# -*- 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 = _descriptor_pool.Default().AddSerializedFile(b'\n\x0bModel.proto\x12\x14\x43oreML.Specification\x1a\x18VisionFeaturePrint.proto\x1a\x17\x41udioFeaturePrint.proto\x1a\x14TextClassifier.proto\x1a\x10WordTagger.proto\x1a\x0fGazetteer.proto\x1a\x13WordEmbedding.proto\x1a\x1b\x41rrayFeatureExtractor.proto\x1a\x1d\x42\x61yesianProbitRegressor.proto\x1a\x18\x43\x61tegoricalMapping.proto\x1a\x11\x43ustomModel.proto\x1a\x14\x44ictVectorizer.proto\x1a\x12\x46\x65\x61tureTypes.proto\x1a\x17\x46\x65\x61tureVectorizer.proto\x1a\x12GLMRegressor.proto\x1a\x13GLMClassifier.proto\x1a\x16NearestNeighbors.proto\x1a\x0eIdentity.proto\x1a\rImputer.proto\x1a\tMIL.proto\x1a\x13NeuralNetwork.proto\x1a\x10Normalizer.proto\x1a\x13OneHotEncoder.proto\x1a\x0cScaler.proto\x1a\x1bNonMaximumSuppression.proto\x1a\tSVM.proto\x1a\x12TreeEnsemble.proto\x1a\x10Parameters.proto\x1a\x1fItemSimilarityRecommender.proto\x1a 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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_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)
