# -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler.  DO NOT EDIT!
# source: google/cloud/bigquery_v2/proto/model.proto

import sys

_b = sys.version_info[0] < 3 and (lambda x: x) or (lambda x: x.encode("latin1"))
from google.protobuf import descriptor as _descriptor
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 google.cloud.bigquery_v2.proto import (
    model_reference_pb2 as google_dot_cloud_dot_bigquery__v2_dot_proto_dot_model__reference__pb2,
)
from google.cloud.bigquery_v2.proto import (
    standard_sql_pb2 as google_dot_cloud_dot_bigquery__v2_dot_proto_dot_standard__sql__pb2,
)
from google.protobuf import empty_pb2 as google_dot_protobuf_dot_empty__pb2
from google.protobuf import timestamp_pb2 as google_dot_protobuf_dot_timestamp__pb2
from google.protobuf import wrappers_pb2 as google_dot_protobuf_dot_wrappers__pb2
from google.api import annotations_pb2 as google_dot_api_dot_annotations__pb2
from google.api import client_pb2 as google_dot_api_dot_client__pb2


DESCRIPTOR = _descriptor.FileDescriptor(
    name="google/cloud/bigquery_v2/proto/model.proto",
    package="google.cloud.bigquery.v2",
    syntax="proto3",
    serialized_options=_b(
        "\n\034com.google.cloud.bigquery.v2B\nModelProtoZ@google.golang.org/genproto/googleapis/cloud/bigquery/v2;bigquery"
    ),
    serialized_pb=_b(
        '\n*google/cloud/bigquery_v2/proto/model.proto\x12\x18google.cloud.bigquery.v2\x1a\x34google/cloud/bigquery_v2/proto/model_reference.proto\x1a\x31google/cloud/bigquery_v2/proto/standard_sql.proto\x1a\x1bgoogle/protobuf/empty.proto\x1a\x1fgoogle/protobuf/timestamp.proto\x1a\x1egoogle/protobuf/wrappers.proto\x1a\x1cgoogle/api/annotations.proto\x1a\x17google/api/client.proto"\x8a\x34\n\x05Model\x12\x0c\n\x04\x65tag\x18\x01 \x01(\t\x12\x41\n\x0fmodel_reference\x18\x02 \x01(\x0b\x32(.google.cloud.bigquery.v2.ModelReference\x12\x15\n\rcreation_time\x18\x05 \x01(\x03\x12\x1a\n\x12last_modified_time\x18\x06 \x01(\x03\x12\x13\n\x0b\x64\x65scription\x18\x0c \x01(\t\x12\x15\n\rfriendly_name\x18\x0e \x01(\t\x12;\n\x06labels\x18\x0f \x03(\x0b\x32+.google.cloud.bigquery.v2.Model.LabelsEntry\x12\x17\n\x0f\x65xpiration_time\x18\x10 \x01(\x03\x12\x10\n\x08location\x18\r \x01(\t\x12=\n\nmodel_type\x18\x07 \x01(\x0e\x32).google.cloud.bigquery.v2.Model.ModelType\x12\x42\n\rtraining_runs\x18\t \x03(\x0b\x32+.google.cloud.bigquery.v2.Model.TrainingRun\x12\x43\n\x0f\x66\x65\x61ture_columns\x18\n \x03(\x0b\x32*.google.cloud.bigquery.v2.StandardSqlField\x12\x41\n\rlabel_columns\x18\x0b \x03(\x0b\x32*.google.cloud.bigquery.v2.StandardSqlField\x1aq\n\x0bKmeansEnums"b\n\x1aKmeansInitializationMethod\x12,\n(KMEANS_INITIALIZATION_METHOD_UNSPECIFIED\x10\x00\x12\n\n\x06RANDOM\x10\x01\x12\n\n\x06\x43USTOM\x10\x02\x1a\xb4\x02\n\x11RegressionMetrics\x12\x39\n\x13mean_absolute_error\x18\x01 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12\x38\n\x12mean_squared_error\x18\x02 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12<\n\x16mean_squared_log_error\x18\x03 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12;\n\x15median_absolute_error\x18\x04 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12/\n\tr_squared\x18\x05 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x1a\xef\x02\n\x1e\x41ggregateClassificationMetrics\x12/\n\tprecision\x18\x01 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12,\n\x06recall\x18\x02 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12.\n\x08\x61\x63\x63uracy\x18\x03 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12/\n\tthreshold\x18\x04 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12.\n\x08\x66\x31_score\x18\x05 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12.\n\x08log_loss\x18\x06 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12-\n\x07roc_auc\x18\x07 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x1a\x9f\x06\n\x1b\x42inaryClassificationMetrics\x12h\n aggregate_classification_metrics\x18\x01 \x01(\x0b\x32>.google.cloud.bigquery.v2.Model.AggregateClassificationMetrics\x12w\n\x1c\x62inary_confusion_matrix_list\x18\x02 \x03(\x0b\x32Q.google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix\x12\x16\n\x0epositive_label\x18\x03 \x01(\t\x12\x16\n\x0enegative_label\x18\x04 \x01(\t\x1a\xec\x03\n\x15\x42inaryConfusionMatrix\x12>\n\x18positive_class_threshold\x18\x01 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12\x33\n\x0etrue_positives\x18\x02 \x01(\x0b\x32\x1b.google.protobuf.Int64Value\x12\x34\n\x0f\x66\x61lse_positives\x18\x03 \x01(\x0b\x32\x1b.google.protobuf.Int64Value\x12\x33\n\x0etrue_negatives\x18\x04 \x01(\x0b\x32\x1b.google.protobuf.Int64Value\x12\x34\n\x0f\x66\x61lse_negatives\x18\x05 \x01(\x0b\x32\x1b.google.protobuf.Int64Value\x12/\n\tprecision\x18\x06 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12,\n\x06recall\x18\x07 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12.\n\x08\x66\x31_score\x18\x08 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12.\n\x08\x61\x63\x63uracy\x18\t \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x1a\x87\x05\n\x1fMultiClassClassificationMetrics\x12h\n aggregate_classification_metrics\x18\x01 \x01(\x0b\x32>.google.cloud.bigquery.v2.Model.AggregateClassificationMetrics\x12n\n\x15\x63onfusion_matrix_list\x18\x02 \x03(\x0b\x32O.google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix\x1a\x89\x03\n\x0f\x43onfusionMatrix\x12:\n\x14\x63onfidence_threshold\x18\x01 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12\x61\n\x04rows\x18\x02 \x03(\x0b\x32S.google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix.Row\x1aQ\n\x05\x45ntry\x12\x17\n\x0fpredicted_label\x18\x01 \x01(\t\x12/\n\nitem_count\x18\x02 \x01(\x0b\x32\x1b.google.protobuf.Int64Value\x1a\x83\x01\n\x03Row\x12\x14\n\x0c\x61\x63tual_label\x18\x01 \x01(\t\x12\x66\n\x07\x65ntries\x18\x02 \x03(\x0b\x32U.google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix.Entry\x1a\xcb\x06\n\x11\x43lusteringMetrics\x12:\n\x14\x64\x61vies_bouldin_index\x18\x01 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12;\n\x15mean_squared_distance\x18\x02 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12K\n\x08\x63lusters\x18\x03 \x03(\x0b\x32\x39.google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster\x1a\xef\x04\n\x07\x43luster\x12\x13\n\x0b\x63\x65ntroid_id\x18\x01 \x01(\x03\x12^\n\x0e\x66\x65\x61ture_values\x18\x02 \x03(\x0b\x32\x46.google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue\x12*\n\x05\x63ount\x18\x03 \x01(\x0b\x32\x1b.google.protobuf.Int64Value\x1a\xc2\x03\n\x0c\x46\x65\x61tureValue\x12\x16\n\x0e\x66\x65\x61ture_column\x18\x01 \x01(\t\x12\x37\n\x0fnumerical_value\x18\x02 \x01(\x0b\x32\x1c.google.protobuf.DoubleValueH\x00\x12t\n\x11\x63\x61tegorical_value\x18\x03 \x01(\x0b\x32W.google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValueH\x00\x1a\xe1\x01\n\x10\x43\x61tegoricalValue\x12~\n\x0f\x63\x61tegory_counts\x18\x01 \x03(\x0b\x32\x65.google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue.CategoryCount\x1aM\n\rCategoryCount\x12\x10\n\x08\x63\x61tegory\x18\x01 \x01(\t\x12*\n\x05\x63ount\x18\x02 \x01(\x0b\x32\x1b.google.protobuf.Int64ValueB\x07\n\x05value\x1a\x95\x03\n\x11\x45valuationMetrics\x12O\n\x12regression_metrics\x18\x01 \x01(\x0b\x32\x31.google.cloud.bigquery.v2.Model.RegressionMetricsH\x00\x12\x64\n\x1d\x62inary_classification_metrics\x18\x02 \x01(\x0b\x32;.google.cloud.bigquery.v2.Model.BinaryClassificationMetricsH\x00\x12m\n"multi_class_classification_metrics\x18\x03 \x01(\x0b\x32?.google.cloud.bigquery.v2.Model.MultiClassClassificationMetricsH\x00\x12O\n\x12\x63lustering_metrics\x18\x04 \x01(\x0b\x32\x31.google.cloud.bigquery.v2.Model.ClusteringMetricsH\x00\x42\t\n\x07metrics\x1a\xab\x0f\n\x0bTrainingRun\x12U\n\x10training_options\x18\x01 \x01(\x0b\x32;.google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions\x12.