|
|
@@ -169,6 +169,7 @@
|
|
|
MetaGraphDef.prototype.collection_def = $util.emptyObject;
|
|
|
MetaGraphDef.prototype.signature_def = $util.emptyObject;
|
|
|
MetaGraphDef.prototype.asset_file_def = $util.emptyArray;
|
|
|
+ MetaGraphDef.prototype.object_graph_def = null;
|
|
|
|
|
|
MetaGraphDef.create = function create(properties) {
|
|
|
return new MetaGraphDef(properties);
|
|
|
@@ -211,6 +212,9 @@
|
|
|
message.asset_file_def = [];
|
|
|
message.asset_file_def.push($root.tensorflow.AssetFileDef.decode(reader, reader.uint32()));
|
|
|
break;
|
|
|
+ case 7:
|
|
|
+ message.object_graph_def = $root.tensorflow.SavedObjectGraph.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
default:
|
|
|
reader.skipType(tag & 7);
|
|
|
break;
|
|
|
@@ -263,6 +267,9 @@
|
|
|
message.asset_file_def = [];
|
|
|
message.asset_file_def.push($root.tensorflow.AssetFileDef.decodeText(reader, true));
|
|
|
break;
|
|
|
+ case "object_graph_def":
|
|
|
+ message.object_graph_def = $root.tensorflow.SavedObjectGraph.decodeText(reader, true);
|
|
|
+ break;
|
|
|
default:
|
|
|
reader.field(tag, message);
|
|
|
break;
|
|
|
@@ -318,6 +325,11 @@
|
|
|
return "asset_file_def." + error;
|
|
|
}
|
|
|
}
|
|
|
+ if (message.object_graph_def != null && message.hasOwnProperty("object_graph_def")) {
|
|
|
+ var error = $root.tensorflow.SavedObjectGraph.verify(message.object_graph_def);
|
|
|
+ if (error)
|
|
|
+ return "object_graph_def." + error;
|
|
|
+ }
|
|
|
return null;
|
|
|
};
|
|
|
|
|
|
@@ -370,6 +382,11 @@
|
|
|
message.asset_file_def[i] = $root.tensorflow.AssetFileDef.fromObject(object.asset_file_def[i]);
|
|
|
}
|
|
|
}
|
|
|
+ if (object.object_graph_def != null) {
|
|
|
+ if (typeof object.object_graph_def !== "object")
|
|
|
+ throw TypeError(".tensorflow.MetaGraphDef.object_graph_def: object expected");
|
|
|
+ message.object_graph_def = $root.tensorflow.SavedObjectGraph.fromObject(object.object_graph_def);
|
|
|
+ }
|
|
|
return message;
|
|
|
};
|
|
|
|
|
|
@@ -387,6 +404,7 @@
|
|
|
object.meta_info_def = null;
|
|
|
object.graph_def = null;
|
|
|
object.saver_def = null;
|
|
|
+ object.object_graph_def = null;
|
|
|
}
|
|
|
if (message.meta_info_def != null && message.hasOwnProperty("meta_info_def"))
|
|
|
object.meta_info_def = $root.tensorflow.MetaGraphDef.MetaInfoDef.toObject(message.meta_info_def, options);
|
|
|
@@ -410,6 +428,8 @@
|
|
|
for (var j = 0; j < message.asset_file_def.length; ++j)
|
|
|
object.asset_file_def[j] = $root.tensorflow.AssetFileDef.toObject(message.asset_file_def[j], options);
|
|
|
}
|
|
|
+ if (message.object_graph_def != null && message.hasOwnProperty("object_graph_def"))
|
|
|
+ object.object_graph_def = $root.tensorflow.SavedObjectGraph.toObject(message.object_graph_def, options);
|
|
|
return object;
|
|
|
};
|
|
|
|
|
|
@@ -7799,6 +7819,4144 @@
|
|
|
return ResourceHandleProto;
|
|
|
})();
|
|
|
|
|
|
+ tensorflow.SavedObjectGraph = (function() {
|
|
|
+
|
|
|
+ function SavedObjectGraph(properties) {
|
|
|
+ this.nodes = [];
|
|
|
+ this.concrete_functions = {};
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ SavedObjectGraph.prototype.nodes = $util.emptyArray;
|
|
|
+ SavedObjectGraph.prototype.concrete_functions = $util.emptyObject;
|
|
|
+
|
|
|
+ SavedObjectGraph.create = function create(properties) {
|
|
|
+ return new SavedObjectGraph(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedObjectGraph.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.SavedObjectGraph(), key;
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ if (!(message.nodes && message.nodes.length))
|
|
|
+ message.nodes = [];
|
|
|
+ message.nodes.push($root.tensorflow.SavedObject.decode(reader, reader.uint32()));
|
|
|
+ break;
|
|
|
+ case 2:
|
|
|
+ reader.skip().pos++;
|
|
|
+ if (message.concrete_functions === $util.emptyObject)
|
|
|
+ message.concrete_functions = {};
|
|
|
+ key = reader.string();
|
|
|
+ reader.pos++;
|
|
|
+ message.concrete_functions[key] = $root.tensorflow.SavedConcreteFunction.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedObjectGraph.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.SavedObjectGraph(), key;
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "nodes":
|
|
|
+ if (!(message.nodes && message.nodes.length))
|
|
|
+ message.nodes = [];
|
|
|
+ message.nodes.push($root.tensorflow.SavedObject.decodeText(reader, true));
|
|
|
+ break;
|
|
|
+ case "concrete_functions":
|
|
|
+ reader.assert("{");
|
|
|
+ if (message.concrete_functions === $util.emptyObject)
|
|
|
+ message.concrete_functions = {};
|
|
|
+ reader.assert("key");
|
|
|
+ reader.value();
|
|
|
+ key = reader.string();
|
|
|
+ reader.assert("value");
|
|
|
+ message.concrete_functions[key] = $root.tensorflow.SavedConcreteFunction.decodeText(reader, true);
|
|
|
+ reader.assert("}");
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedObjectGraph.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ if (message.nodes != null && message.hasOwnProperty("nodes")) {
|
|
|
+ if (!Array.isArray(message.nodes))
|
|
|
+ return "nodes: array expected";
|
|
|
+ for (var i = 0; i < message.nodes.length; ++i) {
|
|
|
+ var error = $root.tensorflow.SavedObject.verify(message.nodes[i]);
|
|
|
+ if (error)
|
|
|
+ return "nodes." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (message.concrete_functions != null && message.hasOwnProperty("concrete_functions")) {
|
|
|
+ if (!$util.isObject(message.concrete_functions))
|
|
|
+ return "concrete_functions: object expected";
|
|
|
+ var key = Object.keys(message.concrete_functions);
|
|
|
+ for (var i = 0; i < key.length; ++i) {
|
|
|
+ var error = $root.tensorflow.SavedConcreteFunction.verify(message.concrete_functions[key[i]]);
|
|
|
+ if (error)
|
|
|
+ return "concrete_functions." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedObjectGraph.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.SavedObjectGraph)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.SavedObjectGraph();
|
|
|
+ if (object.nodes) {
|
|
|
+ if (!Array.isArray(object.nodes))
|
|
|
+ throw TypeError(".tensorflow.SavedObjectGraph.nodes: array expected");
|
|
|
+ message.nodes = [];
|
|
|
+ for (var i = 0; i < object.nodes.length; ++i) {
|
|
|
+ if (typeof object.nodes[i] !== "object")
|
|
|
+ throw TypeError(".tensorflow.SavedObjectGraph.nodes: object expected");
|
|
|
+ message.nodes[i] = $root.tensorflow.SavedObject.fromObject(object.nodes[i]);
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (object.concrete_functions) {
|
|
|
+ if (typeof object.concrete_functions !== "object")
|
|
|
+ throw TypeError(".tensorflow.SavedObjectGraph.concrete_functions: object expected");
|
|
|
+ message.concrete_functions = {};
|
|
|
+ for (var keys = Object.keys(object.concrete_functions), i = 0; i < keys.length; ++i) {
|
|
|
+ if (typeof object.concrete_functions[keys[i]] !== "object")
|
|
|
+ throw TypeError(".tensorflow.SavedObjectGraph.concrete_functions: object expected");
|
|
|
+ message.concrete_functions[keys[i]] = $root.tensorflow.SavedConcreteFunction.fromObject(object.concrete_functions[keys[i]]);
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedObjectGraph.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.arrays || options.defaults)
|
|
|
+ object.nodes = [];
|
|
|
+ if (options.objects || options.defaults)
|
|
|
+ object.concrete_functions = {};
|
|
|
+ if (message.nodes && message.nodes.length) {
|
|
|
+ object.nodes = [];
|
|
|
+ for (var j = 0; j < message.nodes.length; ++j)
|
|
|
+ object.nodes[j] = $root.tensorflow.SavedObject.toObject(message.nodes[j], options);
|
|
|
+ }
|
|
|
+ var keys2;
|
|
|
+ if (message.concrete_functions && (keys2 = Object.keys(message.concrete_functions)).length) {
|
|
|
+ object.concrete_functions = {};
|
|
|
+ for (var j = 0; j < keys2.length; ++j)
|
|
|
+ object.concrete_functions[keys2[j]] = $root.tensorflow.SavedConcreteFunction.toObject(message.concrete_functions[keys2[j]], options);
|
|
|
+ }
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedObjectGraph.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return SavedObjectGraph;
|
|
|
+ })();
|
|
|
+
|
|
|
+ tensorflow.SavedObject = (function() {
|
|
|
+
|
|
|
+ function SavedObject(properties) {
|
|
|
+ this.children = [];
|
|
|
+ this.slot_variables = [];
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ SavedObject.prototype.children = $util.emptyArray;
|
|
|
+ SavedObject.prototype.slot_variables = $util.emptyArray;
|
|
|
+ SavedObject.prototype.user_object = null;
|
|
|
+ SavedObject.prototype.asset = null;
|
|
|
+ SavedObject.prototype["function"] = null;
|
|
|
+ SavedObject.prototype.variable = null;
|
|
|
+ SavedObject.prototype.bare_concrete_function = null;
|
|
|
+ SavedObject.prototype.constant = null;
|
|
|
+ SavedObject.prototype.resource = null;
|
|
|
+
|
|
|
+ var $oneOfFields;
|
|
|
+
|
|
|
+ Object.defineProperty(SavedObject.prototype, "kind", {
|
|
|
+ get: $util.oneOfGetter($oneOfFields = ["user_object", "asset", "function", "variable", "bare_concrete_function", "constant", "resource"]),
|
|
|
+ set: $util.oneOfSetter($oneOfFields)
|
|
|
+ });
|
|
|
+
|
|
|
+ SavedObject.create = function create(properties) {
|
|
|
+ return new SavedObject(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedObject.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.SavedObject();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ if (!(message.children && message.children.length))
|
|
|
+ message.children = [];
|
|
|
+ message.children.push($root.tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference.decode(reader, reader.uint32()));
|
|
|
+ break;
|
|
|
+ case 3:
|
|
|
+ if (!(message.slot_variables && message.slot_variables.length))
|
|
|
+ message.slot_variables = [];
|
|
|
+ message.slot_variables.push($root.tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference.decode(reader, reader.uint32()));
|
|
|
+ break;
|
|
|
+ case 4:
|
|
|
+ message.user_object = $root.tensorflow.SavedUserObject.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ case 5:
|
|
|
+ message.asset = $root.tensorflow.SavedAsset.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ case 6:
|
|
|
+ message["function"] = $root.tensorflow.SavedFunction.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ case 7:
|
|
|
+ message.variable = $root.tensorflow.SavedVariable.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ case 8:
|
|
|
+ message.bare_concrete_function = $root.tensorflow.SavedBareConcreteFunction.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ case 9:
|
|
|
+ message.constant = $root.tensorflow.SavedConstant.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ case 10:
|
|
|
+ message.resource = $root.tensorflow.SavedResource.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedObject.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.SavedObject();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "children":
|
|
|
+ if (!(message.children && message.children.length))
|
|
|
+ message.children = [];
|
|
|
+ message.children.push($root.tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference.decodeText(reader, true));
|
|
|
+ break;
|
|
|
+ case "slot_variables":
|
|
|
+ if (!(message.slot_variables && message.slot_variables.length))
|
|
|
+ message.slot_variables = [];
|
|
|
+ message.slot_variables.push($root.tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference.decodeText(reader, true));
|
|
|
+ break;
|
|
|
+ case "user_object":
|
|
|
+ message.user_object = $root.tensorflow.SavedUserObject.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ case "asset":
|
|
|
+ message.asset = $root.tensorflow.SavedAsset.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ case "function":
|
|
|
+ message["function"] = $root.tensorflow.SavedFunction.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ case "variable":
|
|
|
+ message.variable = $root.tensorflow.SavedVariable.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ case "bare_concrete_function":
|
|
|
+ message.bare_concrete_function = $root.tensorflow.SavedBareConcreteFunction.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ case "constant":
|
|
|
+ message.constant = $root.tensorflow.SavedConstant.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ case "resource":
|
|
|
+ message.resource = $root.tensorflow.SavedResource.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedObject.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ var properties = {};
|
|
|
+ if (message.children != null && message.hasOwnProperty("children")) {
|
|
|
+ if (!Array.isArray(message.children))
|
|
|
+ return "children: array expected";
|
|
|
+ for (var i = 0; i < message.children.length; ++i) {
|
|
|
+ var error = $root.tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference.verify(message.children[i]);
|
|
|
+ if (error)
|
|
|
+ return "children." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (message.slot_variables != null && message.hasOwnProperty("slot_variables")) {
|
|
|
+ if (!Array.isArray(message.slot_variables))
|
|
|
+ return "slot_variables: array expected";
|
|
|
+ for (var i = 0; i < message.slot_variables.length; ++i) {
|
|
|
+ var error = $root.tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference.verify(message.slot_variables[i]);
|
|
|
+ if (error)
|
|
|
+ return "slot_variables." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (message.user_object != null && message.hasOwnProperty("user_object")) {
|
|
|
+ properties.kind = 1;
|
|
|
+ {
|
|
|
+ var error = $root.tensorflow.SavedUserObject.verify(message.user_object);
|
|
|
+ if (error)
|
|
|
+ return "user_object." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (message.asset != null && message.hasOwnProperty("asset")) {
|
|
|
+ if (properties.kind === 1)
|
|
|
+ return "kind: multiple values";
|
|
|
+ properties.kind = 1;
|
|
|
+ {
|
|
|
+ var error = $root.tensorflow.SavedAsset.verify(message.asset);
|
|
|
+ if (error)
|
|
|
+ return "asset." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (message["function"] != null && message.hasOwnProperty("function")) {
|
|
|
+ if (properties.kind === 1)
|
|
|
+ return "kind: multiple values";
|
|
|
+ properties.kind = 1;
|
|
|
+ {
|
|
|
+ var error = $root.tensorflow.SavedFunction.verify(message["function"]);
|
|
|
+ if (error)
|
|
|
+ return "function." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (message.variable != null && message.hasOwnProperty("variable")) {
|
|
|
+ if (properties.kind === 1)
|
|
|
+ return "kind: multiple values";
|
|
|
+ properties.kind = 1;
|
|
|
+ {
|
|
|
+ var error = $root.tensorflow.SavedVariable.verify(message.variable);
|
|
|
+ if (error)
|
|
|
+ return "variable." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (message.bare_concrete_function != null && message.hasOwnProperty("bare_concrete_function")) {
|
|
|
+ if (properties.kind === 1)
|
|
|
+ return "kind: multiple values";
|
|
|
+ properties.kind = 1;
|
|
|
+ {
|
|
|
+ var error = $root.tensorflow.SavedBareConcreteFunction.verify(message.bare_concrete_function);
|
|
|
+ if (error)
|
|
|
+ return "bare_concrete_function." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (message.constant != null && message.hasOwnProperty("constant")) {
|
|
|
+ if (properties.kind === 1)
|
|
|
+ return "kind: multiple values";
|
|
|
+ properties.kind = 1;
|
|
|
+ {
|
|
|
+ var error = $root.tensorflow.SavedConstant.verify(message.constant);
|
|
|
+ if (error)
|
|
|
+ return "constant." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (message.resource != null && message.hasOwnProperty("resource")) {
|
|
|
+ if (properties.kind === 1)
|
|
|
+ return "kind: multiple values";
|
|
|
+ properties.kind = 1;
|
|
|
+ {
|
|
|
+ var error = $root.tensorflow.SavedResource.verify(message.resource);
|
|
|
+ if (error)
|
|
|
+ return "resource." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedObject.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.SavedObject)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.SavedObject();
