# -*- coding: utf-8 -*- # Generated by the protocol buffer compiler. DO NOT EDIT! # source: Model.proto """Generated protocol buffer code.""" from google.protobuf import descriptor as _descriptor from google.protobuf import descriptor_pool as _descriptor_pool from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database # @@protoc_insertion_point(imports) _sym_db = _symbol_database.Default() from . import VisionFeaturePrint_pb2 as VisionFeaturePrint__pb2 from . import AudioFeaturePrint_pb2 as AudioFeaturePrint__pb2 from . import TextClassifier_pb2 as TextClassifier__pb2 try: DataStructures__pb2 = TextClassifier__pb2.DataStructures__pb2 except AttributeError: DataStructures__pb2 = TextClassifier__pb2.DataStructures_pb2 try: FeatureTypes__pb2 = TextClassifier__pb2.FeatureTypes__pb2 except AttributeError: FeatureTypes__pb2 = TextClassifier__pb2.FeatureTypes_pb2 from . import WordTagger_pb2 as WordTagger__pb2 try: DataStructures__pb2 = WordTagger__pb2.DataStructures__pb2 except AttributeError: DataStructures__pb2 = WordTagger__pb2.DataStructures_pb2 try: FeatureTypes__pb2 = WordTagger__pb2.FeatureTypes__pb2 except AttributeError: FeatureTypes__pb2 = WordTagger__pb2.FeatureTypes_pb2 from . import Gazetteer_pb2 as Gazetteer__pb2 try: DataStructures__pb2 = Gazetteer__pb2.DataStructures__pb2 except AttributeError: DataStructures__pb2 = Gazetteer__pb2.DataStructures_pb2 try: FeatureTypes__pb2 = Gazetteer__pb2.FeatureTypes__pb2 except AttributeError: FeatureTypes__pb2 = Gazetteer__pb2.FeatureTypes_pb2 from . import WordEmbedding_pb2 as WordEmbedding__pb2 try: DataStructures__pb2 = WordEmbedding__pb2.DataStructures__pb2 except AttributeError: DataStructures__pb2 = WordEmbedding__pb2.DataStructures_pb2 try: FeatureTypes__pb2 = WordEmbedding__pb2.FeatureTypes__pb2 except AttributeError: FeatureTypes__pb2 = WordEmbedding__pb2.FeatureTypes_pb2 from . import ArrayFeatureExtractor_pb2 as ArrayFeatureExtractor__pb2 from . import BayesianProbitRegressor_pb2 as BayesianProbitRegressor__pb2 from . import CategoricalMapping_pb2 as CategoricalMapping__pb2 try: DataStructures__pb2 = CategoricalMapping__pb2.DataStructures__pb2 except AttributeError: DataStructures__pb2 = CategoricalMapping__pb2.DataStructures_pb2 try: FeatureTypes__pb2 = CategoricalMapping__pb2.FeatureTypes__pb2 except AttributeError: FeatureTypes__pb2 = CategoricalMapping__pb2.FeatureTypes_pb2 from . import CustomModel_pb2 as CustomModel__pb2 from . import DictVectorizer_pb2 as DictVectorizer__pb2 try: DataStructures__pb2 = DictVectorizer__pb2.DataStructures__pb2 except AttributeError: DataStructures__pb2 = DictVectorizer__pb2.DataStructures_pb2 try: FeatureTypes__pb2 = DictVectorizer__pb2.FeatureTypes__pb2 except AttributeError: FeatureTypes__pb2 = DictVectorizer__pb2.FeatureTypes_pb2 from . import FeatureTypes_pb2 as FeatureTypes__pb2 from . import FeatureVectorizer_pb2 as FeatureVectorizer__pb2 from . import GLMRegressor_pb2 as