\n\nstart_time\x18\x08 \x01(\x0b\x32\x1a.google.protobuf.Timestamp\x12L\n\x07results\x18\x06 \x03(\x0b\x32;.google.cloud.bigquery.v2.Model.TrainingRun.IterationResult\x12M\n\x12\x65valuation_metrics\x18\x07 \x01(\x0b\x32\x31.google.cloud.bigquery.v2.Model.EvaluationMetrics\x1a\x9d\t\n\x0fTrainingOptions\x12\x16\n\x0emax_iterations\x18\x01 \x01(\x03\x12;\n\tloss_type\x18\x02 \x01(\x0e\x32(.google.cloud.bigquery.v2.Model.LossType\x12\x12\n\nlearn_rate\x18\x03 \x01(\x01\x12\x37\n\x11l1_regularization\x18\x04 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12\x37\n\x11l2_regularization\x18\x05 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12;\n\x15min_relative_progress\x18\x06 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12.\n\nwarm_start\x18\x07 \x01(\x0b\x32\x1a.google.protobuf.BoolValue\x12.\n\nearly_stop\x18\x08 \x01(\x0b\x32\x1a.google.protobuf.BoolValue\x12\x1b\n\x13input_label_columns\x18\t \x03(\t\x12J\n\x11\x64\x61ta_split_method\x18\n \x01(\x0e\x32/.google.cloud.bigquery.v2.Model.DataSplitMethod\x12 \n\x18\x64\x61ta_split_eval_fraction\x18\x0b \x01(\x01\x12\x19\n\x11\x64\x61ta_split_column\x18\x0c \x01(\t\x12N\n\x13learn_rate_strategy\x18\r \x01(\x0e\x32\x31.google.cloud.bigquery.v2.Model.LearnRateStrategy\x12\x1a\n\x12initial_learn_rate\x18\x10 \x01(\x01\x12o\n\x13label_class_weights\x18\x11 \x03(\x0b\x32R.google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.LabelClassWeightsEntry\x12\x43\n\rdistance_type\x18\x14 \x01(\x0e\x32,.google.cloud.bigquery.v2.Model.DistanceType\x12\x14\n\x0cnum_clusters\x18\x15 \x01(\x03\x12\x11\n\tmodel_uri\x18\x16 \x01(\t\x12S\n\x15optimization_strategy\x18\x17 \x01(\x0e\x32\x34.google.cloud.bigquery.v2.Model.OptimizationStrategy\x12l\n\x1ckmeans_initialization_method\x18! \x01(\x0e\x32\x46.google.cloud.bigquery.v2.Model.KmeansEnums.KmeansInitializationMethod\x12$\n\x1ckmeans_initialization_column\x18" \x01(\t\x1a\x38\n\x16LabelClassWeightsEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\x01:\x02\x38\x01\x1a\xd7\x03\n\x0fIterationResult\x12*\n\x05index\x18\x01 \x01(\x0b\x32\x1b.google.protobuf.Int32Value\x12\x30\n\x0b\x64uration_ms\x18\x04 \x01(\x0b\x32\x1b.google.protobuf.Int64Value\x12\x33\n\rtraining_loss\x18\x05 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12/\n\teval_loss\x18\x06 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12\x12\n\nlearn_rate\x18\x07 \x01(\x01\x12^\n\rcluster_infos\x18\x08 \x03(\x0b\x32G.google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ClusterInfo\x1a\x8b\x01\n\x0b\x43lusterInfo\x12\x13\n\x0b\x63\x65ntroid_id\x18\x01 \x01(\x03\x12\x34\n\x0e\x63luster_radius\x18\x02 \x01(\x0b\x32\x1c.google.protobuf.DoubleValue\x12\x31\n\x0c\x63luster_size\x18\x03 \x01(\x0b\x32\x1b.google.protobuf.Int64Value\x1a-\n\x0bLabelsEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\t:\x02\x38\x01"s\n\tModelType\x12\x1a\n\x16MODEL_TYPE_UNSPECIFIED\x10\x00\x12\x15\n\x11LINEAR_REGRESSION\x10\x01\x12\x17\n\x13LOGISTIC_REGRESSION\x10\x02\x12\n\n\x06KMEANS\x10\x03\x12\x0e\n\nTENSORFLOW\x10\x06"O\n\x08LossType\x12\x19\n\x15LOSS_TYPE_UNSPECIFIED\x10\x00\x12\x15\n\x11MEAN_SQUARED_LOSS\x10\x01\x12\x11\n\rMEAN_LOG_LOSS\x10\x02"H\n\x0c\x44istanceType\x12\x1d\n\x19\x44ISTANCE_TYPE_UNSPECIFIED\x10\x00\x12\r\n\tEUCLIDEAN\x10\x01\x12\n\n\x06\x43OSINE\x10\x02"z\n\x0f\x44\x61taSplitMethod\x12!\n\x1d\x44\x41TA_SPLIT_METHOD_UNSPECIFIED\x10\x00\x12\n\n\x06RANDOM\x10\x01\x12\n\n\x06\x43USTOM\x10\x02\x12\x0e\n\nSEQUENTIAL\x10\x03\x12\x0c\n\x08NO_SPLIT\x10\x04\x12\x0e\n\nAUTO_SPLIT\x10\x05"W\n\x11LearnRateStrategy\x12#\n\x1fLEARN_RATE_STRATEGY_UNSPECIFIED\x10\x00\x12\x0f\n\x0bLINE_SEARCH\x10\x01\x12\x0c\n\x08\x43ONSTANT\x10\x02"n\n\x14OptimizationStrategy\x12%\n!OPTIMIZATION_STRATEGY_UNSPECIFIED\x10\x00\x12\x1a\n\x16\x42\x41TCH_GRADIENT_DESCENT\x10\x01\x12\x13\n\x0fNORMAL_EQUATION\x10\x02"K\n\x0fGetModelRequest\x12\x12\n\nproject_id\x18\x01 \x01(\t\x12\x12\n\ndataset_id\x18\x02 \x01(\t\x12\x10\n\x08model_id\x18\x03 \x01(\t"}\n\x11PatchModelRequest\x12\x12\n\nproject_id\x18\x01 \x01(\t\x12\x12\n\ndataset_id\x18\x02 \x01(\t\x12\x10\n\x08model_id\x18\x03 \x01(\t\x12.\n\x05model\x18\x04 \x01(\x0b\x32\x1f.google.cloud.bigquery.v2.Model"N\n\x12\x44\x65leteModelRequest\x12\x12\n\nproject_id\x18\x01 \x01(\t\x12\x12\n\ndataset_id\x18\x02 \x01(\t\x12\x10\n\x08model_id\x18\x03 \x01(\t"\x82\x01\n\x11ListModelsRequest\x12\x12\n\nproject_id\x18\x01 \x01(\t\x12\x12\n\ndataset_id\x18\x02 \x01(\t\x12\x31\n\x0bmax_results\x18\x03 \x01(\x0b\x32\x1c.google.protobuf.UInt32Value\x12\x12\n\npage_token\x18\x04 \x01(\t"^\n\x12ListModelsResponse\x12/\n\x06models\x18\x01 \x03(\x0b\x32\x1f.google.cloud.bigquery.v2.Model\x12\x17\n\x0fnext_page_token\x18\x02 \x01(\t2\xeb\x04\n\x0cModelService\x12X\n\x08GetModel\x12).google.cloud.bigquery.v2.GetModelRequest\x1a\x1f.google.cloud.bigquery.v2.Model"\x00\x12i\n\nListModels\x12+.google.cloud.bigquery.v2.ListModelsRequest\x1a,.google.cloud.bigquery.v2.ListModelsResponse"\x00\x12\\\n\nPatchModel\x12+.google.cloud.bigquery.v2.PatchModelRequest\x1a\x1f.google.cloud.bigquery.v2.Model"\x00\x12U\n\x0b\x44\x65leteModel\x12,.google.cloud.bigquery.v2.DeleteModelRequest\x1a\x16.google.protobuf.Empty"\x00\x1a\xe0\x01\xca\x41\x17\x62igquery.googleapis.com\xd2\x41\xc2\x01https://www.googleapis.com/auth/bigquery,https://www.googleapis.com/auth/bigquery.readonly,https://www.googleapis.com/auth/cloud-platform,https://www.googleapis.com/auth/cloud-platform.read-onlyBl\n\x1c\x63om.google.cloud.bigquery.v2B\nModelProtoZ@google.golang.org/genproto/googleapis/cloud/bigquery/v2;bigqueryb\x06proto3'
    ),
    dependencies=[
        google_dot_cloud_dot_bigquery__v2_dot_proto_dot_model__reference__pb2.DESCRIPTOR,
        google_dot_cloud_dot_bigquery__v2_dot_proto_dot_standard__sql__pb2.DESCRIPTOR,
        google_dot_protobuf_dot_empty__pb2.DESCRIPTOR,
        google_dot_protobuf_dot_timestamp__pb2.DESCRIPTOR,
        google_dot_protobuf_dot_wrappers__pb2.DESCRIPTOR,
        google_dot_api_dot_annotations__pb2.DESCRIPTOR,
        google_dot_api_dot_client__pb2.DESCRIPTOR,
    ],
)