|
|
|
+ if (object.children) {
|
|
|
+ if (!Array.isArray(object.children))
|
|
|
+ throw TypeError(".tensorflow.SavedObject.children: array expected");
|
|
|
+ message.children = [];
|
|
|
+ for (var i = 0; i < object.children.length; ++i) {
|
|
|
+ if (typeof object.children[i] !== "object")
|
|
|
+ throw TypeError(".tensorflow.SavedObject.children: object expected");
|
|
|
+ message.children[i] = $root.tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference.fromObject(object.children[i]);
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (object.slot_variables) {
|
|
|
+ if (!Array.isArray(object.slot_variables))
|
|
|
+ throw TypeError(".tensorflow.SavedObject.slot_variables: array expected");
|
|
|
+ message.slot_variables = [];
|
|
|
+ for (var i = 0; i < object.slot_variables.length; ++i) {
|
|
|
+ if (typeof object.slot_variables[i] !== "object")
|
|
|
+ throw TypeError(".tensorflow.SavedObject.slot_variables: object expected");
|
|
|
+ message.slot_variables[i] = $root.tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference.fromObject(object.slot_variables[i]);
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (object.user_object != null) {
|
|
|
+ if (typeof object.user_object !== "object")
|
|
|
+ throw TypeError(".tensorflow.SavedObject.user_object: object expected");
|
|
|
+ message.user_object = $root.tensorflow.SavedUserObject.fromObject(object.user_object);
|
|
|
+ }
|
|
|
+ if (object.asset != null) {
|
|
|
+ if (typeof object.asset !== "object")
|
|
|
+ throw TypeError(".tensorflow.SavedObject.asset: object expected");
|
|
|
+ message.asset = $root.tensorflow.SavedAsset.fromObject(object.asset);
|
|
|
+ }
|
|
|
+ if (object["function"] != null) {
|
|
|
+ if (typeof object["function"] !== "object")
|
|
|
+ throw TypeError(".tensorflow.SavedObject.function: object expected");
|
|
|
+ message["function"] = $root.tensorflow.SavedFunction.fromObject(object["function"]);
|
|
|
+ }
|
|
|
+ if (object.variable != null) {
|
|
|
+ if (typeof object.variable !== "object")
|
|
|
+ throw TypeError(".tensorflow.SavedObject.variable: object expected");
|
|
|
+ message.variable = $root.tensorflow.SavedVariable.fromObject(object.variable);
|
|
|
+ }
|
|
|
+ if (object.bare_concrete_function != null) {
|
|
|
+ if (typeof object.bare_concrete_function !== "object")
|
|
|
+ throw TypeError(".tensorflow.SavedObject.bare_concrete_function: object expected");
|
|
|
+ message.bare_concrete_function = $root.tensorflow.SavedBareConcreteFunction.fromObject(object.bare_concrete_function);
|
|
|
+ }
|
|
|
+ if (object.constant != null) {
|
|
|
+ if (typeof object.constant !== "object")
|
|
|
+ throw TypeError(".tensorflow.SavedObject.constant: object expected");
|
|
|
+ message.constant = $root.tensorflow.SavedConstant.fromObject(object.constant);
|
|
|
+ }
|
|
|
+ if (object.resource != null) {
|
|
|
+ if (typeof object.resource !== "object")
|
|
|
+ throw TypeError(".tensorflow.SavedObject.resource: object expected");
|
|
|
+ message.resource = $root.tensorflow.SavedResource.fromObject(object.resource);
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedObject.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.arrays || options.defaults) {
|
|
|
+ object.children = [];
|
|
|
+ object.slot_variables = [];
|
|
|
+ }
|
|
|
+ if (message.children && message.children.length) {
|
|
|
+ object.children = [];
|
|
|
+ for (var j = 0; j < message.children.length; ++j)
|
|
|
+ object.children[j] = $root.tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference.toObject(message.children[j], options);
|
|
|
+ }
|
|
|
+ if (message.slot_variables && message.slot_variables.length) {
|
|
|
+ object.slot_variables = [];
|
|
|
+ for (var j = 0; j < message.slot_variables.length; ++j)
|
|
|
+ object.slot_variables[j] = $root.tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference.toObject(message.slot_variables[j], options);
|
|
|
+ }
|
|
|
+ if (message.user_object != null && message.hasOwnProperty("user_object")) {
|
|
|
+ object.user_object = $root.tensorflow.SavedUserObject.toObject(message.user_object, options);
|
|
|
+ if (options.oneofs)
|
|
|
+ object.kind = "user_object";
|
|
|
+ }
|
|
|
+ if (message.asset != null && message.hasOwnProperty("asset")) {
|
|
|
+ object.asset = $root.tensorflow.SavedAsset.toObject(message.asset, options);
|
|
|
+ if (options.oneofs)
|
|
|
+ object.kind = "asset";
|
|
|
+ }
|
|
|
+ if (message["function"] != null && message.hasOwnProperty("function")) {
|
|
|
+ object["function"] = $root.tensorflow.SavedFunction.toObject(message["function"], options);
|
|
|
+ if (options.oneofs)
|
|
|
+ object.kind = "function";
|
|
|
+ }
|
|
|
+ if (message.variable != null && message.hasOwnProperty("variable")) {
|
|
|
+ object.variable = $root.tensorflow.SavedVariable.toObject(message.variable, options);
|
|
|
+ if (options.oneofs)
|
|
|
+ object.kind = "variable";
|
|
|
+ }
|
|
|
+ if (message.bare_concrete_function != null && message.hasOwnProperty("bare_concrete_function")) {
|
|
|
+ object.bare_concrete_function = $root.tensorflow.SavedBareConcreteFunction.toObject(message.bare_concrete_function, options);
|
|
|
+ if (options.oneofs)
|
|
|
+ object.kind = "bare_concrete_function";
|
|
|
+ }
|
|
|
+ if (message.constant != null && message.hasOwnProperty("constant")) {
|
|
|
+ object.constant = $root.tensorflow.SavedConstant.toObject(message.constant, options);
|
|
|
+ if (options.oneofs)
|
|
|
+ object.kind = "constant";
|
|
|
+ }
|
|
|
+ if (message.resource != null && message.hasOwnProperty("resource")) {
|
|
|
+ object.resource = $root.tensorflow.SavedResource.toObject(message.resource, options);
|
|
|
+ if (options.oneofs)
|
|
|
+ object.kind = "resource";
|
|
|
+ }
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedObject.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return SavedObject;
|
|
|
+ })();
|
|
|
+
|
|
|
+ tensorflow.SavedUserObject = (function() {
|
|
|
+
|
|
|
+ function SavedUserObject(properties) {
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ SavedUserObject.prototype.identifier = "";
|
|
|
+ SavedUserObject.prototype.version = null;
|
|
|
+
|
|
|
+ SavedUserObject.create = function create(properties) {
|
|
|
+ return new SavedUserObject(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedUserObject.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.SavedUserObject();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ message.identifier = reader.string();
|
|
|
+ break;
|
|
|
+ case 2:
|
|
|
+ message.version = $root.tensorflow.VersionDef.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedUserObject.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.SavedUserObject();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "identifier":
|
|
|
+ reader.value();
|
|
|
+ message.identifier = reader.string();
|
|
|
+ break;
|
|
|
+ case "version":
|
|
|
+ message.version = $root.tensorflow.VersionDef.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedUserObject.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ if (message.identifier != null && message.hasOwnProperty("identifier"))
|
|
|
+ if (!$util.isString(message.identifier))
|
|
|
+ return "identifier: string expected";
|
|
|
+ if (message.version != null && message.hasOwnProperty("version")) {
|
|
|
+ var error = $root.tensorflow.VersionDef.verify(message.version);
|
|
|
+ if (error)
|
|
|
+ return "version." + error;
|
|
|
+ }
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedUserObject.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.SavedUserObject)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.SavedUserObject();
|
|
|
+ if (object.identifier != null)
|
|
|
+ message.identifier = String(object.identifier);
|
|
|
+ if (object.version != null) {
|
|
|
+ if (typeof object.version !== "object")
|
|
|
+ throw TypeError(".tensorflow.SavedUserObject.version: object expected");
|
|
|
+ message.version = $root.tensorflow.VersionDef.fromObject(object.version);
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedUserObject.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.defaults) {
|
|
|
+ object.identifier = "";
|
|
|
+ object.version = null;
|
|
|
+ }
|
|
|
+ if (message.identifier != null && message.hasOwnProperty("identifier"))
|
|
|
+ object.identifier = message.identifier;
|
|
|
+ if (message.version != null && message.hasOwnProperty("version"))
|
|
|
+ object.version = $root.tensorflow.VersionDef.toObject(message.version, options);
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedUserObject.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return SavedUserObject;
|
|
|
+ })();
|
|
|
+
|
|
|
+ tensorflow.SavedAsset = (function() {
|
|
|
+
|
|
|
+ function SavedAsset(properties) {
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ SavedAsset.prototype.asset_file_def_index = 0;
|
|
|
+
|
|
|
+ SavedAsset.create = function create(properties) {
|
|
|
+ return new SavedAsset(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedAsset.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.SavedAsset();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ message.asset_file_def_index = reader.int32();
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedAsset.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.SavedAsset();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "asset_file_def_index":
|
|
|
+ reader.value();
|
|
|
+ message.asset_file_def_index = reader.int32();
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedAsset.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ if (message.asset_file_def_index != null && message.hasOwnProperty("asset_file_def_index"))
|
|
|
+ if (!$util.isInteger(message.asset_file_def_index))
|
|
|
+ return "asset_file_def_index: integer expected";
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedAsset.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.SavedAsset)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.SavedAsset();
|
|
|
+ if (object.asset_file_def_index != null)
|
|
|
+ message.asset_file_def_index = object.asset_file_def_index | 0;
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedAsset.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.defaults)
|
|
|
+ object.asset_file_def_index = 0;
|
|
|
+ if (message.asset_file_def_index != null && message.hasOwnProperty("asset_file_def_index"))
|
|
|
+ object.asset_file_def_index = message.asset_file_def_index;
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedAsset.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return SavedAsset;
|
|
|
+ })();
|
|
|
+
|
|
|
+ tensorflow.SavedFunction = (function() {
|
|
|
+
|
|
|
+ function SavedFunction(properties) {
|
|
|
+ this.concrete_functions = [];
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ SavedFunction.prototype.concrete_functions = $util.emptyArray;
|
|
|
+ SavedFunction.prototype.function_spec = null;
|
|
|
+
|
|
|
+ SavedFunction.create = function create(properties) {
|
|
|
+ return new SavedFunction(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedFunction.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.SavedFunction();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ if (!(message.concrete_functions && message.concrete_functions.length))
|
|
|
+ message.concrete_functions = [];
|
|
|
+ message.concrete_functions.push(reader.string());
|
|
|
+ break;
|
|
|
+ case 2:
|
|
|
+ message.function_spec = $root.tensorflow.FunctionSpec.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedFunction.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.SavedFunction();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "concrete_functions":
|
|
|
+ if (!(message.concrete_functions && message.concrete_functions.length))
|
|
|
+ message.concrete_functions = [];
|
|
|
+ reader.value();
|
|
|
+ if (reader.first())
|
|
|
+ while (!reader.last()) {
|
|
|
+ message.concrete_functions.push(reader.string());
|
|
|
+ reader.next();
|
|
|
+ }
|
|
|
+ else
|
|
|
+ message.concrete_functions.push(reader.string());
|
|
|
+ break;
|
|
|
+ case "function_spec":
|
|
|
+ message.function_spec = $root.tensorflow.FunctionSpec.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedFunction.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ if (message.concrete_functions != null && message.hasOwnProperty("concrete_functions")) {
|
|
|
+ if (!Array.isArray(message.concrete_functions))
|
|
|
+ return "concrete_functions: array expected";
|
|
|
+ for (var i = 0; i < message.concrete_functions.length; ++i)
|
|
|
+ if (!$util.isString(message.concrete_functions[i]))
|
|
|
+ return "concrete_functions: string[] expected";
|
|
|
+ }
|
|
|
+ if (message.function_spec != null && message.hasOwnProperty("function_spec")) {
|
|
|
+ var error = $root.tensorflow.FunctionSpec.verify(message.function_spec);
|
|
|
+ if (error)
|
|
|
+ return "function_spec." + error;
|
|
|
+ }
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedFunction.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.SavedFunction)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.SavedFunction();
|
|
|
+ if (object.concrete_functions) {
|
|
|
+ if (!Array.isArray(object.concrete_functions))
|
|
|
+ throw TypeError(".tensorflow.SavedFunction.concrete_functions: array expected");
|
|
|
+ message.concrete_functions = [];
|
|
|
+ for (var i = 0; i < object.concrete_functions.length; ++i)
|
|
|
+ message.concrete_functions[i] = String(object.concrete_functions[i]);
|
|
|
+ }
|
|
|
+ if (object.function_spec != null) {
|
|
|
+ if (typeof object.function_spec !== "object")
|
|
|
+ throw TypeError(".tensorflow.SavedFunction.function_spec: object expected");
|
|
|
+ message.function_spec = $root.tensorflow.FunctionSpec.fromObject(object.function_spec);
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedFunction.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.arrays || options.defaults)
|
|
|
+ object.concrete_functions = [];
|
|
|
+ if (options.defaults)
|
|
|
+ object.function_spec = null;
|
|
|
+ if (message.concrete_functions && message.concrete_functions.length) {
|
|
|
+ object.concrete_functions = [];
|
|
|
+ for (var j = 0; j < message.concrete_functions.length; ++j)
|
|
|
+ object.concrete_functions[j] = message.concrete_functions[j];
|
|
|
+ }
|
|
|
+ if (message.function_spec != null && message.hasOwnProperty("function_spec"))
|
|
|
+ object.function_spec = $root.tensorflow.FunctionSpec.toObject(message.function_spec, options);
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedFunction.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return SavedFunction;
|
|
|
+ })();
|
|
|
+
|
|
|
+ tensorflow.SavedConcreteFunction = (function() {
|
|
|
+
|
|
|
+ function SavedConcreteFunction(properties) {
|
|
|
+ this.bound_inputs = [];
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ SavedConcreteFunction.prototype.bound_inputs = $util.emptyArray;
|
|
|
+ SavedConcreteFunction.prototype.canonicalized_input_signature = null;
|
|
|
+ SavedConcreteFunction.prototype.output_signature = null;
|
|
|
+
|
|
|
+ SavedConcreteFunction.create = function create(properties) {
|
|
|
+ return new SavedConcreteFunction(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedConcreteFunction.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.SavedConcreteFunction();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 2:
|
|
|
+ if (!(message.bound_inputs && message.bound_inputs.length))
|
|
|
+ message.bound_inputs = [];
|
|
|
+ if ((tag & 7) === 2) {
|
|
|
+ var end2 = reader.uint32() + reader.pos;
|
|
|
+ while (reader.pos < end2)
|
|
|
+ message.bound_inputs.push(reader.int32());
|
|
|
+ } else
|
|
|
+ message.bound_inputs.push(reader.int32());
|
|
|
+ break;
|
|
|
+ case 3:
|
|
|
+ message.canonicalized_input_signature = $root.tensorflow.StructuredValue.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ case 4:
