
+  // Version number and status information for applicable model version(s).
+  repeated ModelVersionStatus model_version_status = 1;
+}

tensorflow_serving/apis/inference.proto

@@ -21,6 +21,8 @@ package tensorflow.serving;
 
 // Inference request such as classification, regression, etc...
 message InferenceTask {
+  // Model Specification. If version is not specified, will use the latest
+  // (numerical) version.
   ModelSpec model_spec = 1;
 
   // Signature's method_name. Should be one of the method names defined in

tensorflow_serving/apis/model.proto

@@ -10,10 +10,7 @@ message ModelSpec {
   // Required servable name.
   string name = 1;
 
-  // Optional version. If unspecified, will use the latest (numerical) version.
-  // Typically not needed unless coordinating across multiple models that were
-  // co-trained and/or have inter-dependencies on the versions used at inference
-  // time.
+  // Optional version.
   google.protobuf.Int64Value version = 2;
 
   // A named signature to evaluate. If unspecified, the default signature will

tensorflow_serving/apis/model_service.proto

@@ -0,0 +1,17 @@
+syntax = "proto3";
+
+option cc_enable_arenas = true;
+
+import "tensorflow_serving/apis/get_model_status.proto";
+
+package tensorflow.serving;
+
+// ModelService provides access to information about model versions
+// that have been handled by the model server.
+service ModelService {
+  // Gets status of model. If the ModelSpec in the request does not specify
+  // version, information about all versions of the model will be returned. If
+  // the ModelSpec in the request does specify a version, the status of only
+  // that version will be returned.
+  rpc GetModelStatus(GetModelStatusRequest) returns (GetModelStatusResponse);
+}