_MODEL_KMEANSENUMS_KMEANSINITIALIZATIONMETHOD = _descriptor.EnumDescriptor(
    name="KmeansInitializationMethod",
    full_name="google.cloud.bigquery.v2.Model.KmeansEnums.KmeansInitializationMethod",
    filename=None,
    file=DESCRIPTOR,
    values=[
        _descriptor.EnumValueDescriptor(
            name="KMEANS_INITIALIZATION_METHOD_UNSPECIFIED",
            index=0,
            number=0,
            serialized_options=None,
            type=None,
        ),
        _descriptor.EnumValueDescriptor(
            name="RANDOM", index=1, number=1, serialized_options=None, type=None
        ),
        _descriptor.EnumValueDescriptor(
            name="CUSTOM", index=2, number=2, serialized_options=None, type=None
        ),
    ],
    containing_type=None,
    serialized_options=None,
    serialized_start=898,
    serialized_end=996,
)
_sym_db.RegisterEnumDescriptor(_MODEL_KMEANSENUMS_KMEANSINITIALIZATIONMETHOD)

_MODEL_MODELTYPE = _descriptor.EnumDescriptor(
    name="ModelType",
    full_name="google.cloud.bigquery.v2.Model.ModelType",
    filename=None,
    file=DESCRIPTOR,
    values=[
        _descriptor.EnumValueDescriptor(
            name="MODEL_TYPE_UNSPECIFIED",
            index=0,
            number=0,
            serialized_options=None,
            type=None,
        ),
        _descriptor.EnumValueDescriptor(
            name="LINEAR_REGRESSION",
            index=1,
            number=1,
            serialized_options=None,
            type=None,
        ),
        _descriptor.EnumValueDescriptor(
            name="LOGISTIC_REGRESSION",
            index=2,
            number=2,
            serialized_options=None,
            type=None,
        ),
        _descriptor.EnumValueDescriptor(
            name="KMEANS", index=3, number=3, serialized_options=None, type=None
        ),
        _descriptor.EnumValueDescriptor(
            name="TENSORFLOW", index=4, number=6, serialized_options=None, type=None
        ),
    ],
    containing_type=None,
    serialized_options=None,
    serialized_start=6398,
    serialized_end=6513,
)
_sym_db.RegisterEnumDescriptor(_MODEL_MODELTYPE)

_MODEL_LOSSTYPE = _descriptor.EnumDescriptor(
    name="LossType",
    full_name="google.cloud.bigquery.v2.Model.LossType",
    filename=None,
    file=DESCRIPTOR,
    values=[
        _descriptor.EnumValueDescriptor(
            name="LOSS_TYPE_UNSPECIFIED",
            index=0,
            number=0,
            serialized_options=None,
            type=None,
        ),
        _descriptor.EnumValueDescriptor(
            name="MEAN_SQUARED_LOSS",
            index=1,
            number=1,
            serialized_options=None,
            type=None,
        ),
        _descriptor.EnumValueDescriptor(
            name="MEAN_LOG_LOSS", index=2, number=2, serialized_options=None, type=None
        ),
    ],
    containing_type=None,
    serialized_options=None,
    serialized_start=6515,
    serialized_end=6594,
)
_sym_db.RegisterEnumDescriptor(_MODEL_LOSSTYPE)

_MODEL_DISTANCETYPE = _descriptor.EnumDescriptor(
    name="DistanceType",
    full_name="google.cloud.bigquery.v2.Model.DistanceType",
    filename=None,
    file=DESCRIPTOR,
    values=[
        _descriptor.EnumValueDescriptor(
            name="DISTANCE_TYPE_UNSPECIFIED",
            index=0,
            number=0,
            serialized_options=None,
            type=None,
        ),
        _descriptor.EnumValueDescriptor(
            name="EUCLIDEAN", index=1, number=1, serialized_options=None, type=None
        ),
        _descriptor.EnumValueDescriptor(
            name="COSINE", index=2, number=2, serialized_options=None, type=None
        ),
    ],
    containing_type=None,
    serialized_options=None,
    serialized_start=6596,
    serialized_end=6668,
)
_sym_db.RegisterEnumDescriptor(_MODEL_DISTANCETYPE)

_MODEL_DATASPLITMETHOD = _descriptor.EnumDescriptor(
    name="DataSplitMethod",
    full_name="google.cloud.bigquery.v2.Model.DataSplitMethod",
    filename=None,
    file=DESCRIPTOR,
    values=[
        _descriptor.EnumValueDescriptor(
            name="DATA_SPLIT_METHOD_UNSPECIFIED",
            index=0,
            number=0,
            serialized_options=None,
            type=None,
        ),
        _descriptor.EnumValueDescriptor(
            name="RANDOM", index=1, number=1, serialized_options=None, type=None
        ),
        _descriptor.EnumValueDescriptor(
            name="CUSTOM", index=2, number=2, serialized_options=None, type=None
        ),
        _descriptor.EnumValueDescriptor(
            name="SEQUENTIAL", index=3, number=3, serialized_options=None, type=None
        ),
        _descriptor.EnumValueDescriptor(
            name="NO_SPLIT", index=4, number=4, serialized_options=None, type=None
        ),
        _descriptor.EnumValueDescriptor(
            name="AUTO_SPLIT", index=5, number=5, serialized_options=None, type=None
        ),
    ],
    containing_type=None,
    serialized_options=None,
    serialized_start=6670,
    serialized_end=6792,
)
_sym_db.RegisterEnumDescriptor(_MODEL_DATASPLITMETHOD)

_MODEL_LEARNRATESTRATEGY = _descriptor.EnumDescriptor(
    name="LearnRateStrategy",
    full_name="google.cloud.bigquery.v2.Model.LearnRateStrategy",
    filename=None,
    file=DESCRIPTOR,
    values=[
        _descriptor.EnumValueDescriptor(
            name="LEARN_RATE_STRATEGY_UNSPECIFIED",
            index=0,
            number=0,
            serialized_options=None,
            type=None,
        ),
        _descriptor.EnumValueDescriptor(
            name="LINE_SEARCH", index=1, number=1, serialized_options=None, type=None
        ),
        _descriptor.EnumValueDescriptor(
            name="CONSTANT", index=2, number=2, serialized_options=None, type=None
        ),
    ],
    containing_type=None,
    serialized_options=None,
    serialized_start=6794,
    serialized_end=6881,
)
_sym_db.RegisterEnumDescriptor(_MODEL_LEARNRATESTRATEGY)

_MODEL_OPTIMIZATIONSTRATEGY = _descriptor.EnumDescriptor(
    name="OptimizationStrategy",
    full_name="google.cloud.bigquery.v2.Model.OptimizationStrategy",
    filename=None,
    file=DESCRIPTOR,
    values=[
        _descriptor.EnumValueDescriptor(
            name="OPTIMIZATION_STRATEGY_UNSPECIFIED",
            index=0,
            number=0,
            serialized_options=None,
            type=None,
        ),
        _descriptor.EnumValueDescriptor(
            name="BATCH_GRADIENT_DESCENT",
            index=1,
            number=1,
            serialized_options=None,
            type=None,
        ),
        _descriptor.EnumValueDescriptor(
            name="NORMAL_EQUATION",
            index=2,
            number=2,
            serialized_options=None,
            type=None,
        ),
    ],
    containing_type=None,
    serialized_options=None,
    serialized_start=6883,
    serialized_end=6993,
)
_sym_db.RegisterEnumDescriptor(_MODEL_OPTIMIZATIONSTRATEGY)


_MODEL_KMEANSENUMS = _descriptor.Descriptor(
    name="KmeansEnums",
    full_name="google.cloud.bigquery.v2.Model.KmeansEnums",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[],
    extensions=[],
    nested_types=[],
    enum_types=[_MODEL_KMEANSENUMS_KMEANSINITIALIZATIONMETHOD],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=883,
    serialized_end=996,
)

_MODEL_REGRESSIONMETRICS = _descriptor.Descriptor(
    name="RegressionMetrics",
    full_name="google.cloud.bigquery.v2.Model.RegressionMetrics",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="mean_absolute_error",
            full_name="google.cloud.bigquery.v2.Model.RegressionMetrics.mean_absolute_error",
            index=0,
            number=1,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="mean_squared_error",
            full_name="google.cloud.bigquery.v2.Model.RegressionMetrics.mean_squared_error",
            index=1,
            number=2,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="mean_squared_log_error",
            full_name="google.cloud.bigquery.v2.Model.RegressionMetrics.mean_squared_log_error",
            index=2,
            number=3,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="median_absolute_error",
            full_name="google.cloud.bigquery.v2.Model.RegressionMetrics.median_absolute_error",
            index=3,
            number=4,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="r_squared",
            full_name="google.cloud.bigquery.v2.Model.RegressionMetrics.r_squared",
            index=4,
            number=5,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=999,
    serialized_end=1307,
)