|
|
|
+ message.output_signature = $root.tensorflow.StructuredValue.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedConcreteFunction.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.SavedConcreteFunction();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "bound_inputs":
|
|
|
+ if (!(message.bound_inputs && message.bound_inputs.length))
|
|
|
+ message.bound_inputs = [];
|
|
|
+ reader.value();
|
|
|
+ if (reader.first())
|
|
|
+ while (!reader.last()) {
|
|
|
+ message.bound_inputs.push(reader.int32());
|
|
|
+ reader.next();
|
|
|
+ }
|
|
|
+ else
|
|
|
+ message.bound_inputs.push(reader.int32());
|
|
|
+ break;
|
|
|
+ case "canonicalized_input_signature":
|
|
|
+ message.canonicalized_input_signature = $root.tensorflow.StructuredValue.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ case "output_signature":
|
|
|
+ message.output_signature = $root.tensorflow.StructuredValue.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedConcreteFunction.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ if (message.bound_inputs != null && message.hasOwnProperty("bound_inputs")) {
|
|
|
+ if (!Array.isArray(message.bound_inputs))
|
|
|
+ return "bound_inputs: array expected";
|
|
|
+ for (var i = 0; i < message.bound_inputs.length; ++i)
|
|
|
+ if (!$util.isInteger(message.bound_inputs[i]))
|
|
|
+ return "bound_inputs: integer[] expected";
|
|
|
+ }
|
|
|
+ if (message.canonicalized_input_signature != null && message.hasOwnProperty("canonicalized_input_signature")) {
|
|
|
+ var error = $root.tensorflow.StructuredValue.verify(message.canonicalized_input_signature);
|
|
|
+ if (error)
|
|
|
+ return "canonicalized_input_signature." + error;
|
|
|
+ }
|
|
|
+ if (message.output_signature != null && message.hasOwnProperty("output_signature")) {
|
|
|
+ var error = $root.tensorflow.StructuredValue.verify(message.output_signature);
|
|
|
+ if (error)
|
|
|
+ return "output_signature." + error;
|
|
|
+ }
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedConcreteFunction.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.SavedConcreteFunction)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.SavedConcreteFunction();
|
|
|
+ if (object.bound_inputs) {
|
|
|
+ if (!Array.isArray(object.bound_inputs))
|
|
|
+ throw TypeError(".tensorflow.SavedConcreteFunction.bound_inputs: array expected");
|
|
|
+ message.bound_inputs = [];
|
|
|
+ for (var i = 0; i < object.bound_inputs.length; ++i)
|
|
|
+ message.bound_inputs[i] = object.bound_inputs[i] | 0;
|
|
|
+ }
|
|
|
+ if (object.canonicalized_input_signature != null) {
|
|
|
+ if (typeof object.canonicalized_input_signature !== "object")
|
|
|
+ throw TypeError(".tensorflow.SavedConcreteFunction.canonicalized_input_signature: object expected");
|
|
|
+ message.canonicalized_input_signature = $root.tensorflow.StructuredValue.fromObject(object.canonicalized_input_signature);
|
|
|
+ }
|
|
|
+ if (object.output_signature != null) {
|
|
|
+ if (typeof object.output_signature !== "object")
|
|
|
+ throw TypeError(".tensorflow.SavedConcreteFunction.output_signature: object expected");
|
|
|
+ message.output_signature = $root.tensorflow.StructuredValue.fromObject(object.output_signature);
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedConcreteFunction.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.arrays || options.defaults)
|
|
|
+ object.bound_inputs = [];
|
|
|
+ if (options.defaults) {
|
|
|
+ object.canonicalized_input_signature = null;
|
|
|
+ object.output_signature = null;
|
|
|
+ }
|
|
|
+ if (message.bound_inputs && message.bound_inputs.length) {
|
|
|
+ object.bound_inputs = [];
|
|
|
+ for (var j = 0; j < message.bound_inputs.length; ++j)
|
|
|
+ object.bound_inputs[j] = message.bound_inputs[j];
|
|
|
+ }
|
|
|
+ if (message.canonicalized_input_signature != null && message.hasOwnProperty("canonicalized_input_signature"))
|
|
|
+ object.canonicalized_input_signature = $root.tensorflow.StructuredValue.toObject(message.canonicalized_input_signature, options);
|
|
|
+ if (message.output_signature != null && message.hasOwnProperty("output_signature"))
|
|
|
+ object.output_signature = $root.tensorflow.StructuredValue.toObject(message.output_signature, options);
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedConcreteFunction.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return SavedConcreteFunction;
|
|
|
+ })();
|
|
|
+
|
|
|
+ tensorflow.SavedBareConcreteFunction = (function() {
|
|
|
+
|
|
|
+ function SavedBareConcreteFunction(properties) {
|
|
|
+ this.argument_keywords = [];
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ SavedBareConcreteFunction.prototype.concrete_function_name = "";
|
|
|
+ SavedBareConcreteFunction.prototype.argument_keywords = $util.emptyArray;
|
|
|
+ SavedBareConcreteFunction.prototype.allowed_positional_arguments = $util.Long ? $util.Long.fromBits(0,0,false) : 0;
|
|
|
+
|
|
|
+ SavedBareConcreteFunction.create = function create(properties) {
|
|
|
+ return new SavedBareConcreteFunction(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedBareConcreteFunction.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.SavedBareConcreteFunction();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ message.concrete_function_name = reader.string();
|
|
|
+ break;
|
|
|
+ case 2:
|
|
|
+ if (!(message.argument_keywords && message.argument_keywords.length))
|
|
|
+ message.argument_keywords = [];
|
|
|
+ message.argument_keywords.push(reader.string());
|
|
|
+ break;
|
|
|
+ case 3:
|
|
|
+ message.allowed_positional_arguments = reader.int64();
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedBareConcreteFunction.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.SavedBareConcreteFunction();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "concrete_function_name":
|
|
|
+ reader.value();
|
|
|
+ message.concrete_function_name = reader.string();
|
|
|
+ break;
|
|
|
+ case "argument_keywords":
|
|
|
+ if (!(message.argument_keywords && message.argument_keywords.length))
|
|
|
+ message.argument_keywords = [];
|
|
|
+ reader.value();
|
|
|
+ if (reader.first())
|
|
|
+ while (!reader.last()) {
|
|
|
+ message.argument_keywords.push(reader.string());
|
|
|
+ reader.next();
|
|
|
+ }
|
|
|
+ else
|
|
|
+ message.argument_keywords.push(reader.string());
|
|
|
+ break;
|
|
|
+ case "allowed_positional_arguments":
|
|
|
+ reader.value();
|
|
|
+ message.allowed_positional_arguments = reader.int64();
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedBareConcreteFunction.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ if (message.concrete_function_name != null && message.hasOwnProperty("concrete_function_name"))
|
|
|
+ if (!$util.isString(message.concrete_function_name))
|
|
|
+ return "concrete_function_name: string expected";
|
|
|
+ if (message.argument_keywords != null && message.hasOwnProperty("argument_keywords")) {
|
|
|
+ if (!Array.isArray(message.argument_keywords))
|
|
|
+ return "argument_keywords: array expected";
|
|
|
+ for (var i = 0; i < message.argument_keywords.length; ++i)
|
|
|
+ if (!$util.isString(message.argument_keywords[i]))
|
|
|
+ return "argument_keywords: string[] expected";
|
|
|
+ }
|
|
|
+ if (message.allowed_positional_arguments != null && message.hasOwnProperty("allowed_positional_arguments"))
|
|
|
+ if (!$util.isInteger(message.allowed_positional_arguments) && !(message.allowed_positional_arguments && $util.isInteger(message.allowed_positional_arguments.low) && $util.isInteger(message.allowed_positional_arguments.high)))
|
|
|
+ return "allowed_positional_arguments: integer|Long expected";
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedBareConcreteFunction.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.SavedBareConcreteFunction)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.SavedBareConcreteFunction();
|
|
|
+ if (object.concrete_function_name != null)
|
|
|
+ message.concrete_function_name = String(object.concrete_function_name);
|
|
|
+ if (object.argument_keywords) {
|
|
|
+ if (!Array.isArray(object.argument_keywords))
|
|
|
+ throw TypeError(".tensorflow.SavedBareConcreteFunction.argument_keywords: array expected");
|
|
|
+ message.argument_keywords = [];
|
|
|
+ for (var i = 0; i < object.argument_keywords.length; ++i)
|
|
|
+ message.argument_keywords[i] = String(object.argument_keywords[i]);
|
|
|
+ }
|
|
|
+ if (object.allowed_positional_arguments != null)
|
|
|
+ if ($util.Long)
|
|
|
+ (message.allowed_positional_arguments = $util.Long.fromValue(object.allowed_positional_arguments)).unsigned = false;
|
|
|
+ else if (typeof object.allowed_positional_arguments === "string")
|
|
|
+ message.allowed_positional_arguments = parseInt(object.allowed_positional_arguments, 10);
|
|
|
+ else if (typeof object.allowed_positional_arguments === "number")
|
|
|
+ message.allowed_positional_arguments = object.allowed_positional_arguments;
|
|
|
+ else if (typeof object.allowed_positional_arguments === "object")
|
|
|
+ message.allowed_positional_arguments = new $util.LongBits(object.allowed_positional_arguments.low >>> 0, object.allowed_positional_arguments.high >>> 0).toNumber();
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedBareConcreteFunction.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.arrays || options.defaults)
|
|
|
+ object.argument_keywords = [];
|
|
|
+ if (options.defaults) {
|
|
|
+ object.concrete_function_name = "";
|
|
|
+ if ($util.Long) {
|
|
|
+ var long = new $util.Long(0, 0, false);
|
|
|
+ object.allowed_positional_arguments = options.longs === String ? long.toString() : options.longs === Number ? long.toNumber() : long;
|
|
|
+ } else
|
|
|
+ object.allowed_positional_arguments = options.longs === String ? "0" : 0;
|
|
|
+ }
|
|
|
+ if (message.concrete_function_name != null && message.hasOwnProperty("concrete_function_name"))
|
|
|
+ object.concrete_function_name = message.concrete_function_name;
|
|
|
+ if (message.argument_keywords && message.argument_keywords.length) {
|
|
|
+ object.argument_keywords = [];
|
|
|
+ for (var j = 0; j < message.argument_keywords.length; ++j)
|
|
|
+ object.argument_keywords[j] = message.argument_keywords[j];
|
|
|
+ }
|
|
|
+ if (message.allowed_positional_arguments != null && message.hasOwnProperty("allowed_positional_arguments"))
|
|
|
+ if (typeof message.allowed_positional_arguments === "number")
|
|
|
+ object.allowed_positional_arguments = options.longs === String ? String(message.allowed_positional_arguments) : message.allowed_positional_arguments;
|
|
|
+ else
|
|
|
+ object.allowed_positional_arguments = options.longs === String ? $util.Long.prototype.toString.call(message.allowed_positional_arguments) : options.longs === Number ? new $util.LongBits(message.allowed_positional_arguments.low >>> 0, message.allowed_positional_arguments.high >>> 0).toNumber() : message.allowed_positional_arguments;
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedBareConcreteFunction.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return SavedBareConcreteFunction;
|
|
|
+ })();
|
|
|
+
|
|
|
+ tensorflow.SavedConstant = (function() {
|
|
|
+
|
|
|
+ function SavedConstant(properties) {
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ SavedConstant.prototype.operation = "";
|
|
|
+
|
|
|
+ SavedConstant.create = function create(properties) {
|
|
|
+ return new SavedConstant(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedConstant.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.SavedConstant();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ message.operation = reader.string();
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedConstant.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.SavedConstant();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "operation":
|
|
|
+ reader.value();
|
|
|
+ message.operation = reader.string();
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedConstant.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ if (message.operation != null && message.hasOwnProperty("operation"))
|
|
|
+ if (!$util.isString(message.operation))
|
|
|
+ return "operation: string expected";
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedConstant.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.SavedConstant)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.SavedConstant();
|
|
|
+ if (object.operation != null)
|
|
|
+ message.operation = String(object.operation);
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedConstant.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.defaults)
|
|
|
+ object.operation = "";
|
|
|
+ if (message.operation != null && message.hasOwnProperty("operation"))
|
|
|
+ object.operation = message.operation;
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedConstant.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return SavedConstant;
|
|
|
+ })();
|
|
|
+
|
|
|
+ tensorflow.SavedVariable = (function() {
|
|
|
+
|
|
|
+ function SavedVariable(properties) {
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ SavedVariable.prototype.dtype = 0;
|
|
|
+ SavedVariable.prototype.shape = null;
|
|
|
+ SavedVariable.prototype.trainable = false;
|
|
|
+
|
|
|
+ SavedVariable.create = function create(properties) {
|
|
|
+ return new SavedVariable(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedVariable.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.SavedVariable();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ message.dtype = reader.int32();
|
|
|
+ break;
|
|
|
+ case 2:
|
|
|
+ message.shape = $root.tensorflow.TensorShapeProto.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ case 3:
|
|
|
+ message.trainable = reader.bool();
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedVariable.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.SavedVariable();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "dtype":
|
|
|
+ reader.value();
|
|
|
+ message.dtype = reader.enum($root.tensorflow.DataType);
|
|
|
+ break;
|
|
|
+ case "shape":
|
|
|
+ message.shape = $root.tensorflow.TensorShapeProto.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ case "trainable":
|
|
|
+ reader.value();
|
|
|
+ message.trainable = reader.bool();
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedVariable.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ if (message.dtype != null && message.hasOwnProperty("dtype"))
|
|
|
+ switch (message.dtype) {
|
|
|
+ default:
|
|
|
+ return "dtype: enum value expected";
|
|
|
+ case 0:
|
|
|
+ case 1:
|
|
|
+ case 2:
|
|
|
+ case 3:
|
|
|
+ case 4:
|
|
|
+ case 5:
|
|
|
+ case 6:
|
|
|
+ case 7:
|
|
|
+ case 8:
|
|
|
+ case 9:
|
|
|
+ case 10:
|
|
|
+ case 11:
|
|
|
+ case 12:
|
|
|
+ case 13:
|
|
|
+ case 14:
|
|
|
+ case 15:
|
|
|
+ case 16:
|
|
|
+ case 17:
|
|
|
+ case 18:
|
|
|
+ case 19:
|
|
|
+ case 20:
|
|
|
+ case 21:
|
|
|
+ case 22:
|
|
|
+ case 23:
|
|
|
+ case 101:
|
|
|
+ case 102:
|
|
|
+ case 103:
|
|
|
+ case 104:
|
|
|
+ case 105:
|
|
|
+ case 106:
|
|
|
+ case 107:
|
|
|
+ case 108:
|
|
|
+ case 109:
|
|
|
+ case 110:
|
|
|
+ case 111:
|
|
|
+ case 112:
|
|
|
+ case 113:
|
|
|
+ case 114:
|
|
|
+ case 115:
|
|
|
+ case 116:
|
|
|
+ case 117:
|
|
|
+ case 118:
|
|
|
+ case 119:
|
|
|
+ case 120:
|
|
|
+ case 121:
|
|
|
+ case 122:
|
|
|
+ case 123:
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ if (message.shape != null && message.hasOwnProperty("shape")) {
|
|
|
+ var error = $root.tensorflow.TensorShapeProto.verify(message.shape);
|
|
|
+ if (error)
|
|
|
+ return "shape." + error;
|
|
|
+ }
|
|
|
+ if (message.trainable != null && message.hasOwnProperty("trainable"))
|
|
|
+ if (typeof message.trainable !== "boolean")
|
|
|
+ return "trainable: boolean expected";
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedVariable.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.SavedVariable)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.SavedVariable();