GLMRegressor__pb2 from . import GLMClassifier_pb2 as GLMClassifier__pb2 try: DataStructures__pb2 = GLMClassifier__pb2.DataStructures__pb2 except AttributeError: DataStructures__pb2 = GLMClassifier__pb2.DataStructures_pb2 try: FeatureTypes__pb2 = GLMClassifier__pb2.FeatureTypes__pb2 except AttributeError: FeatureTypes__pb2 = GLMClassifier__pb2.FeatureTypes_pb2 from . import NearestNeighbors_pb2 as NearestNeighbors__pb2 try: DataStructures__pb2 = NearestNeighbors__pb2.DataStructures__pb2 except AttributeError: DataStructures__pb2 = NearestNeighbors__pb2.DataStructures_pb2 try: FeatureTypes__pb2 = NearestNeighbors__pb2.FeatureTypes__pb2 except AttributeError: FeatureTypes__pb2 = NearestNeighbors__pb2.FeatureTypes_pb2 try: Parameters__pb2 = NearestNeighbors__pb2.Parameters__pb2 except AttributeError: Parameters__pb2 = NearestNeighbors__pb2.Parameters_pb2 try: DataStructures__pb2 = NearestNeighbors__pb2.DataStructures__pb2 except AttributeError: DataStructures__pb2 = NearestNeighbors__pb2.DataStructures_pb2 try: FeatureTypes__pb2 = NearestNeighbors__pb2.FeatureTypes__pb2 except AttributeError: FeatureTypes__pb2 = NearestNeighbors__pb2.FeatureTypes_pb2 from . import Identity_pb2 as Identity__pb2 from . import Imputer_pb2 as Imputer__pb2 try: DataStructures__pb2 = Imputer__pb2.DataStructures__pb2 except AttributeError: DataStructures__pb2 = Imputer__pb2.DataStructures_pb2 try: FeatureTypes__pb2 = Imputer__pb2.FeatureTypes__pb2 except AttributeError: FeatureTypes__pb2 = Imputer__pb2.FeatureTypes_pb2 from . import MIL_pb2 as MIL__pb2 from . import NeuralNetwork_pb2 as NeuralNetwork__pb2 try: DataStructures__pb2 = NeuralNetwork__pb2.DataStructures__pb2 except AttributeError: DataStructures__pb2 = NeuralNetwork__pb2.DataStructures_pb2 try: FeatureTypes__pb2 = NeuralNetwork__pb2.FeatureTypes__pb2 except AttributeError: FeatureTypes__pb2 = NeuralNetwork__pb2.FeatureTypes_pb2 try: Parameters__pb2 = NeuralNetwork__pb2.Parameters__pb2 except AttributeError: Parameters__pb2 = NeuralNetwork__pb2.Parameters_pb2 try: DataStructures__pb2 = NeuralNetwork__pb2.DataStructures__pb2 except AttributeError: DataStructures__pb2 = NeuralNetwork__pb2.DataStructures_pb2 try: FeatureTypes__pb2 = NeuralNetwork__pb2.FeatureTypes__pb2 except AttributeError: FeatureTypes__pb2 = NeuralNetwork__pb2.FeatureTypes_pb2 from . import Normalizer_pb2 as Normalizer__pb2 from . import OneHotEncoder_pb2 as OneHotEncoder__pb2 try: DataStructures__pb2 = OneHotEncoder__pb2.DataStructures__pb2 except AttributeError: DataStructures__pb2 = OneHotEncoder__pb2.DataStructures_pb2 try: FeatureTypes__pb2 = OneHotEncoder__pb2.FeatureTypes__pb2 except AttributeError: FeatureTypes__pb2 = OneHotEncoder__pb2.FeatureTypes_pb2 from . import Scaler_pb2 as Scaler__pb2 from . import NonMaximumSuppression_pb2 as NonMaximumSuppression__pb2 try: DataStructures__pb2 = NonMaximumSuppression__pb2.DataStructures__pb2 except AttributeError: DataStructures__pb2 = NonMaximumSuppression__pb2.DataStructures_pb2 try: FeatureTypes__pb2 = NonMaximumSuppression__pb2.FeatureTypes__pb2 except AttributeError: FeatureTypes__pb2 = NonMaximumSuppression__pb2.FeatureTypes_pb2 from . import SVM_pb2 as SVM__pb2 try: DataStructures__pb2 = SVM__pb2.DataStructures__pb2 except AttributeError: DataStructures__pb2 = SVM__pb2.DataStructures_pb2 try: FeatureTypes__pb2 = SVM__pb2.FeatureTypes__pb2 except AttributeError: FeatureTypes__pb2 = SVM__pb2.FeatureTypes_pb2 from . import TreeEnsemble_pb2 as TreeEnsemble__pb2 try: DataStructures__pb2 = TreeEnsemble__pb2.DataStructures__pb2 except AttributeError: DataStructures__pb2 = TreeEnsemble__pb2.DataStructures_pb2 try: FeatureTypes__pb2 = TreeEnsemble__pb2.FeatureTypes__pb2 except AttributeError: FeatureTypes__pb2 = TreeEnsemble__pb2.FeatureTypes_pb2 from . import Parameters_pb2 as Parameters__pb2 try: DataStructures__pb2 = Parameters__pb2.DataStructures__pb2 except AttributeError: DataStructures__pb2 = Parameters__pb2.DataStructures_pb2 try: FeatureTypes__pb2 = Parameters__pb2.FeatureTypes__pb2 except AttributeError: FeatureTypes__pb2 = Parameters__pb2.FeatureTypes_pb2 from . import ItemSimilarityRecommender_pb2 as ItemSimilarityRecommender__pb2 try: DataStructures__pb2 = ItemSimilarityRecommender__pb2.DataStructures__pb2 except AttributeError: DataStructures__pb2 = ItemSimilarityRecommender__pb2.DataStructures_pb2 try: FeatureTypes__pb2 = ItemSimilarityRecommender__pb2.FeatureTypes__pb2 except AttributeError: FeatureTypes__pb2 = ItemSimilarityRecommender__pb2.FeatureTypes_pb2 from . import SoundAnalysisPreprocessing_pb2 as SoundAnalysisPreprocessing__pb2 from . import LinkedModel_pb2 as LinkedModel__pb2 try: Parameters__pb2 = LinkedModel__pb2.Parameters__pb2 except AttributeError: Parameters__pb2 = LinkedModel__pb2.Parameters_pb2 try: DataStructures__pb2 = LinkedModel__pb2.DataStructures__pb2 except AttributeError: DataStructures__pb2 = LinkedModel__pb2.DataStructures_pb2 try: FeatureTypes__pb2 = LinkedModel__pb2.FeatureTypes__pb2 except AttributeError: FeatureTypes__pb2 = LinkedModel__pb2.FeatureTypes_pb2 from . import ClassConfidenceThresholding_pb2 as ClassConfidenceThresholding__pb2 try: DataStructures__pb2 = ClassConfidenceThresholding__pb2.DataStructures__pb2 except AttributeError: DataStructures__pb2 = ClassConfidenceThresholding__pb2.DataStructures_pb2 try: FeatureTypes__pb2 = ClassConfidenceThresholding__pb2.FeatureTypes__pb2 except AttributeError: FeatureTypes__pb2 = ClassConfidenceThresholding__pb2.FeatureTypes_pb2 from .VisionFeaturePrint_pb2 import * from .AudioFeaturePrint_pb2 import * from .TextClassifier_pb2 import * from .WordTagger_pb2 import * from .Gazetteer_pb2 import * from .WordEmbedding_pb2 import * from .ArrayFeatureExtractor_pb2 import * from .BayesianProbitRegressor_pb2 import * from .CategoricalMapping_pb2 import * from .CustomModel_pb2 import * from .DictVectorizer_pb2 import * from .FeatureTypes_pb2 import * from .FeatureVectorizer_pb2 import * from .GLMRegressor_pb2 import * from .GLMClassifier_pb2 import * from .NearestNeighbors_pb2 import * from .Identity_pb2 import * from .Imputer_pb2 import * from .MIL_pb2 import * from .NeuralNetwork_pb2 import * from .Normalizer_pb2 import * from .OneHotEncoder_pb2 import * from .Scaler_pb2 import * from .NonMaximumSuppression_pb2 import * from .SVM_pb2 import * from .TreeEnsemble_pb2 import * from .Parameters_pb2 import * from .ItemSimilarityRecommender_pb2 import * from .SoundAnalysisPreprocessing_pb2 import * from .LinkedModel_pb2 import * from .ClassConfidenceThresholding_pb2 import * DESCRIPTOR = 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SoundAnalysisPreprocessing.proto\x1a\x11LinkedModel.proto\x1a!ClassConfidenceThresholding.proto\"F\n\x08Pipeline\x12+\n\x06models\x18\x01 \x03(\x0b\x32\x1b.CoreML.Specification.Model\x12\r\n\x05names\x18\x02 \x03(\t\"F\n\x12PipelineClassifier\x12\x30\n\x08pipeline\x18\x01 \x01(\x0b\x32\x1e.CoreML.Specification.Pipeline\"E\n\x11PipelineRegressor\x12\x30\n\x08pipeline\x18\x01 \x01(\x0b\x32\x1e.CoreML.Specification.Pipeline\"m\n\x12\x46\x65\x61tureDescription\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x18\n\x10shortDescription\x18\x02 \x01(\t\x12/\n\x04type\x18\x03 \x01(\x0b\x32!.CoreML.Specification.FeatureType\"\xd6\x01\n\x08Metadata\x12\x18\n\x10shortDescription\x18\x01 \x01(\t\x12\x15\n\rversionString\x18\x02 \x01(\t\x12\x0e\n\x06\x61uthor\x18\x03 \x01(\t\x12\x0f\n\x07license\x18\x04 \x01(\t\x12\x44\n\x0buserDefined\x18\x64 \x03(\x0b\x32/.CoreML.Specification.Metadata.UserDefinedEntry\x1a\x32\n\x10UserDefinedEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 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\x01(\x0b\x32/.CoreML.Specification.ItemSimilarityRecommenderH\x00\x12;\n\tmlProgram\x18\xf6\x03 \x01(\x0b\x32%.CoreML.Specification.MILSpec.ProgramH\x00\x12\x39\n\x0b\x63ustomModel\x18\xab\x04 \x01(\x0b\x32!.CoreML.Specification.CustomModelH\x00\x12\x39\n\x0blinkedModel\x18\xac\x04 \x01(\x0b\x32!.CoreML.Specification.LinkedModelH\x00\x12Y\n\x1b\x63lassConfidenceThresholding\x18\xb0\x04 \x01(\x0b\x32\x31.CoreML.Specification.ClassConfidenceThresholdingH\x00\x12=\n\roneHotEncoder\x18\xd8\x04 \x01(\x0b\x32#.CoreML.Specification.OneHotEncoderH\x00\x12\x31\n\x07imputer\x18\xd9\x04 \x01(\x0b\x32\x1d.CoreML.Specification.ImputerH\x00\x12\x45\n\x11\x66\x65\x61tureVectorizer\x18\xda\x04 \x01(\x0b\x32\'.CoreML.Specification.FeatureVectorizerH\x00\x12?