_MODEL_AGGREGATECLASSIFICATIONMETRICS = _descriptor.Descriptor(
    name="AggregateClassificationMetrics",
    full_name="google.cloud.bigquery.v2.Model.AggregateClassificationMetrics",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="precision",
            full_name="google.cloud.bigquery.v2.Model.AggregateClassificationMetrics.precision",
            index=0,
            number=1,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="recall",
            full_name="google.cloud.bigquery.v2.Model.AggregateClassificationMetrics.recall",
            index=1,
            number=2,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="accuracy",
            full_name="google.cloud.bigquery.v2.Model.AggregateClassificationMetrics.accuracy",
            index=2,
            number=3,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="threshold",
            full_name="google.cloud.bigquery.v2.Model.AggregateClassificationMetrics.threshold",
            index=3,
            number=4,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="f1_score",
            full_name="google.cloud.bigquery.v2.Model.AggregateClassificationMetrics.f1_score",
            index=4,
            number=5,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="log_loss",
            full_name="google.cloud.bigquery.v2.Model.AggregateClassificationMetrics.log_loss",
            index=5,
            number=6,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="roc_auc",
            full_name="google.cloud.bigquery.v2.Model.AggregateClassificationMetrics.roc_auc",
            index=6,
            number=7,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=1310,
    serialized_end=1677,
)

_MODEL_BINARYCLASSIFICATIONMETRICS_BINARYCONFUSIONMATRIX = _descriptor.Descriptor(
    name="BinaryConfusionMatrix",
    full_name="google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="positive_class_threshold",
            full_name="google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix.positive_class_threshold",
            index=0,
            number=1,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="true_positives",
            full_name="google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix.true_positives",
            index=1,
            number=2,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="false_positives",
            full_name="google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix.false_positives",
            index=2,
            number=3,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="true_negatives",
            full_name="google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix.true_negatives",
            index=3,
            number=4,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="false_negatives",
            full_name="google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix.false_negatives",
            index=4,
            number=5,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="precision",
            full_name="google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix.precision",
            index=5,
            number=6,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="recall",
            full_name="google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix.recall",
            index=6,
            number=7,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="f1_score",
            full_name="google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix.f1_score",
            index=7,
            number=8,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="accuracy",
            full_name="google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix.accuracy",
            index=8,
            number=9,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=1987,
    serialized_end=2479,
)

_MODEL_BINARYCLASSIFICATIONMETRICS = _descriptor.Descriptor(
    name="BinaryClassificationMetrics",
    full_name="google.cloud.bigquery.v2.Model.BinaryClassificationMetrics",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="aggregate_classification_metrics",
            full_name="google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.aggregate_classification_metrics",
            index=0,
            number=1,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="binary_confusion_matrix_list",
            full_name="google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.binary_confusion_matrix_list",
            index=1,
            number=2,
            type=11,
            cpp_type=10,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="positive_label",
            full_name="google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.positive_label",
            index=2,
            number=3,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="negative_label",
            full_name="google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.negative_label",
            index=3,
            number=4,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[_MODEL_BINARYCLASSIFICATIONMETRICS_BINARYCONFUSIONMATRIX],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=1680,
    serialized_end=2479,
)

_MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX_ENTRY = _descriptor.Descriptor(
    name="Entry",
    full_name="google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix.Entry",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="predicted_label",
            full_name="google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix.Entry.predicted_label",
            index=0,
            number=1,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="item_count",
            full_name="google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix.Entry.item_count",
            index=1,
            number=2,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=2914,
    serialized_end=2995,
)

_MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX_ROW = _descriptor.Descriptor(
    name="Row",
    full_name="google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix.Row",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="actual_label",
            full_name="google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix.Row.actual_label",
            index=0,
            number=1,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="entries",
            full_name="google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix.Row.entries",
            index=1,
            number=2,
            type=11,
            cpp_type=10,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=2998,
    serialized_end=3129,
)

_MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX = _descriptor.Descriptor(
    name="ConfusionMatrix",
    full_name="google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="confidence_threshold",
            full_name="google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix.confidence_threshold",
            index=0,
            number=1,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="rows",
            full_name="google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix.rows",
            index=1,
            number=2,
            type=11,
            cpp_type=10,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[
        _MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX_ENTRY,
        _MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX_ROW,
    ],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=2736,
    serialized_end=3129,
)

_MODEL_MULTICLASSCLASSIFICATIONMETRICS = _descriptor.Descriptor(
    name="MultiClassClassificationMetrics",
    full_name="google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="aggregate_classification_metrics",
            full_name="google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.aggregate_classification_metrics",
            index=0,
            number=1,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="confusion_matrix_list",
            full_name="google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.confusion_matrix_list",
            index=1,
            number=2,
            type=11,
            cpp_type=10,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[_MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=2482,
    serialized_end=3129,
)

_MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE_CATEGORICALVALUE_CATEGORYCOUNT = _descriptor.Descriptor(
    name="CategoryCount",
    full_name="google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue.CategoryCount",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="category",
            full_name="google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue.CategoryCount.category",
            index=0,
            number=1,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="count",
            full_name="google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue.CategoryCount.count",
            index=1,
            number=2,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=3889,
    serialized_end=3966,
)

_MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE_CATEGORICALVALUE = _descriptor.Descriptor(
    name="CategoricalValue",
    full_name="google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="category_counts",
            full_name="google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue.category_counts",
            index=0,
            number=1,
            type=11,
            cpp_type=10,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        )
    ],
    extensions=[],
    nested_types=[
        _MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE_CATEGORICALVALUE_CATEGORYCOUNT
    ],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=3741,
    serialized_end=3966,
)

_MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE = _descriptor.Descriptor(
    name="FeatureValue",
    full_name="google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="feature_column",
            full_name="google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.feature_column",
            index=0,
            number=1,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="numerical_value",
            full_name="google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.numerical_value",
            index=1,
            number=2,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="categorical_value",
            full_name="google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.categorical_value",
            index=2,
            number=3,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[_MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE_CATEGORICALVALUE],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[
        _descriptor.OneofDescriptor(
            name="value",
            full_name="google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.value",
            index=0,
            containing_type=None,
            fields=[],
        )
    ],
    serialized_start=3525,
    serialized_end=3975,
)

_MODEL_CLUSTERINGMETRICS_CLUSTER = _descriptor.Descriptor(
    name="Cluster",
    full_name="google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="centroid_id",
            full_name="google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.centroid_id",
            index=0,
            number=1,
            type=3,
            cpp_type=2,
            label=1,
            has_default_value=False,
            default_value=0,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="feature_values",
            full_name="google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.feature_values",
            index=1,
            number=2,
            type=11,
            cpp_type=10,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="count",
            full_name="google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.count",
            index=2,
            number=3,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[_MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=3352,
    serialized_end=3975,
)

_MODEL_CLUSTERINGMETRICS = _descriptor.Descriptor(
    name="ClusteringMetrics",
    full_name="google.cloud.bigquery.v2.Model.ClusteringMetrics",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="davies_bouldin_index",
            full_name="google.cloud.bigquery.v2.Model.ClusteringMetrics.davies_bouldin_index",
            index=0,
            number=1,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="mean_squared_distance",
            full_name="google.cloud.bigquery.v2.Model.ClusteringMetrics.mean_squared_distance",
            index=1,
            number=2,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="clusters",
            full_name="google.cloud.bigquery.v2.Model.ClusteringMetrics.clusters",
            index=2,
            number=3,
            type=11,
            cpp_type=10,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[_MODEL_CLUSTERINGMETRICS_CLUSTER],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=3132,
    serialized_end=3975,
)

_MODEL_EVALUATIONMETRICS = _descriptor.Descriptor(
    name="EvaluationMetrics",
    full_name="google.cloud.bigquery.v2.Model.EvaluationMetrics",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="regression_metrics",
            full_name="google.cloud.bigquery.v2.Model.EvaluationMetrics.regression_metrics",
            index=0,
            number=1,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="binary_classification_metrics",
            full_name="google.cloud.bigquery.v2.Model.EvaluationMetrics.binary_classification_metrics",
            index=1,
            number=2,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="multi_class_classification_metrics",
            full_name="google.cloud.bigquery.v2.Model.EvaluationMetrics.multi_class_classification_metrics",
            index=2,
            number=3,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="clustering_metrics",
            full_name="google.cloud.bigquery.v2.Model.EvaluationMetrics.clustering_metrics",
            index=3,
            number=4,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[
        _descriptor.OneofDescriptor(
            name="metrics",
            full_name="google.cloud.bigquery.v2.Model.EvaluationMetrics.metrics",
            index=0,
            containing_type=None,
            fields=[],
        )
    ],
    serialized_start=3978,
    serialized_end=4383,
)