|
|
|
+ switch (object.dtype) {
|
|
|
+ case "DT_INVALID":
|
|
|
+ case 0:
|
|
|
+ message.dtype = 0;
|
|
|
+ break;
|
|
|
+ case "DT_FLOAT":
|
|
|
+ case 1:
|
|
|
+ message.dtype = 1;
|
|
|
+ break;
|
|
|
+ case "DT_DOUBLE":
|
|
|
+ case 2:
|
|
|
+ message.dtype = 2;
|
|
|
+ break;
|
|
|
+ case "DT_INT32":
|
|
|
+ case 3:
|
|
|
+ message.dtype = 3;
|
|
|
+ break;
|
|
|
+ case "DT_UINT8":
|
|
|
+ case 4:
|
|
|
+ message.dtype = 4;
|
|
|
+ break;
|
|
|
+ case "DT_INT16":
|
|
|
+ case 5:
|
|
|
+ message.dtype = 5;
|
|
|
+ break;
|
|
|
+ case "DT_INT8":
|
|
|
+ case 6:
|
|
|
+ message.dtype = 6;
|
|
|
+ break;
|
|
|
+ case "DT_STRING":
|
|
|
+ case 7:
|
|
|
+ message.dtype = 7;
|
|
|
+ break;
|
|
|
+ case "DT_COMPLEX64":
|
|
|
+ case 8:
|
|
|
+ message.dtype = 8;
|
|
|
+ break;
|
|
|
+ case "DT_INT64":
|
|
|
+ case 9:
|
|
|
+ message.dtype = 9;
|
|
|
+ break;
|
|
|
+ case "DT_BOOL":
|
|
|
+ case 10:
|
|
|
+ message.dtype = 10;
|
|
|
+ break;
|
|
|
+ case "DT_QINT8":
|
|
|
+ case 11:
|
|
|
+ message.dtype = 11;
|
|
|
+ break;
|
|
|
+ case "DT_QUINT8":
|
|
|
+ case 12:
|
|
|
+ message.dtype = 12;
|
|
|
+ break;
|
|
|
+ case "DT_QINT32":
|
|
|
+ case 13:
|
|
|
+ message.dtype = 13;
|
|
|
+ break;
|
|
|
+ case "DT_BFLOAT16":
|
|
|
+ case 14:
|
|
|
+ message.dtype = 14;
|
|
|
+ break;
|
|
|
+ case "DT_QINT16":
|
|
|
+ case 15:
|
|
|
+ message.dtype = 15;
|
|
|
+ break;
|
|
|
+ case "DT_QUINT16":
|
|
|
+ case 16:
|
|
|
+ message.dtype = 16;
|
|
|
+ break;
|
|
|
+ case "DT_UINT16":
|
|
|
+ case 17:
|
|
|
+ message.dtype = 17;
|
|
|
+ break;
|
|
|
+ case "DT_COMPLEX128":
|
|
|
+ case 18:
|
|
|
+ message.dtype = 18;
|
|
|
+ break;
|
|
|
+ case "DT_HALF":
|
|
|
+ case 19:
|
|
|
+ message.dtype = 19;
|
|
|
+ break;
|
|
|
+ case "DT_RESOURCE":
|
|
|
+ case 20:
|
|
|
+ message.dtype = 20;
|
|
|
+ break;
|
|
|
+ case "DT_VARIANT":
|
|
|
+ case 21:
|
|
|
+ message.dtype = 21;
|
|
|
+ break;
|
|
|
+ case "DT_UINT32":
|
|
|
+ case 22:
|
|
|
+ message.dtype = 22;
|
|
|
+ break;
|
|
|
+ case "DT_UINT64":
|
|
|
+ case 23:
|
|
|
+ message.dtype = 23;
|
|
|
+ break;
|
|
|
+ case "DT_FLOAT_REF":
|
|
|
+ case 101:
|
|
|
+ message.dtype = 101;
|
|
|
+ break;
|
|
|
+ case "DT_DOUBLE_REF":
|
|
|
+ case 102:
|
|
|
+ message.dtype = 102;
|
|
|
+ break;
|
|
|
+ case "DT_INT32_REF":
|
|
|
+ case 103:
|
|
|
+ message.dtype = 103;
|
|
|
+ break;
|
|
|
+ case "DT_UINT8_REF":
|
|
|
+ case 104:
|
|
|
+ message.dtype = 104;
|
|
|
+ break;
|
|
|
+ case "DT_INT16_REF":
|
|
|
+ case 105:
|
|
|
+ message.dtype = 105;
|
|
|
+ break;
|
|
|
+ case "DT_INT8_REF":
|
|
|
+ case 106:
|
|
|
+ message.dtype = 106;
|
|
|
+ break;
|
|
|
+ case "DT_STRING_REF":
|
|
|
+ case 107:
|
|
|
+ message.dtype = 107;
|
|
|
+ break;
|
|
|
+ case "DT_COMPLEX64_REF":
|
|
|
+ case 108:
|
|
|
+ message.dtype = 108;
|
|
|
+ break;
|
|
|
+ case "DT_INT64_REF":
|
|
|
+ case 109:
|
|
|
+ message.dtype = 109;
|
|
|
+ break;
|
|
|
+ case "DT_BOOL_REF":
|
|
|
+ case 110:
|
|
|
+ message.dtype = 110;
|
|
|
+ break;
|
|
|
+ case "DT_QINT8_REF":
|
|
|
+ case 111:
|
|
|
+ message.dtype = 111;
|
|
|
+ break;
|
|
|
+ case "DT_QUINT8_REF":
|
|
|
+ case 112:
|
|
|
+ message.dtype = 112;
|
|
|
+ break;
|
|
|
+ case "DT_QINT32_REF":
|
|
|
+ case 113:
|
|
|
+ message.dtype = 113;
|
|
|
+ break;
|
|
|
+ case "DT_BFLOAT16_REF":
|
|
|
+ case 114:
|
|
|
+ message.dtype = 114;
|
|
|
+ break;
|
|
|
+ case "DT_QINT16_REF":
|
|
|
+ case 115:
|
|
|
+ message.dtype = 115;
|
|
|
+ break;
|
|
|
+ case "DT_QUINT16_REF":
|
|
|
+ case 116:
|
|
|
+ message.dtype = 116;
|
|
|
+ break;
|
|
|
+ case "DT_UINT16_REF":
|
|
|
+ case 117:
|
|
|
+ message.dtype = 117;
|
|
|
+ break;
|
|
|
+ case "DT_COMPLEX128_REF":
|
|
|
+ case 118:
|
|
|
+ message.dtype = 118;
|
|
|
+ break;
|
|
|
+ case "DT_HALF_REF":
|
|
|
+ case 119:
|
|
|
+ message.dtype = 119;
|
|
|
+ break;
|
|
|
+ case "DT_RESOURCE_REF":
|
|
|
+ case 120:
|
|
|
+ message.dtype = 120;
|
|
|
+ break;
|
|
|
+ case "DT_VARIANT_REF":
|
|
|
+ case 121:
|
|
|
+ message.dtype = 121;
|
|
|
+ break;
|
|
|
+ case "DT_UINT32_REF":
|
|
|
+ case 122:
|
|
|
+ message.dtype = 122;
|
|
|
+ break;
|
|
|
+ case "DT_UINT64_REF":
|
|
|
+ case 123:
|
|
|
+ message.dtype = 123;
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ if (object.shape != null) {
|
|
|
+ if (typeof object.shape !== "object")
|
|
|
+ throw TypeError(".tensorflow.SavedVariable.shape: object expected");
|
|
|
+ message.shape = $root.tensorflow.TensorShapeProto.fromObject(object.shape);
|
|
|
+ }
|
|
|
+ if (object.trainable != null)
|
|
|
+ message.trainable = Boolean(object.trainable);
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedVariable.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.defaults) {
|
|
|
+ object.dtype = options.enums === String ? "DT_INVALID" : 0;
|
|
|
+ object.shape = null;
|
|
|
+ object.trainable = false;
|
|
|
+ }
|
|
|
+ if (message.dtype != null && message.hasOwnProperty("dtype"))
|
|
|
+ object.dtype = options.enums === String ? $root.tensorflow.DataType[message.dtype] : message.dtype;
|
|
|
+ if (message.shape != null && message.hasOwnProperty("shape"))
|
|
|
+ object.shape = $root.tensorflow.TensorShapeProto.toObject(message.shape, options);
|
|
|
+ if (message.trainable != null && message.hasOwnProperty("trainable"))
|
|
|
+ object.trainable = message.trainable;
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedVariable.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return SavedVariable;
|
|
|
+ })();
|
|
|
+
|
|
|
+ tensorflow.FunctionSpec = (function() {
|
|
|
+
|
|
|
+ function FunctionSpec(properties) {
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ FunctionSpec.prototype.fullargspec = null;
|
|
|
+ FunctionSpec.prototype.is_method = false;
|
|
|
+ FunctionSpec.prototype.args_to_prepend = null;
|
|
|
+ FunctionSpec.prototype.kwargs_to_include = null;
|
|
|
+ FunctionSpec.prototype.input_signature = null;
|
|
|
+
|
|
|
+ FunctionSpec.create = function create(properties) {
|
|
|
+ return new FunctionSpec(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ FunctionSpec.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.FunctionSpec();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ message.fullargspec = $root.tensorflow.StructuredValue.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ case 2:
|
|
|
+ message.is_method = reader.bool();
|
|
|
+ break;
|
|
|
+ case 3:
|
|
|
+ message.args_to_prepend = $root.tensorflow.StructuredValue.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ case 4:
|
|
|
+ message.kwargs_to_include = $root.tensorflow.StructuredValue.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ case 5:
|
|
|
+ message.input_signature = $root.tensorflow.StructuredValue.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ FunctionSpec.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.FunctionSpec();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "fullargspec":
|
|
|
+ message.fullargspec = $root.tensorflow.StructuredValue.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ case "is_method":
|
|
|
+ reader.value();
|
|
|
+ message.is_method = reader.bool();
|
|
|
+ break;
|
|
|
+ case "args_to_prepend":
|
|
|
+ message.args_to_prepend = $root.tensorflow.StructuredValue.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ case "kwargs_to_include":
|
|
|
+ message.kwargs_to_include = $root.tensorflow.StructuredValue.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ case "input_signature":
|
|
|
+ message.input_signature = $root.tensorflow.StructuredValue.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ FunctionSpec.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ if (message.fullargspec != null && message.hasOwnProperty("fullargspec")) {
|
|
|
+ var error = $root.tensorflow.StructuredValue.verify(message.fullargspec);
|
|
|
+ if (error)
|
|
|
+ return "fullargspec." + error;
|
|
|
+ }
|
|
|
+ if (message.is_method != null && message.hasOwnProperty("is_method"))
|
|
|
+ if (typeof message.is_method !== "boolean")
|
|
|
+ return "is_method: boolean expected";
|
|
|
+ if (message.args_to_prepend != null && message.hasOwnProperty("args_to_prepend")) {
|
|
|
+ var error = $root.tensorflow.StructuredValue.verify(message.args_to_prepend);
|
|
|
+ if (error)
|
|
|
+ return "args_to_prepend." + error;
|
|
|
+ }
|
|
|
+ if (message.kwargs_to_include != null && message.hasOwnProperty("kwargs_to_include")) {
|
|
|
+ var error = $root.tensorflow.StructuredValue.verify(message.kwargs_to_include);
|
|
|
+ if (error)
|
|
|
+ return "kwargs_to_include." + error;
|
|
|
+ }
|
|
|
+ if (message.input_signature != null && message.hasOwnProperty("input_signature")) {
|
|
|
+ var error = $root.tensorflow.StructuredValue.verify(message.input_signature);
|
|
|
+ if (error)
|
|
|
+ return "input_signature." + error;
|
|
|
+ }
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ FunctionSpec.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.FunctionSpec)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.FunctionSpec();
|
|
|
+ if (object.fullargspec != null) {
|
|
|
+ if (typeof object.fullargspec !== "object")
|
|
|
+ throw TypeError(".tensorflow.FunctionSpec.fullargspec: object expected");
|
|
|
+ message.fullargspec = $root.tensorflow.StructuredValue.fromObject(object.fullargspec);
|
|
|
+ }
|
|
|
+ if (object.is_method != null)
|
|
|
+ message.is_method = Boolean(object.is_method);
|
|
|
+ if (object.args_to_prepend != null) {
|
|
|
+ if (typeof object.args_to_prepend !== "object")
|
|
|
+ throw TypeError(".tensorflow.FunctionSpec.args_to_prepend: object expected");
|
|
|
+ message.args_to_prepend = $root.tensorflow.StructuredValue.fromObject(object.args_to_prepend);
|
|
|
+ }
|
|
|
+ if (object.kwargs_to_include != null) {
|
|
|
+ if (typeof object.kwargs_to_include !== "object")
|
|
|
+ throw TypeError(".tensorflow.FunctionSpec.kwargs_to_include: object expected");
|
|
|
+ message.kwargs_to_include = $root.tensorflow.StructuredValue.fromObject(object.kwargs_to_include);
|
|
|
+ }
|
|
|
+ if (object.input_signature != null) {
|
|
|
+ if (typeof object.input_signature !== "object")
|
|
|
+ throw TypeError(".tensorflow.FunctionSpec.input_signature: object expected");
|
|
|
+ message.input_signature = $root.tensorflow.StructuredValue.fromObject(object.input_signature);
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ FunctionSpec.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.defaults) {
|
|
|
+ object.fullargspec = null;
|
|
|
+ object.is_method = false;
|
|
|
+ object.args_to_prepend = null;
|
|
|
+ object.kwargs_to_include = null;
|
|
|
+ object.input_signature = null;
|
|
|
+ }
|
|
|
+ if (message.fullargspec != null && message.hasOwnProperty("fullargspec"))
|
|
|
+ object.fullargspec = $root.tensorflow.StructuredValue.toObject(message.fullargspec, options);
|
|
|
+ if (message.is_method != null && message.hasOwnProperty("is_method"))
|
|
|
+ object.is_method = message.is_method;
|
|
|
+ if (message.args_to_prepend != null && message.hasOwnProperty("args_to_prepend"))
|
|
|
+ object.args_to_prepend = $root.tensorflow.StructuredValue.toObject(message.args_to_prepend, options);
|
|
|
+ if (message.kwargs_to_include != null && message.hasOwnProperty("kwargs_to_include"))
|
|
|
+ object.kwargs_to_include = $root.tensorflow.StructuredValue.toObject(message.kwargs_to_include, options);
|
|
|
+ if (message.input_signature != null && message.hasOwnProperty("input_signature"))
|
|
|
+ object.input_signature = $root.tensorflow.StructuredValue.toObject(message.input_signature, options);
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ FunctionSpec.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return FunctionSpec;
|
|
|
+ })();
|
|
|
+
|
|
|
+ tensorflow.SavedResource = (function() {
|
|
|
+
|
|
|
+ function SavedResource(properties) {
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ SavedResource.create = function create(properties) {
|
|
|
+ return new SavedResource(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedResource.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.SavedResource();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedResource.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.SavedResource();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedResource.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedResource.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.SavedResource)
|
|
|
+ return object;
|
|
|
+ return new $root.tensorflow.SavedResource();
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedResource.toObject = function toObject() {
|
|
|
+ return {};
|
|
|
+ };
|
|
|
+
|
|
|
+ SavedResource.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return SavedResource;
|
|
|
+ })();
|
|
|
+
|
|
|
+ tensorflow.TrackableObjectGraph = (function() {
|
|
|
+
|
|
|
+ function TrackableObjectGraph(properties) {
|
|
|
+ this.nodes = [];
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ TrackableObjectGraph.prototype.nodes = $util.emptyArray;
|
|
|
+
|
|
|
+ TrackableObjectGraph.create = function create(properties) {
|
|
|
+ return new TrackableObjectGraph(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ TrackableObjectGraph.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.TrackableObjectGraph();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ if (!(message.nodes && message.nodes.length))
|
|
|
+ message.nodes = [];
|
|
|
+ message.nodes.push($root.tensorflow.TrackableObjectGraph.TrackableObject.decode(reader, reader.uint32()));
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ TrackableObjectGraph.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.TrackableObjectGraph();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "nodes":
|
|
|
+ if (!(message.nodes && message.nodes.length))
|
|
|
+ message.nodes = [];
|
|
|
+ message.nodes.push($root.tensorflow.TrackableObjectGraph.TrackableObject.decodeText(reader, true));
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ TrackableObjectGraph.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ if (message.nodes != null && message.hasOwnProperty("nodes")) {
|
|
|
+ if (!Array.isArray(message.nodes))
|
|
|
+ return "nodes: array expected";
|
|
|
+ for (var i = 0; i < message.nodes.length; ++i) {
|
|
|
+ var error = $root.tensorflow.TrackableObjectGraph.TrackableObject.verify(message.nodes[i]);
|
|
|
+ if (error)
|
|
|
+ return "nodes." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ TrackableObjectGraph.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.TrackableObjectGraph)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.TrackableObjectGraph();
|
|
|
+ if (object.nodes) {
|
|
|
+ if (!Array.isArray(object.nodes))
|
|
|
+ throw TypeError(".tensorflow.TrackableObjectGraph.nodes: array expected");
|
|
|
+ message.nodes = [];
|
|
|
+ for (var i = 0; i < object.nodes.length; ++i) {
|
|
|
+ if (typeof object.nodes[i] !== "object")
|
|
|
+ throw TypeError(".tensorflow.TrackableObjectGraph.nodes: object expected");
|
|
|
+ message.nodes[i] = $root.tensorflow.TrackableObjectGraph.TrackableObject.fromObject(object.nodes[i]);
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ TrackableObjectGraph.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.arrays || options.defaults)
|
|
|
+ object.nodes = [];
|
|
|
+ if (message.nodes && message.nodes.length) {
|
|
|
+ object.nodes = [];
|
|
|
+ for (var j = 0; j < message.nodes.length; ++j)
|
|
|
+ object.nodes[j] = $root.tensorflow.TrackableObjectGraph.TrackableObject.toObject(message.nodes[j], options);
|
|
|
+ }
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ TrackableObjectGraph.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ TrackableObjectGraph.TrackableObject = (function() {
|
|
|
+
|
|
|
+ function TrackableObject(properties) {
|
|
|
+ this.children = [];
|
|
|
+ this.attributes = [];
|
|
|
+ this.slot_variables = [];