\n\x0e\x64ictVectorizer\x18\xdb\x04 \x01(\x0b\x32$.CoreML.Specification.DictVectorizerH\x00\x12/\n\x06scaler\x18\xdc\x04 \x01(\x0b\x32\x1c.CoreML.Specification.ScalerH\x00\x12G\n\x12\x63\x61tegoricalMapping\x18\xde\x04 \x01(\x0b\x32(.CoreML.Specification.CategoricalMappingH\x00\x12\x37\n\nnormalizer\x18\xdf\x04 \x01(\x0b\x32 .CoreML.Specification.NormalizerH\x00\x12M\n\x15\x61rrayFeatureExtractor\x18\xe1\x04 \x01(\x0b\x32+.CoreML.Specification.ArrayFeatureExtractorH\x00\x12M\n\x15nonMaximumSuppression\x18\xe2\x04 \x01(\x0b\x32+.CoreML.Specification.NonMaximumSuppressionH\x00\x12\x33\n\x08identity\x18\x84\x07 \x01(\x0b\x32\x1e.CoreML.Specification.IdentityH\x00\x12L\n\x0etextClassifier\x18\xd0\x0f \x01(\x0b\x32\x31.CoreML.Specification.CoreMLModels.TextClassifierH\x00\x12\x44\n\nwordTagger\x18\xd1\x0f \x01(\x0b\x32-.CoreML.Specification.CoreMLModels.WordTaggerH\x00\x12T\n\x12visionFeaturePrint\x18\xd2\x0f \x01(\x0b\x32\x35.CoreML.Specification.CoreMLModels.VisionFeaturePrintH\x00\x12\x64\n\x1asoundAnalysisPreprocessing\x18\xd3\x0f \x01(\x0b\x32=.CoreML.Specification.CoreMLModels.SoundAnalysisPreprocessingH\x00\x12\x42\n\tgazetteer\x18\xd4\x0f \x01(\x0b\x32,.CoreML.Specification.CoreMLModels.GazetteerH\x00\x12J\n\rwordEmbedding\x18\xd5\x0f \x01(\x0b\x32\x30.CoreML.Specification.CoreMLModels.WordEmbeddingH\x00\x12R\n\x11\x61udioFeaturePrint\x18\xd6\x0f \x01(\x0b\x32\x34.CoreML.Specification.CoreMLModels.AudioFeaturePrintH\x00\x12\x41\n\x0fserializedModel\x18\xb8\x17 \x01(\x0b\x32%.CoreML.Specification.SerializedModelH\x00\x42\x06\n\x04TypeB\x02H\x03P\x00P\x01P\x02P\x03P\x04P\x05P\x06P\x07P\x08P\tP\nP\x0bP\x0cP\rP\x0eP\x0fP\x10P\x11P\x12P\x13P\x14P\x15P\x16P\x17P\x18P\x19P\x1aP\x1bP\x1cP\x1dP\x1e\x62\x06proto3') _PIPELINE = DESCRIPTOR.message_types_by_name['Pipeline'] _PIPELINECLASSIFIER = DESCRIPTOR.message_types_by_name['PipelineClassifier'] _PIPELINEREGRESSOR = DESCRIPTOR.message_types_by_name['PipelineRegressor'] _FEATUREDESCRIPTION = DESCRIPTOR.message_types_by_name['FeatureDescription'] _METADATA = DESCRIPTOR.message_types_by_name['Metadata'] _METADATA_USERDEFINEDENTRY = _METADATA.nested_types_by_name['UserDefinedEntry'] _FUNCTIONDESCRIPTION = DESCRIPTOR.message_types_by_name['FunctionDescription'] _MODELDESCRIPTION = DESCRIPTOR.message_types_by_name['ModelDescription'] _SERIALIZEDMODEL = DESCRIPTOR.message_types_by_name['SerializedModel'] _MODEL = DESCRIPTOR.message_types_by_name['Model'] Pipeline = _reflection.GeneratedProtocolMessageType('Pipeline', (_message.Message,), { 'DESCRIPTOR' : _PIPELINE, '__module__' : 'Model_pb2' # @@protoc_insertion_point(class_scope:CoreML.Specification.Pipeline) }) _sym_db.RegisterMessage(Pipeline) PipelineClassifier = _reflection.GeneratedProtocolMessageType('PipelineClassifier', (_message.Message,), { 'DESCRIPTOR' : _PIPELINECLASSIFIER, '__module__' : 'Model_pb2' # @@protoc_insertion_point(class_scope:CoreML.Specification.PipelineClassifier) }) _sym_db.RegisterMessage(PipelineClassifier) PipelineRegressor = _reflection.GeneratedProtocolMessageType('PipelineRegressor', (_message.Message,), { 'DESCRIPTOR' : _PIPELINEREGRESSOR, '__module__' : 'Model_pb2' # @@protoc_insertion_point(class_scope:CoreML.Specification.PipelineRegressor) }) _sym_db.RegisterMessage(PipelineRegressor) FeatureDescription = _reflection.GeneratedProtocolMessageType('FeatureDescription', (_message.Message,), { 'DESCRIPTOR' : _FEATUREDESCRIPTION, '__module__' : 'Model_pb2' # @@protoc_insertion_point(class_scope:CoreML.Specification.FeatureDescription) }) _sym_db.RegisterMessage(FeatureDescription) Metadata = _reflection.GeneratedProtocolMessageType('Metadata', (_message.Message,), { 'UserDefinedEntry' : _reflection.GeneratedProtocolMessageType('UserDefinedEntry', (_message.Message,), { 'DESCRIPTOR' : _METADATA_USERDEFINEDENTRY, '__module__' : 'Model_pb2' # @@protoc_insertion_point(class_scope:CoreML.Specification.Metadata.UserDefinedEntry) }) , 'DESCRIPTOR' : _METADATA, '__module__' : 'Model_pb2' # @@protoc_insertion_point(class_scope:CoreML.Specification.Metadata) }) _sym_db.RegisterMessage(Metadata) _sym_db.RegisterMessage(Metadata.UserDefinedEntry) FunctionDescription = _reflection.GeneratedProtocolMessageType('FunctionDescription', (_message.Message,), { 'DESCRIPTOR' : _FUNCTIONDESCRIPTION, '__module__' : 'Model_pb2' # @@protoc_insertion_point(class_scope:CoreML.Specification.FunctionDescription) }) _sym_db.RegisterMessage(FunctionDescription) ModelDescription = _reflection.GeneratedProtocolMessageType('ModelDescription', (_message.Message,), { 'DESCRIPTOR' : _MODELDESCRIPTION, '__module__' : 'Model_pb2' # @@protoc_insertion_point(class_scope:CoreML.Specification.ModelDescription) }) _sym_db.RegisterMessage(ModelDescription) SerializedModel = _reflection.GeneratedProtocolMessageType('SerializedModel', (_message.Message,), { 'DESCRIPTOR' : _SERIALIZEDMODEL, '__module__' : 'Model_pb2' # @@protoc_insertion_point(class_scope:CoreML.Specification.SerializedModel) }) _sym_db.RegisterMessage(SerializedModel) Model = _reflection.GeneratedProtocolMessageType('Model', (_message.Message,), { 'DESCRIPTOR' : _MODEL, '__module__' : 'Model_pb2' # @@protoc_insertion_point(class_scope:CoreML.Specification.Model) }) _sym_db.RegisterMessage(Model) if _descriptor._USE_C_DESCRIPTORS == False: DESCRIPTOR._options = None DESCRIPTOR._serialized_options = b'H\003' _METADATA_USERDEFINEDENTRY._options = None _METADATA_USERDEFINEDENTRY._serialized_options = b'8\001' _PIPELINE._serialized_start=718 _PIPELINE._serialized_end=788 _PIPELINECLASSIFIER._serialized_start=790 _PIPELINECLASSIFIER._serialized_end=860 _PIPELINEREGRESSOR._serialized_start=862 _PIPELINEREGRESSOR._serialized_end=931 _FEATUREDESCRIPTION._serialized_start=933 _FEATUREDESCRIPTION._serialized_end=1042 _METADATA._serialized_start=1045 _METADATA._serialized_end=1259 _METADATA_USERDEFINEDENTRY._serialized_start=1209 _METADATA_USERDEFINEDENTRY._serialized_end=1259 _FUNCTIONDESCRIPTION._serialized_start=1262 _FUNCTIONDESCRIPTION._serialized_end=1535 _MODELDESCRIPTION._serialized_start=1538 _MODELDESCRIPTION._serialized_end=2000 _SERIALIZEDMODEL._serialized_start=2002 _SERIALIZEDMODEL._serialized_end=2054 _MODEL._serialized_start=2057 _MODEL._serialized_end=4858 # @@protoc_insertion_point(module_scope)