_MODEL_TRAININGRUN_TRAININGOPTIONS_LABELCLASSWEIGHTSENTRY = _descriptor.Descriptor(
    name="LabelClassWeightsEntry",
    full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.LabelClassWeightsEntry",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="key",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.LabelClassWeightsEntry.key",
            index=0,
            number=1,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="value",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.LabelClassWeightsEntry.value",
            index=1,
            number=2,
            type=1,
            cpp_type=5,
            label=1,
            has_default_value=False,
            default_value=float(0),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[],
    enum_types=[],
    serialized_options=_b("8\001"),
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=5819,
    serialized_end=5875,
)

_MODEL_TRAININGRUN_TRAININGOPTIONS = _descriptor.Descriptor(
    name="TrainingOptions",
    full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="max_iterations",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.max_iterations",
            index=0,
            number=1,
            type=3,
            cpp_type=2,
            label=1,
            has_default_value=False,
            default_value=0,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="loss_type",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.loss_type",
            index=1,
            number=2,
            type=14,
            cpp_type=8,
            label=1,
            has_default_value=False,
            default_value=0,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="learn_rate",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.learn_rate",
            index=2,
            number=3,
            type=1,
            cpp_type=5,
            label=1,
            has_default_value=False,
            default_value=float(0),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="l1_regularization",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.l1_regularization",
            index=3,
            number=4,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="l2_regularization",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.l2_regularization",
            index=4,
            number=5,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="min_relative_progress",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.min_relative_progress",
            index=5,
            number=6,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="warm_start",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.warm_start",
            index=6,
            number=7,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="early_stop",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.early_stop",
            index=7,
            number=8,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="input_label_columns",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.input_label_columns",
            index=8,
            number=9,
            type=9,
            cpp_type=9,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="data_split_method",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.data_split_method",
            index=9,
            number=10,
            type=14,
            cpp_type=8,
            label=1,
            has_default_value=False,
            default_value=0,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="data_split_eval_fraction",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.data_split_eval_fraction",
            index=10,
            number=11,
            type=1,
            cpp_type=5,
            label=1,
            has_default_value=False,
            default_value=float(0),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="data_split_column",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.data_split_column",
            index=11,
            number=12,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="learn_rate_strategy",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.learn_rate_strategy",
            index=12,
            number=13,
            type=14,
            cpp_type=8,
            label=1,
            has_default_value=False,
            default_value=0,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="initial_learn_rate",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.initial_learn_rate",
            index=13,
            number=16,
            type=1,
            cpp_type=5,
            label=1,
            has_default_value=False,
            default_value=float(0),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="label_class_weights",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.label_class_weights",
            index=14,
            number=17,
            type=11,
            cpp_type=10,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="distance_type",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.distance_type",
            index=15,
            number=20,
            type=14,
            cpp_type=8,
            label=1,
            has_default_value=False,
            default_value=0,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="num_clusters",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.num_clusters",
            index=16,
            number=21,
            type=3,
            cpp_type=2,
            label=1,
            has_default_value=False,
            default_value=0,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="model_uri",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.model_uri",
            index=17,
            number=22,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="optimization_strategy",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.optimization_strategy",
            index=18,
            number=23,
            type=14,
            cpp_type=8,
            label=1,
            has_default_value=False,
            default_value=0,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="kmeans_initialization_method",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.kmeans_initialization_method",
            index=19,
            number=33,
            type=14,
            cpp_type=8,
            label=1,
            has_default_value=False,
            default_value=0,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="kmeans_initialization_column",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.kmeans_initialization_column",
            index=20,
            number=34,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[_MODEL_TRAININGRUN_TRAININGOPTIONS_LABELCLASSWEIGHTSENTRY],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=4694,
    serialized_end=5875,
)

_MODEL_TRAININGRUN_ITERATIONRESULT_CLUSTERINFO = _descriptor.Descriptor(
    name="ClusterInfo",
    full_name="google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ClusterInfo",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="centroid_id",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ClusterInfo.centroid_id",
            index=0,
            number=1,
            type=3,
            cpp_type=2,
            label=1,
            has_default_value=False,
            default_value=0,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="cluster_radius",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ClusterInfo.cluster_radius",
            index=1,
            number=2,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="cluster_size",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ClusterInfo.cluster_size",
            index=2,
            number=3,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=6210,
    serialized_end=6349,
)

_MODEL_TRAININGRUN_ITERATIONRESULT = _descriptor.Descriptor(
    name="IterationResult",
    full_name="google.cloud.bigquery.v2.Model.TrainingRun.IterationResult",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="index",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.index",
            index=0,
            number=1,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="duration_ms",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.duration_ms",
            index=1,
            number=4,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="training_loss",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.training_loss",
            index=2,
            number=5,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="eval_loss",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.eval_loss",
            index=3,
            number=6,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="learn_rate",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.learn_rate",
            index=4,
            number=7,
            type=1,
            cpp_type=5,
            label=1,
            has_default_value=False,
            default_value=float(0),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="cluster_infos",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.cluster_infos",
            index=5,
            number=8,
            type=11,
            cpp_type=10,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[_MODEL_TRAININGRUN_ITERATIONRESULT_CLUSTERINFO],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=5878,
    serialized_end=6349,
)

_MODEL_TRAININGRUN = _descriptor.Descriptor(
    name="TrainingRun",
    full_name="google.cloud.bigquery.v2.Model.TrainingRun",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="training_options",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.training_options",
            index=0,
            number=1,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="start_time",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.start_time",
            index=1,
            number=8,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="results",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.results",
            index=2,
            number=6,
            type=11,
            cpp_type=10,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="evaluation_metrics",
            full_name="google.cloud.bigquery.v2.Model.TrainingRun.evaluation_metrics",
            index=3,
            number=7,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[
        _MODEL_TRAININGRUN_TRAININGOPTIONS,
        _MODEL_TRAININGRUN_ITERATIONRESULT,
    ],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=4386,
    serialized_end=6349,
)

_MODEL_LABELSENTRY = _descriptor.Descriptor(
    name="LabelsEntry",
    full_name="google.cloud.bigquery.v2.Model.LabelsEntry",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="key",
            full_name="google.cloud.bigquery.v2.Model.LabelsEntry.key",
            index=0,
            number=1,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="value",
            full_name="google.cloud.bigquery.v2.Model.LabelsEntry.value",
            index=1,
            number=2,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[],
    enum_types=[],
    serialized_options=_b("8\001"),
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=6351,
    serialized_end=6396,
)

_MODEL = _descriptor.Descriptor(
    name="Model",
    full_name="google.cloud.bigquery.v2.Model",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="etag",
            full_name="google.cloud.bigquery.v2.Model.etag",
            index=0,
            number=1,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="model_reference",
            full_name="google.cloud.bigquery.v2.Model.model_reference",
            index=1,
            number=2,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="creation_time",
            full_name="google.cloud.bigquery.v2.Model.creation_time",
            index=2,
            number=5,
            type=3,
            cpp_type=2,
            label=1,
            has_default_value=False,
            default_value=0,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="last_modified_time",
            full_name="google.cloud.bigquery.v2.Model.last_modified_time",
            index=3,
            number=6,
            type=3,
            cpp_type=2,
            label=1,
            has_default_value=False,
            default_value=0,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="description",
            full_name="google.cloud.bigquery.v2.Model.description",
            index=4,
            number=12,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="friendly_name",
            full_name="google.cloud.bigquery.v2.Model.friendly_name",
            index=5,
            number=14,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="labels",
            full_name="google.cloud.bigquery.v2.Model.labels",
            index=6,
            number=15,
            type=11,
            cpp_type=10,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="expiration_time",
            full_name="google.cloud.bigquery.v2.Model.expiration_time",
            index=7,
            number=16,
            type=3,
            cpp_type=2,
            label=1,
            has_default_value=False,
            default_value=0,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="location",
            full_name="google.cloud.bigquery.v2.Model.location",
            index=8,
            number=13,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="model_type",
            full_name="google.cloud.bigquery.v2.Model.model_type",
            index=9,
            number=7,
            type=14,
            cpp_type=8,
            label=1,
            has_default_value=False,
            default_value=0,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="training_runs",
            full_name="google.cloud.bigquery.v2.Model.training_runs",
            index=10,
            number=9,
            type=11,
            cpp_type=10,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="feature_columns",
            full_name="google.cloud.bigquery.v2.Model.feature_columns",
            index=11,
            number=10,
            type=11,
            cpp_type=10,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="label_columns",
            full_name="google.cloud.bigquery.v2.Model.label_columns",
            index=12,
            number=11,
            type=11,
            cpp_type=10,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[
        _MODEL_KMEANSENUMS,
        _MODEL_REGRESSIONMETRICS,
        _MODEL_AGGREGATECLASSIFICATIONMETRICS,
        _MODEL_BINARYCLASSIFICATIONMETRICS,
        _MODEL_MULTICLASSCLASSIFICATIONMETRICS,
        _MODEL_CLUSTERINGMETRICS,
        _MODEL_EVALUATIONMETRICS,
        _MODEL_TRAININGRUN,
        _MODEL_LABELSENTRY,
    ],
    enum_types=[
        _MODEL_MODELTYPE,
        _MODEL_LOSSTYPE,
        _MODEL_DISTANCETYPE,
        _MODEL_DATASPLITMETHOD,
        _MODEL_LEARNRATESTRATEGY,
        _MODEL_OPTIMIZATIONSTRATEGY,
    ],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=327,
    serialized_end=6993,
)