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ TrackableObject.prototype.children = $util.emptyArray;
|
|
|
+ TrackableObject.prototype.attributes = $util.emptyArray;
|
|
|
+ TrackableObject.prototype.slot_variables = $util.emptyArray;
|
|
|
+
|
|
|
+ TrackableObject.create = function create(properties) {
|
|
|
+ return new TrackableObject(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ TrackableObject.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.TrackableObjectGraph.TrackableObject();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ if (!(message.children && message.children.length))
|
|
|
+ message.children = [];
|
|
|
+ message.children.push($root.tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference.decode(reader, reader.uint32()));
|
|
|
+ break;
|
|
|
+ case 2:
|
|
|
+ if (!(message.attributes && message.attributes.length))
|
|
|
+ message.attributes = [];
|
|
|
+ message.attributes.push($root.tensorflow.TrackableObjectGraph.TrackableObject.SerializedTensor.decode(reader, reader.uint32()));
|
|
|
+ break;
|
|
|
+ case 3:
|
|
|
+ if (!(message.slot_variables && message.slot_variables.length))
|
|
|
+ message.slot_variables = [];
|
|
|
+ message.slot_variables.push($root.tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference.decode(reader, reader.uint32()));
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ TrackableObject.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.TrackableObjectGraph.TrackableObject();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "children":
|
|
|
+ if (!(message.children && message.children.length))
|
|
|
+ message.children = [];
|
|
|
+ message.children.push($root.tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference.decodeText(reader, true));
|
|
|
+ break;
|
|
|
+ case "attributes":
|
|
|
+ if (!(message.attributes && message.attributes.length))
|
|
|
+ message.attributes = [];
|
|
|
+ message.attributes.push($root.tensorflow.TrackableObjectGraph.TrackableObject.SerializedTensor.decodeText(reader, true));
|
|
|
+ break;
|
|
|
+ case "slot_variables":
|
|
|
+ if (!(message.slot_variables && message.slot_variables.length))
|
|
|
+ message.slot_variables = [];
|
|
|
+ message.slot_variables.push($root.tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference.decodeText(reader, true));
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ TrackableObject.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ if (message.children != null && message.hasOwnProperty("children")) {
|
|
|
+ if (!Array.isArray(message.children))
|
|
|
+ return "children: array expected";
|
|
|
+ for (var i = 0; i < message.children.length; ++i) {
|
|
|
+ var error = $root.tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference.verify(message.children[i]);
|
|
|
+ if (error)
|
|
|
+ return "children." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (message.attributes != null && message.hasOwnProperty("attributes")) {
|
|
|
+ if (!Array.isArray(message.attributes))
|
|
|
+ return "attributes: array expected";
|
|
|
+ for (var i = 0; i < message.attributes.length; ++i) {
|
|
|
+ var error = $root.tensorflow.TrackableObjectGraph.TrackableObject.SerializedTensor.verify(message.attributes[i]);
|
|
|
+ if (error)
|
|
|
+ return "attributes." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (message.slot_variables != null && message.hasOwnProperty("slot_variables")) {
|
|
|
+ if (!Array.isArray(message.slot_variables))
|
|
|
+ return "slot_variables: array expected";
|
|
|
+ for (var i = 0; i < message.slot_variables.length; ++i) {
|
|
|
+ var error = $root.tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference.verify(message.slot_variables[i]);
|
|
|
+ if (error)
|
|
|
+ return "slot_variables." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ TrackableObject.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.TrackableObjectGraph.TrackableObject)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.TrackableObjectGraph.TrackableObject();
|
|
|
+ if (object.children) {
|
|
|
+ if (!Array.isArray(object.children))
|
|
|
+ throw TypeError(".tensorflow.TrackableObjectGraph.TrackableObject.children: array expected");
|
|
|
+ message.children = [];
|
|
|
+ for (var i = 0; i < object.children.length; ++i) {
|
|
|
+ if (typeof object.children[i] !== "object")
|
|
|
+ throw TypeError(".tensorflow.TrackableObjectGraph.TrackableObject.children: object expected");
|
|
|
+ message.children[i] = $root.tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference.fromObject(object.children[i]);
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (object.attributes) {
|
|
|
+ if (!Array.isArray(object.attributes))
|
|
|
+ throw TypeError(".tensorflow.TrackableObjectGraph.TrackableObject.attributes: array expected");
|
|
|
+ message.attributes = [];
|
|
|
+ for (var i = 0; i < object.attributes.length; ++i) {
|
|
|
+ if (typeof object.attributes[i] !== "object")
|
|
|
+ throw TypeError(".tensorflow.TrackableObjectGraph.TrackableObject.attributes: object expected");
|
|
|
+ message.attributes[i] = $root.tensorflow.TrackableObjectGraph.TrackableObject.SerializedTensor.fromObject(object.attributes[i]);
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (object.slot_variables) {
|
|
|
+ if (!Array.isArray(object.slot_variables))
|
|
|
+ throw TypeError(".tensorflow.TrackableObjectGraph.TrackableObject.slot_variables: array expected");
|
|
|
+ message.slot_variables = [];
|
|
|
+ for (var i = 0; i < object.slot_variables.length; ++i) {
|
|
|
+ if (typeof object.slot_variables[i] !== "object")
|
|
|
+ throw TypeError(".tensorflow.TrackableObjectGraph.TrackableObject.slot_variables: object expected");
|
|
|
+ message.slot_variables[i] = $root.tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference.fromObject(object.slot_variables[i]);
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ TrackableObject.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.arrays || options.defaults) {
|
|
|
+ object.children = [];
|
|
|
+ object.attributes = [];
|
|
|
+ object.slot_variables = [];
|
|
|
+ }
|
|
|
+ if (message.children && message.children.length) {
|
|
|
+ object.children = [];
|
|
|
+ for (var j = 0; j < message.children.length; ++j)
|
|
|
+ object.children[j] = $root.tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference.toObject(message.children[j], options);
|
|
|
+ }
|
|
|
+ if (message.attributes && message.attributes.length) {
|
|
|
+ object.attributes = [];
|
|
|
+ for (var j = 0; j < message.attributes.length; ++j)
|
|
|
+ object.attributes[j] = $root.tensorflow.TrackableObjectGraph.TrackableObject.SerializedTensor.toObject(message.attributes[j], options);
|
|
|
+ }
|
|
|
+ if (message.slot_variables && message.slot_variables.length) {
|
|
|
+ object.slot_variables = [];
|
|
|
+ for (var j = 0; j < message.slot_variables.length; ++j)
|
|
|
+ object.slot_variables[j] = $root.tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference.toObject(message.slot_variables[j], options);
|
|
|
+ }
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ TrackableObject.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ TrackableObject.ObjectReference = (function() {
|
|
|
+
|
|
|
+ function ObjectReference(properties) {
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ ObjectReference.prototype.node_id = 0;
|
|
|
+ ObjectReference.prototype.local_name = "";
|
|
|
+
|
|
|
+ ObjectReference.create = function create(properties) {
|
|
|
+ return new ObjectReference(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ ObjectReference.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ message.node_id = reader.int32();
|
|
|
+ break;
|
|
|
+ case 2:
|
|
|
+ message.local_name = reader.string();
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ ObjectReference.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "node_id":
|
|
|
+ reader.value();
|
|
|
+ message.node_id = reader.int32();
|
|
|
+ break;
|
|
|
+ case "local_name":
|
|
|
+ reader.value();
|
|
|
+ message.local_name = reader.string();
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ ObjectReference.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ if (message.node_id != null && message.hasOwnProperty("node_id"))
|
|
|
+ if (!$util.isInteger(message.node_id))
|
|
|
+ return "node_id: integer expected";
|
|
|
+ if (message.local_name != null && message.hasOwnProperty("local_name"))
|
|
|
+ if (!$util.isString(message.local_name))
|
|
|
+ return "local_name: string expected";
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ ObjectReference.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.TrackableObjectGraph.TrackableObject.ObjectReference();
|
|
|
+ if (object.node_id != null)
|
|
|
+ message.node_id = object.node_id | 0;
|
|
|
+ if (object.local_name != null)
|
|
|
+ message.local_name = String(object.local_name);
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ ObjectReference.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.defaults) {
|
|
|
+ object.node_id = 0;
|
|
|
+ object.local_name = "";
|
|
|
+ }
|
|
|
+ if (message.node_id != null && message.hasOwnProperty("node_id"))
|
|
|
+ object.node_id = message.node_id;
|
|
|
+ if (message.local_name != null && message.hasOwnProperty("local_name"))
|
|
|
+ object.local_name = message.local_name;
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ ObjectReference.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return ObjectReference;
|
|
|
+ })();
|
|
|
+
|
|
|
+ TrackableObject.SerializedTensor = (function() {
|
|
|
+
|
|
|
+ function SerializedTensor(properties) {
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ SerializedTensor.prototype.name = "";
|
|
|
+ SerializedTensor.prototype.full_name = "";
|
|
|
+ SerializedTensor.prototype.checkpoint_key = "";
|
|
|
+ SerializedTensor.prototype.optional_restore = false;
|
|
|
+
|
|
|
+ SerializedTensor.create = function create(properties) {
|
|
|
+ return new SerializedTensor(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ SerializedTensor.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.TrackableObjectGraph.TrackableObject.SerializedTensor();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ message.name = reader.string();
|
|
|
+ break;
|
|
|
+ case 2:
|
|
|
+ message.full_name = reader.string();
|
|
|
+ break;
|
|
|
+ case 3:
|
|
|
+ message.checkpoint_key = reader.string();
|
|
|
+ break;
|
|
|
+ case 4:
|
|
|
+ message.optional_restore = reader.bool();
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SerializedTensor.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.TrackableObjectGraph.TrackableObject.SerializedTensor();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "name":
|
|
|
+ reader.value();
|
|
|
+ message.name = reader.string();
|
|
|
+ break;
|
|
|
+ case "full_name":
|
|
|
+ reader.value();
|
|
|
+ message.full_name = reader.string();
|
|
|
+ break;
|
|
|
+ case "checkpoint_key":
|
|
|
+ reader.value();
|
|
|
+ message.checkpoint_key = reader.string();
|
|
|
+ break;
|
|
|
+ case "optional_restore":
|
|
|
+ reader.value();
|
|
|
+ message.optional_restore = reader.bool();
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SerializedTensor.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ if (message.name != null && message.hasOwnProperty("name"))
|
|
|
+ if (!$util.isString(message.name))
|
|
|
+ return "name: string expected";
|
|
|
+ if (message.full_name != null && message.hasOwnProperty("full_name"))
|
|
|
+ if (!$util.isString(message.full_name))
|
|
|
+ return "full_name: string expected";
|
|
|
+ if (message.checkpoint_key != null && message.hasOwnProperty("checkpoint_key"))
|
|
|
+ if (!$util.isString(message.checkpoint_key))
|
|
|
+ return "checkpoint_key: string expected";
|
|
|
+ if (message.optional_restore != null && message.hasOwnProperty("optional_restore"))
|
|
|
+ if (typeof message.optional_restore !== "boolean")
|
|
|
+ return "optional_restore: boolean expected";
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ SerializedTensor.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.TrackableObjectGraph.TrackableObject.SerializedTensor)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.TrackableObjectGraph.TrackableObject.SerializedTensor();
|
|
|
+ if (object.name != null)
|
|
|
+ message.name = String(object.name);
|
|
|
+ if (object.full_name != null)
|
|
|
+ message.full_name = String(object.full_name);
|
|
|
+ if (object.checkpoint_key != null)
|
|
|
+ message.checkpoint_key = String(object.checkpoint_key);
|
|
|
+ if (object.optional_restore != null)
|
|
|
+ message.optional_restore = Boolean(object.optional_restore);
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SerializedTensor.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.defaults) {
|
|
|
+ object.name = "";
|
|
|
+ object.full_name = "";
|
|
|
+ object.checkpoint_key = "";
|
|
|
+ object.optional_restore = false;
|
|
|
+ }
|
|
|
+ if (message.name != null && message.hasOwnProperty("name"))
|
|
|
+ object.name = message.name;
|
|
|
+ if (message.full_name != null && message.hasOwnProperty("full_name"))
|
|
|
+ object.full_name = message.full_name;
|
|
|
+ if (message.checkpoint_key != null && message.hasOwnProperty("checkpoint_key"))
|
|
|
+ object.checkpoint_key = message.checkpoint_key;
|
|
|
+ if (message.optional_restore != null && message.hasOwnProperty("optional_restore"))
|
|
|
+ object.optional_restore = message.optional_restore;
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ SerializedTensor.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return SerializedTensor;
|
|
|
+ })();
|
|
|
+
|
|
|
+ TrackableObject.SlotVariableReference = (function() {
|
|
|
+
|
|
|
+ function SlotVariableReference(properties) {
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ SlotVariableReference.prototype.original_variable_node_id = 0;
|
|
|
+ SlotVariableReference.prototype.slot_name = "";
|
|
|
+ SlotVariableReference.prototype.slot_variable_node_id = 0;
|
|
|
+
|
|
|
+ SlotVariableReference.create = function create(properties) {
|
|
|
+ return new SlotVariableReference(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ SlotVariableReference.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ message.original_variable_node_id = reader.int32();
|
|
|
+ break;
|
|
|
+ case 2:
|
|
|
+ message.slot_name = reader.string();
|
|
|
+ break;
|
|
|
+ case 3:
|
|
|
+ message.slot_variable_node_id = reader.int32();
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SlotVariableReference.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "original_variable_node_id":
|
|
|
+ reader.value();
|
|
|
+ message.original_variable_node_id = reader.int32();
|
|
|
+ break;
|
|
|
+ case "slot_name":
|
|
|
+ reader.value();
|
|
|
+ message.slot_name = reader.string();
|
|
|
+ break;
|
|
|
+ case "slot_variable_node_id":
|
|
|
+ reader.value();
|
|
|
+ message.slot_variable_node_id = reader.int32();
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SlotVariableReference.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ if (message.original_variable_node_id != null && message.hasOwnProperty("original_variable_node_id"))
|
|
|
+ if (!$util.isInteger(message.original_variable_node_id))
|
|
|
+ return "original_variable_node_id: integer expected";
|
|
|
+ if (message.slot_name != null && message.hasOwnProperty("slot_name"))
|
|
|
+ if (!$util.isString(message.slot_name))
|
|
|
+ return "slot_name: string expected";
|
|
|
+ if (message.slot_variable_node_id != null && message.hasOwnProperty("slot_variable_node_id"))
|
|
|
+ if (!$util.isInteger(message.slot_variable_node_id))
|
|
|
+ return "slot_variable_node_id: integer expected";
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ SlotVariableReference.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference();
|
|
|
+ if (object.original_variable_node_id != null)
|
|
|
+ message.original_variable_node_id = object.original_variable_node_id | 0;
|
|
|
+ if (object.slot_name != null)
|
|
|
+ message.slot_name = String(object.slot_name);
|
|
|
+ if (object.slot_variable_node_id != null)
|
|
|
+ message.slot_variable_node_id = object.slot_variable_node_id | 0;
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ SlotVariableReference.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.defaults) {
|
|
|
+ object.original_variable_node_id = 0;
|
|
|
+ object.slot_name = "";
|
|
|
+ object.slot_variable_node_id = 0;
|
|
|
+ }
|
|
|
+ if (message.original_variable_node_id != null && message.hasOwnProperty("original_variable_node_id"))
|
|
|
+ object.original_variable_node_id = message.original_variable_node_id;
|
|
|
+ if (message.slot_name != null && message.hasOwnProperty("slot_name"))
|
|
|
+ object.slot_name = message.slot_name;
|
|
|
+ if (message.slot_variable_node_id != null && message.hasOwnProperty("slot_variable_node_id"))
|
|
|
+ object.slot_variable_node_id = message.slot_variable_node_id;
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ SlotVariableReference.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return SlotVariableReference;
|
|
|
+ })();
|
|
|
+
|
|
|
+ return TrackableObject;
|
|
|
+ })();
|
|
|
+
|
|
|
+ return TrackableObjectGraph;
|
|
|
+ })();
|
|
|
+
|
|
|
+ tensorflow.StructuredValue = (function() {
|
|
|
+
|
|
|
+ function StructuredValue(properties) {
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ StructuredValue.prototype.none_value = null;
|
|
|
+ StructuredValue.prototype.float64_value = 0;
|
|
|
+ StructuredValue.prototype.int64_value = $util.Long ? $util.Long.fromBits(0,0,false) : 0;
|
|
|
+ StructuredValue.prototype.string_value = "";
|
|
|
+ StructuredValue.prototype.bool_value = false;
|
|
|
+ StructuredValue.prototype.tensor_shape_value = null;
|
|
|
+ StructuredValue.prototype.tensor_dtype_value = 0;
|
|
|
+ StructuredValue.prototype.tensor_spec_value = null;
|
|
|
+ StructuredValue.prototype.list_value = null;
|
|
|
+ StructuredValue.prototype.tuple_value = null;
|
|
|
+ StructuredValue.prototype.dict_value = null;
|
|
|
+ StructuredValue.prototype.named_tuple_value = null;
|
|
|
+
|
|
|
+ var $oneOfFields;
|
|
|
+
|
|
|
+ Object.defineProperty(StructuredValue.prototype, "kind", {
|
|
|
+ get: $util.oneOfGetter($oneOfFields = ["none_value", "float64_value", "int64_value", "string_value", "bool_value", "tensor_shape_value", "tensor_dtype_value", "tensor_spec_value", "list_value", "tuple_value", "dict_value", "named_tuple_value"]),
|
|
|
+ set: $util.oneOfSetter($oneOfFields)
|
|
|
+ });
|
|
|
+
|
|
|
+ StructuredValue.create = function create(properties) {
|
|
|
+ return new StructuredValue(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ StructuredValue.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.StructuredValue();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ message.none_value = $root.tensorflow.NoneValue.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ case 11:
|
|
|
+ message.float64_value = reader.double();
|
|
|
+ break;
|
|
|
+ case 12:
|
|
|
+ message.int64_value = reader.sint64();
|
|
|
+ break;
|
|
|
+ case 13:
|
|
|
+ message.string_value = reader.string();
|
|
|
+ break;
|
|
|
+ case 14:
|
|
|
+ message.bool_value = reader.bool();
|
|
|
+ break;
|
|
|
+ case 31:
|
|
|
+ message.tensor_shape_value = $root.tensorflow.TensorShapeProto.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ case 32:
|
|
|
+ message.tensor_dtype_value = reader.int32();
|
|
|
+ break;
|
|
|
+ case 33:
|
|
|
+ message.tensor_spec_value = $root.tensorflow.TensorSpecProto.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ case 51:
|
|
|
+ message.list_value = $root.tensorflow.ListValue.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ case 52:
|
|
|
+ message.tuple_value = $root.tensorflow.TupleValue.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ case 53:
|
|
|
+ message.dict_value = $root.tensorflow.DictValue.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ case 54:
|
|
|
+ message.named_tuple_value = $root.tensorflow.NamedTupleValue.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ StructuredValue.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.StructuredValue();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "none_value":
|
|
|
+ message.none_value = $root.tensorflow.NoneValue.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ case "float64_value":
|
|
|
+ reader.value();
|
|
|
+ message.float64_value = reader.double();
|
|
|
+ break;
|
|
|
+ case "int64_value":
|
|
|
+ reader.value();
|
|
|
+ message.int64_value = reader.sint64();
|
|
|
+ break;
|
|
|
+ case "string_value":
|
|
|
+ reader.value();
|
|
|
+ message.string_value = reader.string();
|
|
|
+ break;
|
|
|
+ case "bool_value":
|
|
|
+ reader.value();
|
|
|
+ message.bool_value = reader.bool();
|
|
|
+ break;
|
|
|
+ case "tensor_shape_value":
|
|
|
+ message.tensor_shape_value = $root.tensorflow.TensorShapeProto.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ case "tensor_dtype_value":
|
|
|
+ reader.value();
|
|
|
+ message.tensor_dtype_value = reader.enum($root.tensorflow.DataType);
|
|
|
+ break;
|
|
|
+ case "tensor_spec_value":
|
|
|
+ message.tensor_spec_value = $root.tensorflow.TensorSpecProto.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ case "list_value":
|
|
|
+ message.list_value = $root.tensorflow.ListValue.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ case "tuple_value":
|
|
|
+ message.tuple_value = $root.tensorflow.TupleValue.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ case "dict_value":
|
|
|
+ message.dict_value = $root.tensorflow.DictValue.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ case "named_tuple_value":
|
|
|
+ message.named_tuple_value = $root.tensorflow.NamedTupleValue.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ StructuredValue.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ var properties = {};
|
|
|
+ if (message.none_value != null && message.hasOwnProperty("none_value")) {
|
|
|
+ properties.kind = 1;
|
|
|
+ {
|
|
|
+ var error = $root.tensorflow.NoneValue.verify(message.none_value);
|
|
|
+ if (error)
|
|
|
+ return "none_value." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (message.float64_value != null && message.hasOwnProperty("float64_value")) {
|
|
|
+ if (properties.kind === 1)
|
|
|
+ return "kind: multiple values";
|
|
|
+ properties.kind = 1;
|
|
|
+ if (typeof message.float64_value !== "number")
|
|
|
+ return "float64_value: number expected";
|
|
|
+ }
|
|
|
+ if (message.int64_value != null && message.hasOwnProperty("int64_value")) {
|
|
|
+ if (properties.kind === 1)
|
|
|
+ return "kind: multiple values";
|
|
|
+ properties.kind = 1;
|
|
|
+ if (!$util.isInteger(message.int64_value) && !(message.int64_value && $util.isInteger(message.int64_value.low) && $util.isInteger(message.int64_value.high)))
|
|
|
+ return "int64_value: integer|Long expected";
|
|
|
+ }
|
|
|
+ if (message.string_value != null && message.hasOwnProperty("string_value")) {
|
|
|
+ if (properties.kind === 1)
|
|
|
+ return "kind: multiple values";
|
|
|
+ properties.kind = 1;
|
|
|
+ if (!$util.isString(message.string_value))
|
|
|
+ return "string_value: string expected";
|
|
|
+ }
|
|
|
+ if (message.bool_value != null && message.hasOwnProperty("bool_value")) {
|
|
|
+ if (properties.kind === 1)
|
|
|
+ return "kind: multiple values";
|
|
|
+ properties.kind = 1;
|
|
|
+ if (typeof message.bool_value !== "boolean")
|
|
|
+ return "bool_value: boolean expected";
|
|
|
+ }
|
|
|
+ if (message.tensor_shape_value != null && message.hasOwnProperty("tensor_shape_value")) {
|
|
|
+ if (properties.kind === 1)
|
|
|
+ return "kind: multiple values";
|
|
|
+ properties.kind = 1;
|
|
|
+ {
|
|
|
+ var error = $root.tensorflow.TensorShapeProto.verify(message.tensor_shape_value);
|
|
|
+ if (error)
|
|
|
+ return "tensor_shape_value." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (message.tensor_dtype_value != null && message.hasOwnProperty("tensor_dtype_value")) {
|
|
|
+ if (properties.kind === 1)
|
|
|
+ return "kind: multiple values";
|
|
|
+ properties.kind = 1;
|
|
|
+ switch (message.tensor_dtype_value) {
|
|
|
+ default:
|
|
|
+ return "tensor_dtype_value: enum value expected";
|
|
|
+ case 0:
|
|
|
+ case 1:
|
|
|
+ case 2:
|
|
|
+ case 3:
|
|
|
+ case 4:
|
|
|
+ case 5:
|
|
|
+ case 6:
|
|
|
+ case 7:
|
|
|
+ case 8:
|
|
|
+ case 9:
|
|
|
+ case 10:
|
|
|
+ case 11:
|
|
|
+ case 12:
|
|
|
+ case 13:
|
|
|
+ case 14:
|
|
|
+ case 15:
|
|
|
+ case 16:
|
|
|
+ case 17:
|
|
|
+ case 18:
|
|
|
+ case 19:
|
|
|
+ case 20:
|
|
|
+ case 21:
|
|
|
+ case 22:
|
|
|
+ case 23:
|
|
|
+ case 101:
|
|
|
+ case 102:
|
|
|
+ case 103:
|
|
|
+ case 104:
|
|
|
+ case 105:
|
|
|
+ case 106:
|
|
|
+ case 107:
|
|
|
+ case 108:
|
|
|
+ case 109:
|
|
|
+ case 110:
|
|
|
+ case 111:
|
|
|
+ case 112:
|
|
|
+ case 113:
|
|
|
+ case 114:
|
|
|
+ case 115:
|
|
|
+ case 116:
|
|
|
+ case 117:
|
|
|
+ case 118:
|
|
|
+ case 119:
|
|
|
+ case 120:
|
|
|
+ case 121:
|
|
|
+ case 122:
|
|
|
+ case 123:
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (message.tensor_spec_value != null && message.hasOwnProperty("tensor_spec_value")) {
|
|
|
+ if (properties.kind === 1)
|
|
|
+ return "kind: multiple values";
|
|
|
+ properties.kind = 1;
|
|
|
+ {
|
|
|
+ var error = $root.tensorflow.TensorSpecProto.verify(message.tensor_spec_value);
|
|
|
+ if (error)
|
|
|
+ return "tensor_spec_value." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (message.list_value != null && message.hasOwnProperty("list_value")) {
|
|
|
+ if (properties.kind === 1)
|
|
|
+ return "kind: multiple values";
|
|
|
+ properties.kind = 1;
|
|
|
+ {
|
|
|
+ var error = $root.tensorflow.ListValue.verify(message.list_value);
|
|
|
+ if (error)
|
|
|
+ return "list_value." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (message.tuple_value != null && message.hasOwnProperty("tuple_value")) {
|
|
|
+ if (properties.kind === 1)
|
|
|
+ return "kind: multiple values";
|
|
|
+ properties.kind = 1;
|
|
|
+ {
|
|
|
+ var error = $root.tensorflow.TupleValue.verify(message.tuple_value);
|
|
|
+ if (error)
|
|
|
+ return "tuple_value." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (message.dict_value != null && message.hasOwnProperty("dict_value")) {
|
|
|
+ if (properties.kind === 1)
|
|
|
+ return "kind: multiple values";
|
|
|
+ properties.kind = 1;
|
|
|
+ {
|
|
|
+ var error = $root.tensorflow.DictValue.verify(message.dict_value);
|
|
|
+ if (error)
|
|
|
+ return "dict_value." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (message.named_tuple_value != null && message.hasOwnProperty("named_tuple_value")) {
|
|
|
+ if (properties.kind === 1)
|
|
|
+ return "kind: multiple values";
|
|
|
+ properties.kind = 1;
|
|
|
+ {
|
|
|
+ var error = $root.tensorflow.NamedTupleValue.verify(message.named_tuple_value);
|
|
|
+ if (error)
|
|
|
+ return "named_tuple_value." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ StructuredValue.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.StructuredValue)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.StructuredValue();
|
|
|
+ if (object.none_value != null) {
|
|
|
+ if (typeof object.none_value !== "object")
|
|
|
+ throw TypeError(".tensorflow.StructuredValue.none_value: object expected");
|
|
|
+ message.none_value = $root.tensorflow.NoneValue.fromObject(object.none_value);
|
|
|
+ }
|
|
|
+ if (object.float64_value != null)
|
|
|
+ message.float64_value = Number(object.float64_value);
|
|
|
+ if (object.int64_value != null)
|
|
|
+ if ($util.Long)
|
|
|
+ (message.int64_value = $util.Long.fromValue(object.int64_value)).unsigned = false;
|
|
|
+ else if (typeof object.int64_value === "string")
|
|
|
+ message.int64_value = parseInt(object.int64_value, 10);
|
|
|
+ else if (typeof object.int64_value === "number")
|
|
|
+ message.int64_value = object.int64_value;
|
|
|
+ else if (typeof object.int64_value === "object")
|
|
|
+ message.int64_value = new $util.LongBits(object.int64_value.low >>> 0, object.int64_value.high >>> 0).toNumber();
|
|
|
+ if (object.string_value != null)
|
|
|
+ message.string_value = String(object.string_value);
|
|
|
+ if (object.bool_value != null)
|
|
|
+ message.bool_value = Boolean(object.bool_value);
|
|
|
+ if (object.tensor_shape_value != null) {
|
|
|
+ if (typeof object.tensor_shape_value !== "object")
|
|
|
+ throw TypeError(".tensorflow.StructuredValue.tensor_shape_value: object expected");
|
|
|
+ message.tensor_shape_value = $root.tensorflow.TensorShapeProto.fromObject(object.tensor_shape_value);
|
|
|
+ }
|
|
|
+ switch (object.tensor_dtype_value) {
|
|
|
+ case "DT_INVALID":
|
|
|
+ case 0:
|
|
|
+ message.tensor_dtype_value = 0;
|
|
|
+ break;
|
|
|
+ case "DT_FLOAT":
|
|
|
+ case 1:
|
|
|
+ message.tensor_dtype_value = 1;
|
|
|
+ break;
|
|
|
+ case "DT_DOUBLE":
|
|
|
+ case 2:
|
|
|
+ message.tensor_dtype_value = 2;
|
|
|
+ break;
|
|
|
+ case "DT_INT32":
|
|
|
+ case 3:
|
|
|
+ message.tensor_dtype_value = 3;
|
|
|
+ break;
|
|
|
+ case "DT_UINT8":
|
|
|
+ case 4:
|
|
|
+ message.tensor_dtype_value = 4;
|
|
|
+ break;
|
|
|
+ case "DT_INT16":
|
|
|
+ case 5:
|
|
|
+ message.tensor_dtype_value = 5;
|
|
|
+ break;
|
|
|
+ case "DT_INT8":
|
|
|
+ case 6:
|
|
|
+ message.tensor_dtype_value = 6;
|
|
|
+ break;
|
|
|
+ case "DT_STRING":
|
|
|
+ case 7:
|
|
|
+ message.tensor_dtype_value = 7;
|
|
|
+ break;
|
|
|
+ case "DT_COMPLEX64":
|
|
|
+ case 8:
|
|
|
+ message.tensor_dtype_value = 8;
|
|
|
+ break;
|
|
|
+ case "DT_INT64":
|
|
|
+ case 9:
|
|
|
+ message.tensor_dtype_value = 9;
|
|
|
+ break;
|
|
|
+ case "DT_BOOL":
|
|
|
+ case 10:
|
|
|
+ message.tensor_dtype_value = 10;
|
|
|
+ break;
|
|
|
+ case "DT_QINT8":
|
|
|
+ case 11:
|
|
|
+ message.tensor_dtype_value = 11;
|
|
|
+ break;
|
|
|
+ case "DT_QUINT8":
|
|
|
+ case 12:
|
|
|
+ message.tensor_dtype_value = 12;
|
|
|
+ break;
|
|
|
+ case "DT_QINT32":
|
|
|
+ case 13:
|
|
|
+ message.tensor_dtype_value = 13;
|
|
|
+ break;
|
|
|
+ case "DT_BFLOAT16":
|
|
|
+ case 14:
|
|
|
+ message.tensor_dtype_value = 14;
|
|
|
+ break;
|
|
|
+ case "DT_QINT16":
|
|
|
+ case 15:
|
|
|
+ message.tensor_dtype_value = 15;
|
|
|
+ break;
|
|
|
+ case "DT_QUINT16":
|
|
|
+ case 16:
|
|
|
+ message.tensor_dtype_value = 16;
|
|
|
+ break;
|
|
|
+ case "DT_UINT16":
|
|
|
+ case 17:
|
|
|
+ message.tensor_dtype_value = 17;
|
|
|
+ break;
|
|
|
+ case "DT_COMPLEX128":
|
|
|
+ case 18:
|
|
|
+ message.tensor_dtype_value = 18;
|
|
|
+ break;
|
|
|
+ case "DT_HALF":
|
|
|
+ case 19:
|
|
|
+ message.tensor_dtype_value = 19;
|
|
|
+ break;
|
|
|
+ case "DT_RESOURCE":
|
|
|
+ case 20:
|
|
|
+ message.tensor_dtype_value = 20;
|
|
|
+ break;
|
|
|
+ case "DT_VARIANT":
|
|
|
+ case 21:
|
|
|
+ message.tensor_dtype_value = 21;
|
|
|
+ break;
|
|
|
+ case "DT_UINT32":
|
|
|
+ case 22:
|
|
|
+ message.tensor_dtype_value = 22;
|
|
|
+ break;
|
|
|
+ case "DT_UINT64":
|
|
|
+ case 23:
|
|
|
+ message.tensor_dtype_value = 23;
|
|
|
+ break;
|
|
|
+ case "DT_FLOAT_REF":
|
|
|
+ case 101:
|
|
|
+ message.tensor_dtype_value = 101;
|
|
|
+ break;
|
|
|
+ case "DT_DOUBLE_REF":
|
|
|
+ case 102:
|
|
|
+ message.tensor_dtype_value = 102;
|
|
|
+ break;
|
|
|
+ case "DT_INT32_REF":
|
|
|
+ case 103:
|
|
|
+ message.tensor_dtype_value = 103;
|
|
|
+ break;
|
|
|
+ case "DT_UINT8_REF":
|
|
|
+ case 104:
|
|
|
+ message.tensor_dtype_value = 104;
|
|
|
+ break;
|
|
|
+ case "DT_INT16_REF":
|
|
|
+ case 105:
|
|
|
+ message.tensor_dtype_value = 105;
|
|
|
+ break;
|
|
|
+ case "DT_INT8_REF":
|
|
|
+ case 106:
|
|
|
+ message.tensor_dtype_value = 106;
|
|
|
+ break;
|
|
|
+ case "DT_STRING_REF":
|
|
|
+ case 107:
|
|
|
+ message.tensor_dtype_value = 107;
|
|
|
+ break;
|
|
|
+ case "DT_COMPLEX64_REF":
|
|
|
+ case 108:
|
|
|
+ message.tensor_dtype_value = 108;
|
|
|
+ break;
|
|
|
+ case "DT_INT64_REF":
|
|
|
+ case 109:
|
|
|
+ message.tensor_dtype_value = 109;
|
|
|
+ break;
|
|
|
+ case "DT_BOOL_REF":
|
|
|
+ case 110:
|
|
|
+ message.tensor_dtype_value = 110;
|
|
|
+ break;
|
|
|
+ case "DT_QINT8_REF":
|
|
|
+ case 111:
|
|
|
+ message.tensor_dtype_value = 111;
|
|
|
+ break;
|
|
|
+ case "DT_QUINT8_REF":
|
|
|
+ case 112:
|
|
|
+ message.tensor_dtype_value = 112;
|
|
|
+ break;
|
|
|
+ case "DT_QINT32_REF":
|
|
|
+ case 113:
|
|
|
+ message.tensor_dtype_value = 113;
|
|
|
+ break;
|
|
|
+ case "DT_BFLOAT16_REF":
|
|
|
+ case 114:
|
|
|
+ message.tensor_dtype_value = 114;
|
|
|
+ break;
|
|
|
+ case "DT_QINT16_REF":
|
|
|
+ case 115:
|
|
|
+ message.tensor_dtype_value = 115;
|
|
|
+ break;
|
|
|
+ case "DT_QUINT16_REF":
|
|
|
+ case 116:
|
|
|
+ message.tensor_dtype_value = 116;
|
|
|
+ break;
|
|
|
+ case "DT_UINT16_REF":
|
|
|
+ case 117:
|
|
|
+ message.tensor_dtype_value = 117;
|
|
|
+ break;
|
|
|
+ case "DT_COMPLEX128_REF":
|
|
|
+ case 118:
|
|
|
+ message.tensor_dtype_value = 118;
|
|
|
+ break;
|
|
|
+ case "DT_HALF_REF":
|
|
|
+ case 119:
|
|
|
+ message.tensor_dtype_value = 119;
|
|
|
+ break;
|
|
|
+ case "DT_RESOURCE_REF":
|
|
|
+ case 120:
|
|
|
+ message.tensor_dtype_value = 120;
|
|
|
+ break;
|
|
|
+ case "DT_VARIANT_REF":
|
|
|
+ case 121:
|
|
|
+ message.tensor_dtype_value = 121;
|
|
|
+ break;
|
|
|
+ case "DT_UINT32_REF":
|
|
|
+ case 122:
|
|
|
+ message.tensor_dtype_value = 122;
|
|
|
+ break;
|
|
|
+ case "DT_UINT64_REF":
|
|
|
+ case 123:
|
|
|
+ message.tensor_dtype_value = 123;
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ if (object.tensor_spec_value != null) {
|
|
|
+ if (typeof object.tensor_spec_value !== "object")
|
|
|
+ throw TypeError(".tensorflow.StructuredValue.tensor_spec_value: object expected");
|
|
|
+ message.tensor_spec_value = $root.tensorflow.TensorSpecProto.fromObject(object.tensor_spec_value);
|
|
|
+ }
|
|
|
+ if (object.list_value != null) {
|
|
|
+ if (typeof object.list_value !== "object")
|
|
|
+ throw TypeError(".tensorflow.StructuredValue.list_value: object expected");
|
|
|
+ message.list_value = $root.tensorflow.ListValue.fromObject(object.list_value);
|
|
|
+ }
|
|
|
+ if (object.tuple_value != null) {
|
|
|
+ if (typeof object.tuple_value !== "object")
|
|
|
+ throw TypeError(".tensorflow.StructuredValue.tuple_value: object expected");
|
|
|
+ message.tuple_value = $root.tensorflow.TupleValue.fromObject(object.tuple_value);
|
|
|
+ }
|
|
|
+ if (object.dict_value != null) {
|
|
|
+ if (typeof object.dict_value !== "object")
|
|
|
+ throw TypeError(".tensorflow.StructuredValue.dict_value: object expected");
|
|
|
+ message.dict_value = $root.tensorflow.DictValue.fromObject(object.dict_value);
|
|
|
+ }
|
|
|
+ if (object.named_tuple_value != null) {
|
|
|
+ if (typeof object.named_tuple_value !== "object")
|
|
|
+ throw TypeError(".tensorflow.StructuredValue.named_tuple_value: object expected");
|
|
|
+ message.named_tuple_value = $root.tensorflow.NamedTupleValue.fromObject(object.named_tuple_value);
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ StructuredValue.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (message.none_value != null && message.hasOwnProperty("none_value")) {
|
|
|
+ object.none_value = $root.tensorflow.NoneValue.toObject(message.none_value, options);
|
|
|
+ if (options.oneofs)
|
|
|
+ object.kind = "none_value";
|
|
|
+ }
|
|
|
+ if (message.float64_value != null && message.hasOwnProperty("float64_value")) {
|
|
|
+ object.float64_value = options.json && !isFinite(message.float64_value) ? String(message.float64_value) : message.float64_value;
|
|
|
+ if (options.oneofs)
|
|
|
+ object.kind = "float64_value";
|
|
|
+ }
|
|
|
+ if (message.int64_value != null && message.hasOwnProperty("int64_value")) {
|
|
|
+ if (typeof message.int64_value === "number")
|
|
|
+ object.int64_value = options.longs === String ? String(message.int64_value) : message.int64_value;
|
|
|
+ else
|
|
|
+ object.int64_value = options.longs === String ? $util.Long.prototype.toString.call(message.int64_value) : options.longs === Number ? new $util.LongBits(message.int64_value.low >>> 0, message.int64_value.high >>> 0).toNumber() : message.int64_value;
|
|
|
+ if (options.oneofs)
|
|
|
+ object.kind = "int64_value";
|
|
|
+ }
|
|
|
+ if (message.string_value != null && message.hasOwnProperty("string_value")) {
|
|
|
+ object.string_value = message.string_value;
|
|
|
+ if (options.oneofs)
|
|
|
+ object.kind = "string_value";
|
|
|
+ }
|
|
|
+ if (message.bool_value != null && message.hasOwnProperty("bool_value")) {
|
|
|
+ object.bool_value = message.bool_value;
|
|
|
+ if (options.oneofs)
|
|
|
+ object.kind = "bool_value";
|
|
|
+ }
|
|
|
+ if (message.tensor_shape_value != null && message.hasOwnProperty("tensor_shape_value")) {
|
|
|
+ object.tensor_shape_value = $root.tensorflow.TensorShapeProto.toObject(message.tensor_shape_value, options);
|
|
|
+ if (options.oneofs)
|
|
|
+ object.kind = "tensor_shape_value";
|
|
|
+ }
|
|
|
+ if (message.tensor_dtype_value != null && message.hasOwnProperty("tensor_dtype_value")) {
|
|
|
+ object.tensor_dtype_value = options.enums === String ? $root.tensorflow.DataType[message.tensor_dtype_value] : message.tensor_dtype_value;
|
|
|
+ if (options.oneofs)
|
|
|
+ object.kind = "tensor_dtype_value";
|
|
|
+ }
|
|
|
+ if (message.tensor_spec_value != null && message.hasOwnProperty("tensor_spec_value")) {
|
|
|
+ object.tensor_spec_value = $root.tensorflow.TensorSpecProto.toObject(message.tensor_spec_value, options);
|
|
|
+ if (options.oneofs)
|
|
|
+ object.kind = "tensor_spec_value";
|
|
|
+ }
|
|
|
+ if (message.list_value != null && message.hasOwnProperty("list_value")) {
|
|
|
+ object.list_value = $root.tensorflow.ListValue.toObject(message.list_value, options);
|
|
|
+ if (options.oneofs)
|
|
|
+ object.kind = "list_value";
|
|
|
+ }
|
|
|
+ if (message.tuple_value != null && message.hasOwnProperty("tuple_value")) {
|
|
|
+ object.tuple_value = $root.tensorflow.TupleValue.toObject(message.tuple_value, options);
|
|
|
+ if (options.oneofs)
|
|
|
+ object.kind = "tuple_value";
|
|
|
+ }
|
|
|
+ if (message.dict_value != null && message.hasOwnProperty("dict_value")) {
|
|
|
+ object.dict_value = $root.tensorflow.DictValue.toObject(message.dict_value, options);
|
|
|
+ if (options.oneofs)
|
|
|
+ object.kind = "dict_value";
|
|
|
+ }
|
|
|
+ if (message.named_tuple_value != null && message.hasOwnProperty("named_tuple_value")) {
|
|
|
+ object.named_tuple_value = $root.tensorflow.NamedTupleValue.toObject(message.named_tuple_value, options);
|
|
|
+ if (options.oneofs)
|
|
|
+ object.kind = "named_tuple_value";
|
|
|
+ }
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ StructuredValue.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return StructuredValue;
|
|
|
+ })();
|
|
|
+
|
|
|
+ tensorflow.NoneValue = (function() {
|
|
|
+
|
|
|
+ function NoneValue(properties) {
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ NoneValue.create = function create(properties) {
|
|
|
+ return new NoneValue(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ NoneValue.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.NoneValue();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ NoneValue.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.NoneValue();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ NoneValue.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ NoneValue.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.NoneValue)
|
|
|
+ return object;
|
|
|
+ return new $root.tensorflow.NoneValue();
|
|
|
+ };
|
|
|
+
|
|
|
+ NoneValue.toObject = function toObject() {
|
|
|
+ return {};
|
|
|
+ };
|
|
|
+
|
|
|
+ NoneValue.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return NoneValue;
|
|
|
+ })();
|
|
|
+
|
|
|
+ tensorflow.ListValue = (function() {
|
|
|
+
|
|
|
+ function ListValue(properties) {
|
|
|
+ this.values = [];
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ ListValue.prototype.values = $util.emptyArray;
|
|
|
+
|
|
|
+ ListValue.create = function create(properties) {
|
|
|
+ return new ListValue(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ ListValue.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.ListValue();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ if (!(message.values && message.values.length))
|
|
|
+ message.values = [];
|
|
|
+ message.values.push($root.tensorflow.StructuredValue.decode(reader, reader.uint32()));
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ ListValue.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.ListValue();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "values":
|
|
|
+ if (!(message.values && message.values.length))
|
|
|
+ message.values = [];
|
|
|
+ message.values.push($root.tensorflow.StructuredValue.decodeText(reader, true));
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ ListValue.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ if (message.values != null && message.hasOwnProperty("values")) {
|
|
|
+ if (!Array.isArray(message.values))
|
|
|
+ return "values: array expected";
|
|
|
+ for (var i = 0; i < message.values.length; ++i) {
|
|
|
+ var error = $root.tensorflow.StructuredValue.verify(message.values[i]);
|
|
|
+ if (error)
|
|
|
+ return "values." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ ListValue.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.ListValue)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.ListValue();
|
|
|
+ if (object.values) {
|
|
|
+ if (!Array.isArray(object.values))
|
|
|
+ throw TypeError(".tensorflow.ListValue.values: array expected");
|
|
|
+ message.values = [];
|
|
|
+ for (var i = 0; i < object.values.length; ++i) {
|
|
|
+ if (typeof object.values[i] !== "object")
|
|
|
+ throw TypeError(".tensorflow.ListValue.values: object expected");
|
|
|
+ message.values[i] = $root.tensorflow.StructuredValue.fromObject(object.values[i]);
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ ListValue.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.arrays || options.defaults)
|
|
|
+ object.values = [];
|
|
|
+ if (message.values && message.values.length) {
|
|
|
+ object.values = [];
|
|
|
+ for (var j = 0; j < message.values.length; ++j)
|
|
|
+ object.values[j] = $root.tensorflow.StructuredValue.toObject(message.values[j], options);
|
|
|
+ }
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ ListValue.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return ListValue;
|
|
|
+ })();
|
|
|
+
|
|
|
+ tensorflow.TupleValue = (function() {
|
|
|
+
|
|
|
+ function TupleValue(properties) {
|
|
|
+ this.values = [];
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ TupleValue.prototype.values = $util.emptyArray;
|
|
|
+
|
|
|
+ TupleValue.create = function create(properties) {
|
|
|
+ return new TupleValue(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ TupleValue.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.TupleValue();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ if (!(message.values && message.values.length))
|
|
|
+ message.values = [];
|
|
|
+ message.values.push($root.tensorflow.StructuredValue.decode(reader, reader.uint32()));
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ TupleValue.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.TupleValue();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "values":
|
|
|
+ if (!(message.values && message.values.length))
|
|
|
+ message.values = [];
|
|
|
+ message.values.push($root.tensorflow.StructuredValue.decodeText(reader, true));
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ TupleValue.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ if (message.values != null && message.hasOwnProperty("values")) {
|
|
|
+ if (!Array.isArray(message.values))
|
|
|
+ return "values: array expected";
|
|
|
+ for (var i = 0; i < message.values.length; ++i) {
|
|
|
+ var error = $root.tensorflow.StructuredValue.verify(message.values[i]);
|
|
|
+ if (error)
|
|
|
+ return "values." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ TupleValue.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.TupleValue)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.TupleValue();
|
|
|
+ if (object.values) {
|
|
|
+ if (!Array.isArray(object.values))
|
|
|
+ throw TypeError(".tensorflow.TupleValue.values: array expected");
|
|
|
+ message.values = [];
|
|
|
+ for (var i = 0; i < object.values.length; ++i) {
|
|
|
+ if (typeof object.values[i] !== "object")
|
|
|
+ throw TypeError(".tensorflow.TupleValue.values: object expected");
|
|
|
+ message.values[i] = $root.tensorflow.StructuredValue.fromObject(object.values[i]);
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ TupleValue.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.arrays || options.defaults)
|
|
|
+ object.values = [];
|
|
|
+ if (message.values && message.values.length) {
|
|
|
+ object.values = [];
|
|
|
+ for (var j = 0; j < message.values.length; ++j)
|
|
|
+ object.values[j] = $root.tensorflow.StructuredValue.toObject(message.values[j], options);
|
|
|
+ }
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ TupleValue.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return TupleValue;
|
|
|
+ })();
|
|
|
+
|
|
|
+ tensorflow.DictValue = (function() {
|
|
|
+
|
|
|
+ function DictValue(properties) {
|
|
|
+ this.fields = {};
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ DictValue.prototype.fields = $util.emptyObject;
|
|
|
+
|
|
|
+ DictValue.create = function create(properties) {
|
|
|
+ return new DictValue(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ DictValue.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.DictValue(), key;
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ reader.skip().pos++;
|
|
|
+ if (message.fields === $util.emptyObject)
|
|
|
+ message.fields = {};
|
|
|
+ key = reader.string();
|
|
|
+ reader.pos++;
|
|
|
+ message.fields[key] = $root.tensorflow.StructuredValue.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ DictValue.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.DictValue(), key;
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "fields":
|
|
|
+ reader.assert("{");
|
|
|
+ if (message.fields === $util.emptyObject)
|
|
|
+ message.fields = {};
|
|
|
+ reader.assert("key");
|
|
|
+ reader.value();
|
|
|
+ key = reader.string();
|
|
|
+ reader.assert("value");
|
|
|
+ message.fields[key] = $root.tensorflow.StructuredValue.decodeText(reader, true);
|
|
|
+ reader.assert("}");
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ DictValue.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ if (message.fields != null && message.hasOwnProperty("fields")) {
|
|
|
+ if (!$util.isObject(message.fields))
|
|
|
+ return "fields: object expected";
|
|
|
+ var key = Object.keys(message.fields);
|
|
|
+ for (var i = 0; i < key.length; ++i) {
|
|
|
+ var error = $root.tensorflow.StructuredValue.verify(message.fields[key[i]]);
|
|
|
+ if (error)
|
|
|
+ return "fields." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ DictValue.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.DictValue)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.DictValue();
|
|
|
+ if (object.fields) {
|
|
|
+ if (typeof object.fields !== "object")
|
|
|
+ throw TypeError(".tensorflow.DictValue.fields: object expected");
|
|
|
+ message.fields = {};
|
|
|
+ for (var keys = Object.keys(object.fields), i = 0; i < keys.length; ++i) {
|
|
|
+ if (typeof object.fields[keys[i]] !== "object")
|
|
|
+ throw TypeError(".tensorflow.DictValue.fields: object expected");
|
|
|
+ message.fields[keys[i]] = $root.tensorflow.StructuredValue.fromObject(object.fields[keys[i]]);
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ DictValue.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.objects || options.defaults)
|
|
|
+ object.fields = {};
|
|
|
+ var keys2;
|
|
|
+ if (message.fields && (keys2 = Object.keys(message.fields)).length) {