_GETMODELREQUEST = _descriptor.Descriptor(
    name="GetModelRequest",
    full_name="google.cloud.bigquery.v2.GetModelRequest",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="project_id",
            full_name="google.cloud.bigquery.v2.GetModelRequest.project_id",
            index=0,
            number=1,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="dataset_id",
            full_name="google.cloud.bigquery.v2.GetModelRequest.dataset_id",
            index=1,
            number=2,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="model_id",
            full_name="google.cloud.bigquery.v2.GetModelRequest.model_id",
            index=2,
            number=3,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=6995,
    serialized_end=7070,
)


_PATCHMODELREQUEST = _descriptor.Descriptor(
    name="PatchModelRequest",
    full_name="google.cloud.bigquery.v2.PatchModelRequest",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="project_id",
            full_name="google.cloud.bigquery.v2.PatchModelRequest.project_id",
            index=0,
            number=1,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="dataset_id",
            full_name="google.cloud.bigquery.v2.PatchModelRequest.dataset_id",
            index=1,
            number=2,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="model_id",
            full_name="google.cloud.bigquery.v2.PatchModelRequest.model_id",
            index=2,
            number=3,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="model",
            full_name="google.cloud.bigquery.v2.PatchModelRequest.model",
            index=3,
            number=4,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=7072,
    serialized_end=7197,
)


_DELETEMODELREQUEST = _descriptor.Descriptor(
    name="DeleteModelRequest",
    full_name="google.cloud.bigquery.v2.DeleteModelRequest",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="project_id",
            full_name="google.cloud.bigquery.v2.DeleteModelRequest.project_id",
            index=0,
            number=1,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="dataset_id",
            full_name="google.cloud.bigquery.v2.DeleteModelRequest.dataset_id",
            index=1,
            number=2,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="model_id",
            full_name="google.cloud.bigquery.v2.DeleteModelRequest.model_id",
            index=2,
            number=3,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=7199,
    serialized_end=7277,
)


_LISTMODELSREQUEST = _descriptor.Descriptor(
    name="ListModelsRequest",
    full_name="google.cloud.bigquery.v2.ListModelsRequest",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="project_id",
            full_name="google.cloud.bigquery.v2.ListModelsRequest.project_id",
            index=0,
            number=1,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="dataset_id",
            full_name="google.cloud.bigquery.v2.ListModelsRequest.dataset_id",
            index=1,
            number=2,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="max_results",
            full_name="google.cloud.bigquery.v2.ListModelsRequest.max_results",
            index=2,
            number=3,
            type=11,
            cpp_type=10,
            label=1,
            has_default_value=False,
            default_value=None,
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="page_token",
            full_name="google.cloud.bigquery.v2.ListModelsRequest.page_token",
            index=3,
            number=4,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=7280,
    serialized_end=7410,
)


_LISTMODELSRESPONSE = _descriptor.Descriptor(
    name="ListModelsResponse",
    full_name="google.cloud.bigquery.v2.ListModelsResponse",
    filename=None,
    file=DESCRIPTOR,
    containing_type=None,
    fields=[
        _descriptor.FieldDescriptor(
            name="models",
            full_name="google.cloud.bigquery.v2.ListModelsResponse.models",
            index=0,
            number=1,
            type=11,
            cpp_type=10,
            label=3,
            has_default_value=False,
            default_value=[],
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
        _descriptor.FieldDescriptor(
            name="next_page_token",
            full_name="google.cloud.bigquery.v2.ListModelsResponse.next_page_token",
            index=1,
            number=2,
            type=9,
            cpp_type=9,
            label=1,
            has_default_value=False,
            default_value=_b("").decode("utf-8"),
            message_type=None,
            enum_type=None,
            containing_type=None,
            is_extension=False,
            extension_scope=None,
            serialized_options=None,
            file=DESCRIPTOR,
        ),
    ],
    extensions=[],
    nested_types=[],
    enum_types=[],
    serialized_options=None,
    is_extendable=False,
    syntax="proto3",
    extension_ranges=[],
    oneofs=[],
    serialized_start=7412,
    serialized_end=7506,
)