|
|
|
+ object.fields = {};
|
|
|
+ for (var j = 0; j < keys2.length; ++j)
|
|
|
+ object.fields[keys2[j]] = $root.tensorflow.StructuredValue.toObject(message.fields[keys2[j]], options);
|
|
|
+ }
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ DictValue.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return DictValue;
|
|
|
+ })();
|
|
|
+
|
|
|
+ tensorflow.PairValue = (function() {
|
|
|
+
|
|
|
+ function PairValue(properties) {
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ PairValue.prototype.key = "";
|
|
|
+ PairValue.prototype.value = null;
|
|
|
+
|
|
|
+ PairValue.create = function create(properties) {
|
|
|
+ return new PairValue(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ PairValue.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.PairValue();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ message.key = reader.string();
|
|
|
+ break;
|
|
|
+ case 2:
|
|
|
+ message.value = $root.tensorflow.StructuredValue.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ PairValue.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.PairValue();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "key":
|
|
|
+ reader.value();
|
|
|
+ message.key = reader.string();
|
|
|
+ break;
|
|
|
+ case "value":
|
|
|
+ message.value = $root.tensorflow.StructuredValue.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ PairValue.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ if (message.key != null && message.hasOwnProperty("key"))
|
|
|
+ if (!$util.isString(message.key))
|
|
|
+ return "key: string expected";
|
|
|
+ if (message.value != null && message.hasOwnProperty("value")) {
|
|
|
+ var error = $root.tensorflow.StructuredValue.verify(message.value);
|
|
|
+ if (error)
|
|
|
+ return "value." + error;
|
|
|
+ }
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ PairValue.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.PairValue)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.PairValue();
|
|
|
+ if (object.key != null)
|
|
|
+ message.key = String(object.key);
|
|
|
+ if (object.value != null) {
|
|
|
+ if (typeof object.value !== "object")
|
|
|
+ throw TypeError(".tensorflow.PairValue.value: object expected");
|
|
|
+ message.value = $root.tensorflow.StructuredValue.fromObject(object.value);
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ PairValue.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.defaults) {
|
|
|
+ object.key = "";
|
|
|
+ object.value = null;
|
|
|
+ }
|
|
|
+ if (message.key != null && message.hasOwnProperty("key"))
|
|
|
+ object.key = message.key;
|
|
|
+ if (message.value != null && message.hasOwnProperty("value"))
|
|
|
+ object.value = $root.tensorflow.StructuredValue.toObject(message.value, options);
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ PairValue.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return PairValue;
|
|
|
+ })();
|
|
|
+
|
|
|
+ tensorflow.NamedTupleValue = (function() {
|
|
|
+
|
|
|
+ function NamedTupleValue(properties) {
|
|
|
+ this.values = [];
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ NamedTupleValue.prototype.name = "";
|
|
|
+ NamedTupleValue.prototype.values = $util.emptyArray;
|
|
|
+
|
|
|
+ NamedTupleValue.create = function create(properties) {
|
|
|
+ return new NamedTupleValue(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ NamedTupleValue.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.NamedTupleValue();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ message.name = reader.string();
|
|
|
+ break;
|
|
|
+ case 2:
|
|
|
+ if (!(message.values && message.values.length))
|
|
|
+ message.values = [];
|
|
|
+ message.values.push($root.tensorflow.PairValue.decode(reader, reader.uint32()));
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ NamedTupleValue.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.NamedTupleValue();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "name":
|
|
|
+ reader.value();
|
|
|
+ message.name = reader.string();
|
|
|
+ break;
|
|
|
+ case "values":
|
|
|
+ if (!(message.values && message.values.length))
|
|
|
+ message.values = [];
|
|
|
+ message.values.push($root.tensorflow.PairValue.decodeText(reader, true));
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ NamedTupleValue.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ if (message.name != null && message.hasOwnProperty("name"))
|
|
|
+ if (!$util.isString(message.name))
|
|
|
+ return "name: string expected";
|
|
|
+ if (message.values != null && message.hasOwnProperty("values")) {
|
|
|
+ if (!Array.isArray(message.values))
|
|
|
+ return "values: array expected";
|
|
|
+ for (var i = 0; i < message.values.length; ++i) {
|
|
|
+ var error = $root.tensorflow.PairValue.verify(message.values[i]);
|
|
|
+ if (error)
|
|
|
+ return "values." + error;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ NamedTupleValue.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.NamedTupleValue)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.NamedTupleValue();
|
|
|
+ if (object.name != null)
|
|
|
+ message.name = String(object.name);
|
|
|
+ if (object.values) {
|
|
|
+ if (!Array.isArray(object.values))
|
|
|
+ throw TypeError(".tensorflow.NamedTupleValue.values: array expected");
|
|
|
+ message.values = [];
|
|
|
+ for (var i = 0; i < object.values.length; ++i) {
|
|
|
+ if (typeof object.values[i] !== "object")
|
|
|
+ throw TypeError(".tensorflow.NamedTupleValue.values: object expected");
|
|
|
+ message.values[i] = $root.tensorflow.PairValue.fromObject(object.values[i]);
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ NamedTupleValue.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.arrays || options.defaults)
|
|
|
+ object.values = [];
|
|
|
+ if (options.defaults)
|
|
|
+ object.name = "";
|
|
|
+ if (message.name != null && message.hasOwnProperty("name"))
|
|
|
+ object.name = message.name;
|
|
|
+ if (message.values && message.values.length) {
|
|
|
+ object.values = [];
|
|
|
+ for (var j = 0; j < message.values.length; ++j)
|
|
|
+ object.values[j] = $root.tensorflow.PairValue.toObject(message.values[j], options);
|
|
|
+ }
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ NamedTupleValue.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return NamedTupleValue;
|
|
|
+ })();
|
|
|
+
|
|
|
+ tensorflow.TensorSpecProto = (function() {
|
|
|
+
|
|
|
+ function TensorSpecProto(properties) {
|
|
|
+ if (properties)
|
|
|
+ for (var keys = Object.keys(properties), i = 0; i < keys.length; ++i)
|
|
|
+ if (properties[keys[i]] != null)
|
|
|
+ this[keys[i]] = properties[keys[i]];
|
|
|
+ }
|
|
|
+
|
|
|
+ TensorSpecProto.prototype.name = "";
|
|
|
+ TensorSpecProto.prototype.shape = null;
|
|
|
+ TensorSpecProto.prototype.dtype = 0;
|
|
|
+
|
|
|
+ TensorSpecProto.create = function create(properties) {
|
|
|
+ return new TensorSpecProto(properties);
|
|
|
+ };
|
|
|
+
|
|
|
+ TensorSpecProto.decode = function decode(reader, length) {
|
|
|
+ if (!(reader instanceof $Reader))
|
|
|
+ reader = $Reader.create(reader);
|
|
|
+ var end = length === undefined ? reader.len : reader.pos + length, message = new $root.tensorflow.TensorSpecProto();
|
|
|
+ while (reader.pos < end) {
|
|
|
+ var tag = reader.uint32();
|
|
|
+ switch (tag >>> 3) {
|
|
|
+ case 1:
|
|
|
+ message.name = reader.string();
|
|
|
+ break;
|
|
|
+ case 2:
|
|
|
+ message.shape = $root.tensorflow.TensorShapeProto.decode(reader, reader.uint32());
|
|
|
+ break;
|
|
|
+ case 3:
|
|
|
+ message.dtype = reader.int32();
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.skipType(tag & 7);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ TensorSpecProto.decodeText = function decodeText(reader, block) {
|
|
|
+ if (!(reader instanceof $TextReader))
|
|
|
+ reader = $TextReader.create(reader);
|
|
|
+ var message = new $root.tensorflow.TensorSpecProto();
|
|
|
+ reader.start(block);
|
|
|
+ while (!reader.end(block)) {
|
|
|
+ var tag = reader.tag();
|
|
|
+ switch (tag) {
|
|
|
+ case "name":
|
|
|
+ reader.value();
|
|
|
+ message.name = reader.string();
|
|
|
+ break;
|
|
|
+ case "shape":
|
|
|
+ message.shape = $root.tensorflow.TensorShapeProto.decodeText(reader, true);
|
|
|
+ break;
|
|
|
+ case "dtype":
|
|
|
+ reader.value();
|
|
|
+ message.dtype = reader.enum($root.tensorflow.DataType);
|
|
|
+ break;
|
|
|
+ default:
|
|
|
+ reader.field(tag, message);
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ TensorSpecProto.verify = function verify(message) {
|
|
|
+ if (typeof message !== "object" || message === null)
|
|
|
+ return "object expected";
|
|
|
+ if (message.name != null && message.hasOwnProperty("name"))
|
|
|
+ if (!$util.isString(message.name))
|
|
|
+ return "name: string expected";
|
|
|
+ if (message.shape != null && message.hasOwnProperty("shape")) {
|
|
|
+ var error = $root.tensorflow.TensorShapeProto.verify(message.shape);
|
|
|
+ if (error)
|
|
|
+ return "shape." + error;
|
|
|
+ }
|
|
|
+ if (message.dtype != null && message.hasOwnProperty("dtype"))
|
|
|
+ switch (message.dtype) {
|
|
|
+ default:
|
|
|
+ return "dtype: enum value expected";
|
|
|
+ case 0:
|
|
|
+ case 1:
|
|
|
+ case 2:
|
|
|
+ case 3:
|
|
|
+ case 4:
|
|
|
+ case 5:
|
|
|
+ case 6:
|
|
|
+ case 7:
|
|
|
+ case 8:
|
|
|
+ case 9:
|
|
|
+ case 10:
|
|
|
+ case 11:
|
|
|
+ case 12:
|
|
|
+ case 13:
|
|
|
+ case 14:
|
|
|
+ case 15:
|
|
|
+ case 16:
|
|
|
+ case 17:
|
|
|
+ case 18:
|
|
|
+ case 19:
|
|
|
+ case 20:
|
|
|
+ case 21:
|
|
|
+ case 22:
|
|
|
+ case 23:
|
|
|
+ case 101:
|
|
|
+ case 102:
|
|
|
+ case 103:
|
|
|
+ case 104:
|
|
|
+ case 105:
|
|
|
+ case 106:
|
|
|
+ case 107:
|
|
|
+ case 108:
|
|
|
+ case 109:
|
|
|
+ case 110:
|
|
|
+ case 111:
|
|
|
+ case 112:
|
|
|
+ case 113:
|
|
|
+ case 114:
|
|
|
+ case 115:
|
|
|
+ case 116:
|
|
|
+ case 117:
|
|
|
+ case 118:
|
|
|
+ case 119:
|
|
|
+ case 120:
|
|
|
+ case 121:
|
|
|
+ case 122:
|
|
|
+ case 123:
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ return null;
|
|
|
+ };
|
|
|
+
|
|
|
+ TensorSpecProto.fromObject = function fromObject(object) {
|
|
|
+ if (object instanceof $root.tensorflow.TensorSpecProto)
|
|
|
+ return object;
|
|
|
+ var message = new $root.tensorflow.TensorSpecProto();
|
|
|
+ if (object.name != null)
|
|
|
+ message.name = String(object.name);
|
|
|
+ if (object.shape != null) {
|
|
|
+ if (typeof object.shape !== "object")
|
|
|
+ throw TypeError(".tensorflow.TensorSpecProto.shape: object expected");
|
|
|
+ message.shape = $root.tensorflow.TensorShapeProto.fromObject(object.shape);
|
|
|
+ }
|
|
|
+ switch (object.dtype) {
|
|
|
+ case "DT_INVALID":
|
|
|
+ case 0:
|
|
|
+ message.dtype = 0;
|
|
|
+ break;
|
|
|
+ case "DT_FLOAT":
|
|
|
+ case 1:
|
|
|
+ message.dtype = 1;
|
|
|
+ break;
|
|
|
+ case "DT_DOUBLE":
|
|
|
+ case 2:
|
|
|
+ message.dtype = 2;
|
|
|
+ break;
|
|
|
+ case "DT_INT32":
|
|
|
+ case 3:
|
|
|
+ message.dtype = 3;
|
|
|
+ break;
|
|
|
+ case "DT_UINT8":
|
|
|
+ case 4:
|
|
|
+ message.dtype = 4;
|
|
|
+ break;
|
|
|
+ case "DT_INT16":
|
|
|
+ case 5:
|
|
|
+ message.dtype = 5;
|
|
|
+ break;
|
|
|
+ case "DT_INT8":
|
|
|
+ case 6:
|
|
|
+ message.dtype = 6;
|
|
|
+ break;
|
|
|
+ case "DT_STRING":
|
|
|
+ case 7:
|
|
|
+ message.dtype = 7;
|
|
|
+ break;
|
|
|
+ case "DT_COMPLEX64":
|
|
|
+ case 8:
|
|
|
+ message.dtype = 8;
|
|
|
+ break;
|
|
|
+ case "DT_INT64":
|
|
|
+ case 9:
|
|
|
+ message.dtype = 9;
|
|
|
+ break;
|
|
|
+ case "DT_BOOL":
|
|
|
+ case 10:
|
|
|
+ message.dtype = 10;
|
|
|
+ break;
|
|
|
+ case "DT_QINT8":
|
|
|
+ case 11:
|
|
|
+ message.dtype = 11;
|
|
|
+ break;
|
|
|
+ case "DT_QUINT8":
|
|
|
+ case 12:
|
|
|
+ message.dtype = 12;
|
|
|
+ break;
|
|
|
+ case "DT_QINT32":
|
|
|
+ case 13:
|
|
|
+ message.dtype = 13;
|
|
|
+ break;
|
|
|
+ case "DT_BFLOAT16":
|
|
|
+ case 14:
|
|
|
+ message.dtype = 14;
|
|
|
+ break;
|
|
|
+ case "DT_QINT16":
|
|
|
+ case 15:
|
|
|
+ message.dtype = 15;
|
|
|
+ break;
|
|
|
+ case "DT_QUINT16":
|
|
|
+ case 16:
|
|
|
+ message.dtype = 16;
|
|
|
+ break;
|
|
|
+ case "DT_UINT16":
|
|
|
+ case 17:
|
|
|
+ message.dtype = 17;
|
|
|
+ break;
|
|
|
+ case "DT_COMPLEX128":
|
|
|
+ case 18:
|
|
|
+ message.dtype = 18;
|
|
|
+ break;
|
|
|
+ case "DT_HALF":
|
|
|
+ case 19:
|
|
|
+ message.dtype = 19;
|
|
|
+ break;
|
|
|
+ case "DT_RESOURCE":
|
|
|
+ case 20:
|
|
|
+ message.dtype = 20;
|
|
|
+ break;
|
|
|
+ case "DT_VARIANT":
|
|
|
+ case 21:
|
|
|
+ message.dtype = 21;
|
|
|
+ break;
|
|
|
+ case "DT_UINT32":
|
|
|
+ case 22:
|
|
|
+ message.dtype = 22;
|
|
|
+ break;
|
|
|
+ case "DT_UINT64":
|
|
|
+ case 23:
|
|
|
+ message.dtype = 23;
|
|
|
+ break;
|
|
|
+ case "DT_FLOAT_REF":
|
|
|
+ case 101:
|
|
|
+ message.dtype = 101;
|
|
|
+ break;
|
|
|
+ case "DT_DOUBLE_REF":
|
|
|
+ case 102:
|
|
|
+ message.dtype = 102;
|
|
|
+ break;
|
|
|
+ case "DT_INT32_REF":
|
|
|
+ case 103:
|
|
|
+ message.dtype = 103;
|
|
|
+ break;
|
|
|
+ case "DT_UINT8_REF":
|
|
|
+ case 104:
|
|
|
+ message.dtype = 104;
|
|
|
+ break;
|
|
|
+ case "DT_INT16_REF":
|
|
|
+ case 105:
|
|
|
+ message.dtype = 105;
|
|
|
+ break;
|
|
|
+ case "DT_INT8_REF":
|
|
|
+ case 106:
|
|
|
+ message.dtype = 106;
|
|
|
+ break;
|
|
|
+ case "DT_STRING_REF":
|
|
|
+ case 107:
|
|
|
+ message.dtype = 107;
|
|
|
+ break;
|
|
|
+ case "DT_COMPLEX64_REF":
|
|
|
+ case 108:
|
|
|
+ message.dtype = 108;
|
|
|
+ break;
|
|
|
+ case "DT_INT64_REF":
|
|
|
+ case 109:
|
|
|
+ message.dtype = 109;
|
|
|
+ break;
|
|
|
+ case "DT_BOOL_REF":
|
|
|
+ case 110:
|
|
|
+ message.dtype = 110;
|
|
|
+ break;
|
|
|
+ case "DT_QINT8_REF":
|
|
|
+ case 111:
|
|
|
+ message.dtype = 111;
|
|
|
+ break;
|
|
|
+ case "DT_QUINT8_REF":
|
|
|
+ case 112:
|
|
|
+ message.dtype = 112;
|
|
|
+ break;
|
|
|
+ case "DT_QINT32_REF":
|
|
|
+ case 113:
|
|
|
+ message.dtype = 113;
|
|
|
+ break;
|
|
|
+ case "DT_BFLOAT16_REF":
|
|
|
+ case 114:
|
|
|
+ message.dtype = 114;
|
|
|
+ break;
|
|
|
+ case "DT_QINT16_REF":
|
|
|
+ case 115:
|
|
|
+ message.dtype = 115;
|
|
|
+ break;
|
|
|
+ case "DT_QUINT16_REF":
|
|
|
+ case 116:
|
|
|
+ message.dtype = 116;
|
|
|
+ break;
|
|
|
+ case "DT_UINT16_REF":
|
|
|
+ case 117:
|
|
|
+ message.dtype = 117;
|
|
|
+ break;
|
|
|
+ case "DT_COMPLEX128_REF":
|
|
|
+ case 118:
|
|
|
+ message.dtype = 118;
|
|
|
+ break;
|
|
|
+ case "DT_HALF_REF":
|
|
|
+ case 119:
|
|
|
+ message.dtype = 119;
|
|
|
+ break;
|
|
|
+ case "DT_RESOURCE_REF":
|
|
|
+ case 120:
|
|
|
+ message.dtype = 120;
|
|
|
+ break;
|
|
|
+ case "DT_VARIANT_REF":
|
|
|
+ case 121:
|
|
|
+ message.dtype = 121;
|
|
|
+ break;
|
|
|
+ case "DT_UINT32_REF":
|
|
|
+ case 122:
|
|
|
+ message.dtype = 122;
|
|
|
+ break;
|
|
|
+ case "DT_UINT64_REF":
|
|
|
+ case 123:
|
|
|
+ message.dtype = 123;
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ return message;
|
|
|
+ };
|
|
|
+
|
|
|
+ TensorSpecProto.toObject = function toObject(message, options) {
|
|
|
+ if (!options)
|
|
|
+ options = {};
|
|
|
+ var object = {};
|
|
|
+ if (options.defaults) {
|
|
|
+ object.name = "";
|
|
|
+ object.shape = null;
|
|
|
+ object.dtype = options.enums === String ? "DT_INVALID" : 0;
|
|
|
+ }
|
|
|
+ if (message.name != null && message.hasOwnProperty("name"))
|
|
|
+ object.name = message.name;
|
|
|
+ if (message.shape != null && message.hasOwnProperty("shape"))
|
|
|
+ object.shape = $root.tensorflow.TensorShapeProto.toObject(message.shape, options);
|
|
|
+ if (message.dtype != null && message.hasOwnProperty("dtype"))
|
|
|
+ object.dtype = options.enums === String ? $root.tensorflow.DataType[message.dtype] : message.dtype;
|
|
|
+ return object;
|
|
|
+ };
|
|
|
+
|
|
|
+ TensorSpecProto.prototype.toJSON = function toJSON() {
|
|
|
+ return this.constructor.toObject(this, $protobuf.util.toJSONOptions);
|
|
|
+ };
|
|
|
+
|
|
|
+ return TensorSpecProto;
|
|
|
+ })();
|
|
|
+
|
|
|
return tensorflow;
|
|
|
})();
|
|
|
|
Lutz Roeder