_MODEL_KMEANSENUMS.containing_type = _MODEL
_MODEL_KMEANSENUMS_KMEANSINITIALIZATIONMETHOD.containing_type = _MODEL_KMEANSENUMS
_MODEL_REGRESSIONMETRICS.fields_by_name[
    "mean_absolute_error"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_REGRESSIONMETRICS.fields_by_name[
    "mean_squared_error"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_REGRESSIONMETRICS.fields_by_name[
    "mean_squared_log_error"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_REGRESSIONMETRICS.fields_by_name[
    "median_absolute_error"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_REGRESSIONMETRICS.fields_by_name[
    "r_squared"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_REGRESSIONMETRICS.containing_type = _MODEL
_MODEL_AGGREGATECLASSIFICATIONMETRICS.fields_by_name[
    "precision"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_AGGREGATECLASSIFICATIONMETRICS.fields_by_name[
    "recall"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_AGGREGATECLASSIFICATIONMETRICS.fields_by_name[
    "accuracy"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_AGGREGATECLASSIFICATIONMETRICS.fields_by_name[
    "threshold"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_AGGREGATECLASSIFICATIONMETRICS.fields_by_name[
    "f1_score"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_AGGREGATECLASSIFICATIONMETRICS.fields_by_name[
    "log_loss"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_AGGREGATECLASSIFICATIONMETRICS.fields_by_name[
    "roc_auc"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_AGGREGATECLASSIFICATIONMETRICS.containing_type = _MODEL
_MODEL_BINARYCLASSIFICATIONMETRICS_BINARYCONFUSIONMATRIX.fields_by_name[
    "positive_class_threshold"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_BINARYCLASSIFICATIONMETRICS_BINARYCONFUSIONMATRIX.fields_by_name[
    "true_positives"
].message_type = google_dot_protobuf_dot_wrappers__pb2._INT64VALUE
_MODEL_BINARYCLASSIFICATIONMETRICS_BINARYCONFUSIONMATRIX.fields_by_name[
    "false_positives"
].message_type = google_dot_protobuf_dot_wrappers__pb2._INT64VALUE
_MODEL_BINARYCLASSIFICATIONMETRICS_BINARYCONFUSIONMATRIX.fields_by_name[
    "true_negatives"
].message_type = google_dot_protobuf_dot_wrappers__pb2._INT64VALUE
_MODEL_BINARYCLASSIFICATIONMETRICS_BINARYCONFUSIONMATRIX.fields_by_name[
    "false_negatives"
].message_type = google_dot_protobuf_dot_wrappers__pb2._INT64VALUE
_MODEL_BINARYCLASSIFICATIONMETRICS_BINARYCONFUSIONMATRIX.fields_by_name[
    "precision"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_BINARYCLASSIFICATIONMETRICS_BINARYCONFUSIONMATRIX.fields_by_name[
    "recall"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_BINARYCLASSIFICATIONMETRICS_BINARYCONFUSIONMATRIX.fields_by_name[
    "f1_score"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_BINARYCLASSIFICATIONMETRICS_BINARYCONFUSIONMATRIX.fields_by_name[
    "accuracy"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_BINARYCLASSIFICATIONMETRICS_BINARYCONFUSIONMATRIX.containing_type = (
    _MODEL_BINARYCLASSIFICATIONMETRICS
)
_MODEL_BINARYCLASSIFICATIONMETRICS.fields_by_name[
    "aggregate_classification_metrics"
].message_type = _MODEL_AGGREGATECLASSIFICATIONMETRICS
_MODEL_BINARYCLASSIFICATIONMETRICS.fields_by_name[
    "binary_confusion_matrix_list"
].message_type = _MODEL_BINARYCLASSIFICATIONMETRICS_BINARYCONFUSIONMATRIX
_MODEL_BINARYCLASSIFICATIONMETRICS.containing_type = _MODEL
_MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX_ENTRY.fields_by_name[
    "item_count"
].message_type = google_dot_protobuf_dot_wrappers__pb2._INT64VALUE
_MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX_ENTRY.containing_type = (
    _MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX
)
_MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX_ROW.fields_by_name[
    "entries"
].message_type = _MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX_ENTRY
_MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX_ROW.containing_type = (
    _MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX
)
_MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX.fields_by_name[
    "confidence_threshold"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX.fields_by_name[
    "rows"
].message_type = _MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX_ROW
_MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX.containing_type = (
    _MODEL_MULTICLASSCLASSIFICATIONMETRICS
)
_MODEL_MULTICLASSCLASSIFICATIONMETRICS.fields_by_name[
    "aggregate_classification_metrics"
].message_type = _MODEL_AGGREGATECLASSIFICATIONMETRICS
_MODEL_MULTICLASSCLASSIFICATIONMETRICS.fields_by_name[
    "confusion_matrix_list"
].message_type = _MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX
_MODEL_MULTICLASSCLASSIFICATIONMETRICS.containing_type = _MODEL
_MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE_CATEGORICALVALUE_CATEGORYCOUNT.fields_by_name[
    "count"
].message_type = google_dot_protobuf_dot_wrappers__pb2._INT64VALUE
_MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE_CATEGORICALVALUE_CATEGORYCOUNT.containing_type = (
    _MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE_CATEGORICALVALUE
)
_MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE_CATEGORICALVALUE.fields_by_name[
    "category_counts"
].message_type = (
    _MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE_CATEGORICALVALUE_CATEGORYCOUNT
)
_MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE_CATEGORICALVALUE.containing_type = (
    _MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE
)
_MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE.fields_by_name[
    "numerical_value"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE.fields_by_name[
    "categorical_value"
].message_type = _MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE_CATEGORICALVALUE
_MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE.containing_type = (
    _MODEL_CLUSTERINGMETRICS_CLUSTER
)
_MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE.oneofs_by_name["value"].fields.append(
    _MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE.fields_by_name["numerical_value"]
)
_MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE.fields_by_name[
    "numerical_value"
].containing_oneof = _MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE.oneofs_by_name[
    "value"
]
_MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE.oneofs_by_name["value"].fields.append(
    _MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE.fields_by_name["categorical_value"]
)
_MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE.fields_by_name[
    "categorical_value"
].containing_oneof = _MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE.oneofs_by_name[
    "value"
]
_MODEL_CLUSTERINGMETRICS_CLUSTER.fields_by_name[
    "feature_values"
].message_type = _MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE
_MODEL_CLUSTERINGMETRICS_CLUSTER.fields_by_name[
    "count"
].message_type = google_dot_protobuf_dot_wrappers__pb2._INT64VALUE
_MODEL_CLUSTERINGMETRICS_CLUSTER.containing_type = _MODEL_CLUSTERINGMETRICS
_MODEL_CLUSTERINGMETRICS.fields_by_name[
    "davies_bouldin_index"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_CLUSTERINGMETRICS.fields_by_name[
    "mean_squared_distance"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_CLUSTERINGMETRICS.fields_by_name[
    "clusters"
].message_type = _MODEL_CLUSTERINGMETRICS_CLUSTER
_MODEL_CLUSTERINGMETRICS.containing_type = _MODEL
_MODEL_EVALUATIONMETRICS.fields_by_name[
    "regression_metrics"
].message_type = _MODEL_REGRESSIONMETRICS
_MODEL_EVALUATIONMETRICS.fields_by_name[
    "binary_classification_metrics"
].message_type = _MODEL_BINARYCLASSIFICATIONMETRICS
_MODEL_EVALUATIONMETRICS.fields_by_name[
    "multi_class_classification_metrics"
].message_type = _MODEL_MULTICLASSCLASSIFICATIONMETRICS
_MODEL_EVALUATIONMETRICS.fields_by_name[
    "clustering_metrics"
].message_type = _MODEL_CLUSTERINGMETRICS
_MODEL_EVALUATIONMETRICS.containing_type = _MODEL
_MODEL_EVALUATIONMETRICS.oneofs_by_name["metrics"].fields.append(
    _MODEL_EVALUATIONMETRICS.fields_by_name["regression_metrics"]
)
_MODEL_EVALUATIONMETRICS.fields_by_name[
    "regression_metrics"
].containing_oneof = _MODEL_EVALUATIONMETRICS.oneofs_by_name["metrics"]
_MODEL_EVALUATIONMETRICS.oneofs_by_name["metrics"].fields.append(
    _MODEL_EVALUATIONMETRICS.fields_by_name["binary_classification_metrics"]
)
_MODEL_EVALUATIONMETRICS.fields_by_name[
    "binary_classification_metrics"
].containing_oneof = _MODEL_EVALUATIONMETRICS.oneofs_by_name["metrics"]
_MODEL_EVALUATIONMETRICS.oneofs_by_name["metrics"].fields.append(
    _MODEL_EVALUATIONMETRICS.fields_by_name["multi_class_classification_metrics"]
)
_MODEL_EVALUATIONMETRICS.fields_by_name[
    "multi_class_classification_metrics"
].containing_oneof = _MODEL_EVALUATIONMETRICS.oneofs_by_name["metrics"]
_MODEL_EVALUATIONMETRICS.oneofs_by_name["metrics"].fields.append(
    _MODEL_EVALUATIONMETRICS.fields_by_name["clustering_metrics"]
)
_MODEL_EVALUATIONMETRICS.fields_by_name[
    "clustering_metrics"
].containing_oneof = _MODEL_EVALUATIONMETRICS.oneofs_by_name["metrics"]
_MODEL_TRAININGRUN_TRAININGOPTIONS_LABELCLASSWEIGHTSENTRY.containing_type = (
    _MODEL_TRAININGRUN_TRAININGOPTIONS
)
_MODEL_TRAININGRUN_TRAININGOPTIONS.fields_by_name[
    "loss_type"
].enum_type = _MODEL_LOSSTYPE
_MODEL_TRAININGRUN_TRAININGOPTIONS.fields_by_name[
    "l1_regularization"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_TRAININGRUN_TRAININGOPTIONS.fields_by_name[
    "l2_regularization"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_TRAININGRUN_TRAININGOPTIONS.fields_by_name[
    "min_relative_progress"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_TRAININGRUN_TRAININGOPTIONS.fields_by_name[
    "warm_start"
].message_type = google_dot_protobuf_dot_wrappers__pb2._BOOLVALUE
_MODEL_TRAININGRUN_TRAININGOPTIONS.fields_by_name[
    "early_stop"
].message_type = google_dot_protobuf_dot_wrappers__pb2._BOOLVALUE
_MODEL_TRAININGRUN_TRAININGOPTIONS.fields_by_name[
    "data_split_method"
].enum_type = _MODEL_DATASPLITMETHOD
_MODEL_TRAININGRUN_TRAININGOPTIONS.fields_by_name[
    "learn_rate_strategy"
].enum_type = _MODEL_LEARNRATESTRATEGY
_MODEL_TRAININGRUN_TRAININGOPTIONS.fields_by_name[
    "label_class_weights"
].message_type = _MODEL_TRAININGRUN_TRAININGOPTIONS_LABELCLASSWEIGHTSENTRY
_MODEL_TRAININGRUN_TRAININGOPTIONS.fields_by_name[
    "distance_type"
].enum_type = _MODEL_DISTANCETYPE
_MODEL_TRAININGRUN_TRAININGOPTIONS.fields_by_name[
    "optimization_strategy"
].enum_type = _MODEL_OPTIMIZATIONSTRATEGY
_MODEL_TRAININGRUN_TRAININGOPTIONS.fields_by_name[
    "kmeans_initialization_method"
].enum_type = _MODEL_KMEANSENUMS_KMEANSINITIALIZATIONMETHOD
_MODEL_TRAININGRUN_TRAININGOPTIONS.containing_type = _MODEL_TRAININGRUN
_MODEL_TRAININGRUN_ITERATIONRESULT_CLUSTERINFO.fields_by_name[
    "cluster_radius"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_TRAININGRUN_ITERATIONRESULT_CLUSTERINFO.fields_by_name[
    "cluster_size"
].message_type = google_dot_protobuf_dot_wrappers__pb2._INT64VALUE
_MODEL_TRAININGRUN_ITERATIONRESULT_CLUSTERINFO.containing_type = (
    _MODEL_TRAININGRUN_ITERATIONRESULT
)
_MODEL_TRAININGRUN_ITERATIONRESULT.fields_by_name[
    "index"
].message_type = google_dot_protobuf_dot_wrappers__pb2._INT32VALUE
_MODEL_TRAININGRUN_ITERATIONRESULT.fields_by_name[
    "duration_ms"
].message_type = google_dot_protobuf_dot_wrappers__pb2._INT64VALUE
_MODEL_TRAININGRUN_ITERATIONRESULT.fields_by_name[
    "training_loss"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_TRAININGRUN_ITERATIONRESULT.fields_by_name[
    "eval_loss"
].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE
_MODEL_TRAININGRUN_ITERATIONRESULT.fields_by_name[
    "cluster_infos"
].message_type = _MODEL_TRAININGRUN_ITERATIONRESULT_CLUSTERINFO
_MODEL_TRAININGRUN_ITERATIONRESULT.containing_type = _MODEL_TRAININGRUN
_MODEL_TRAININGRUN.fields_by_name[
    "training_options"
].message_type = _MODEL_TRAININGRUN_TRAININGOPTIONS
_MODEL_TRAININGRUN.fields_by_name[
    "start_time"
].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_MODEL_TRAININGRUN.fields_by_name[
    "results"
].message_type = _MODEL_TRAININGRUN_ITERATIONRESULT
_MODEL_TRAININGRUN.fields_by_name[
    "evaluation_metrics"
].message_type = _MODEL_EVALUATIONMETRICS
_MODEL_TRAININGRUN.containing_type = _MODEL
_MODEL_LABELSENTRY.containing_type = _MODEL
_MODEL.fields_by_name[
    "model_reference"
].message_type = (
    google_dot_cloud_dot_bigquery__v2_dot_proto_dot_model__reference__pb2._MODELREFERENCE
)
_MODEL.fields_by_name["labels"].message_type = _MODEL_LABELSENTRY
_MODEL.fields_by_name["model_type"].enum_type = _MODEL_MODELTYPE
_MODEL.fields_by_name["training_runs"].message_type = _MODEL_TRAININGRUN
_MODEL.fields_by_name[
    "feature_columns"
].message_type = (
    google_dot_cloud_dot_bigquery__v2_dot_proto_dot_standard__sql__pb2._STANDARDSQLFIELD
)
_MODEL.fields_by_name[
    "label_columns"
].message_type = (
    google_dot_cloud_dot_bigquery__v2_dot_proto_dot_standard__sql__pb2._STANDARDSQLFIELD
)
_MODEL_MODELTYPE.containing_type = _MODEL
_MODEL_LOSSTYPE.containing_type = _MODEL
_MODEL_DISTANCETYPE.containing_type = _MODEL
_MODEL_DATASPLITMETHOD.containing_type = _MODEL
_MODEL_LEARNRATESTRATEGY.containing_type = _MODEL
_MODEL_OPTIMIZATIONSTRATEGY.containing_type = _MODEL
_PATCHMODELREQUEST.fields_by_name["model"].message_type = _MODEL
_LISTMODELSREQUEST.fields_by_name[
    "max_results"
].message_type = google_dot_protobuf_dot_wrappers__pb2._UINT32VALUE
_LISTMODELSRESPONSE.fields_by_name["models"].message_type = _MODEL
DESCRIPTOR.message_types_by_name["Model"] = _MODEL
DESCRIPTOR.message_types_by_name["GetModelRequest"] = _GETMODELREQUEST
DESCRIPTOR.message_types_by_name["PatchModelRequest"] = _PATCHMODELREQUEST
DESCRIPTOR.message_types_by_name["DeleteModelRequest"] = _DELETEMODELREQUEST
DESCRIPTOR.message_types_by_name["ListModelsRequest"] = _LISTMODELSREQUEST
DESCRIPTOR.message_types_by_name["ListModelsResponse"] = _LISTMODELSRESPONSE
_sym_db.RegisterFileDescriptor(DESCRIPTOR)

Model = _reflection.GeneratedProtocolMessageType(
    "Model",
    (_message.Message,),
    dict(
        KmeansEnums=_reflection.GeneratedProtocolMessageType(
            "KmeansEnums",
            (_message.Message,),
            dict(
                DESCRIPTOR=_MODEL_KMEANSENUMS,
                __module__="google.cloud.bigquery_v2.proto.model_pb2"
                # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.KmeansEnums)
            ),
        ),
        RegressionMetrics=_reflection.GeneratedProtocolMessageType(
            "RegressionMetrics",
            (_message.Message,),
            dict(
                DESCRIPTOR=_MODEL_REGRESSIONMETRICS,
                __module__="google.cloud.bigquery_v2.proto.model_pb2",
                __doc__="""Evaluation metrics for regression and explicit feedback type matrix
    factorization models.
    
    
    Attributes:
        mean_absolute_error:
            Mean absolute error.
        mean_squared_error:
            Mean squared error.
        mean_squared_log_error:
            Mean squared log error.
        median_absolute_error:
            Median absolute error.
        r_squared:
            R^2 score.
    """,
                # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.RegressionMetrics)
            ),
        ),
        AggregateClassificationMetrics=_reflection.GeneratedProtocolMessageType(
            "AggregateClassificationMetrics",
            (_message.Message,),
            dict(
                DESCRIPTOR=_MODEL_AGGREGATECLASSIFICATIONMETRICS,
                __module__="google.cloud.bigquery_v2.proto.model_pb2",
                __doc__="""Aggregate metrics for classification/classifier models. For multi-class
    models, the metrics are either macro-averaged or micro-averaged. When
    macro-averaged, the metrics are calculated for each label and then an
    unweighted average is taken of those values. When micro-averaged, the
    metric is calculated globally by counting the total number of correctly
    predicted rows.
    
    
    Attributes:
        precision:
            Precision is the fraction of actual positive predictions that
            had positive actual labels. For multiclass this is a macro-
            averaged metric treating each class as a binary classifier.
        recall:
            Recall is the fraction of actual positive labels that were
            given a positive prediction. For multiclass this is a macro-
            averaged metric.
        accuracy:
            Accuracy is the fraction of predictions given the correct
            label. For multiclass this is a micro-averaged metric.
        threshold:
            Threshold at which the metrics are computed. For binary
            classification models this is the positive class threshold.
            For multi-class classfication models this is the confidence
            threshold.
        f1_score:
            The F1 score is an average of recall and precision. For
            multiclass this is a macro-averaged metric.
        log_loss:
            Logarithmic Loss. For multiclass this is a macro-averaged
            metric.
        roc_auc:
            Area Under a ROC Curve. For multiclass this is a macro-
            averaged metric.
    """,
                # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.AggregateClassificationMetrics)
            ),
        ),
        BinaryClassificationMetrics=_reflection.GeneratedProtocolMessageType(
            "BinaryClassificationMetrics",
            (_message.Message,),
            dict(
                BinaryConfusionMatrix=_reflection.GeneratedProtocolMessageType(
                    "BinaryConfusionMatrix",
                    (_message.Message,),
                    dict(
                        DESCRIPTOR=_MODEL_BINARYCLASSIFICATIONMETRICS_BINARYCONFUSIONMATRIX,
                        __module__="google.cloud.bigquery_v2.proto.model_pb2",
                        __doc__="""Confusion matrix for binary classification models.
      
      
      Attributes:
          positive_class_threshold:
              Threshold value used when computing each of the following
              metric.
          true_positives:
              Number of true samples predicted as true.
          false_positives:
              Number of false samples predicted as true.
          true_negatives:
              Number of true samples predicted as false.
          false_negatives:
              Number of false samples predicted as false.
          precision:
              The fraction of actual positive predictions that had positive
              actual labels.
          recall:
              The fraction of actual positive labels that were given a
              positive prediction.
          f1_score:
              The equally weighted average of recall and precision.
          accuracy:
              The fraction of predictions given the correct label.
      """,
                        # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix)
                    ),
                ),
                DESCRIPTOR=_MODEL_BINARYCLASSIFICATIONMETRICS,
                __module__="google.cloud.bigquery_v2.proto.model_pb2",
                __doc__="""Evaluation metrics for binary classification/classifier models.
    
    
    Attributes:
        aggregate_classification_metrics:
            Aggregate classification metrics.
        binary_confusion_matrix_list:
            Binary confusion matrix at multiple thresholds.
        positive_label:
            Label representing the positive class.
        negative_label:
            Label representing the negative class.
    """,
                # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.BinaryClassificationMetrics)
            ),
        ),
        MultiClassClassificationMetrics=_reflection.GeneratedProtocolMessageType(
            "MultiClassClassificationMetrics",
            (_message.Message,),
            dict(
                ConfusionMatrix=_reflection.GeneratedProtocolMessageType(
                    "ConfusionMatrix",
                    (_message.Message,),
                    dict(
                        Entry=_reflection.GeneratedProtocolMessageType(
                            "Entry",
                            (_message.Message,),
                            dict(
                                DESCRIPTOR=_MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX_ENTRY,
                                __module__="google.cloud.bigquery_v2.proto.model_pb2",
                                __doc__="""A single entry in the confusion matrix.
        
        
        Attributes:
            predicted_label:
                The predicted label. For confidence\_threshold > 0, we will
                also add an entry indicating the number of items under the
                confidence threshold.
            item_count:
                Number of items being predicted as this label.
        """,
                                # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix.Entry)
                            ),
                        ),
                        Row=_reflection.GeneratedProtocolMessageType(
                            "Row",
                            (_message.Message,),
                            dict(
                                DESCRIPTOR=_MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX_ROW,
                                __module__="google.cloud.bigquery_v2.proto.model_pb2",
                                __doc__="""A single row in the confusion matrix.
        
        
        Attributes:
            actual_label:
                The original label of this row.
            entries:
                Info describing predicted label distribution.
        """,
                                # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix.Row)
                            ),
                        ),
                        DESCRIPTOR=_MODEL_MULTICLASSCLASSIFICATIONMETRICS_CONFUSIONMATRIX,
                        __module__="google.cloud.bigquery_v2.proto.model_pb2",
                        __doc__="""Confusion matrix for multi-class classification models.
      
      
      Attributes:
          confidence_threshold:
              Confidence threshold used when computing the entries of the
              confusion matrix.
          rows:
              One row per actual label.
      """,
                        # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix)
                    ),
                ),
                DESCRIPTOR=_MODEL_MULTICLASSCLASSIFICATIONMETRICS,
                __module__="google.cloud.bigquery_v2.proto.model_pb2",
                __doc__="""Evaluation metrics for multi-class classification/classifier models.
    
    
    Attributes:
        aggregate_classification_metrics:
            Aggregate classification metrics.
        confusion_matrix_list:
            Confusion matrix at different thresholds.
    """,
                # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics)
            ),
        ),
        ClusteringMetrics=_reflection.GeneratedProtocolMessageType(
            "ClusteringMetrics",
            (_message.Message,),
            dict(
                Cluster=_reflection.GeneratedProtocolMessageType(
                    "Cluster",
                    (_message.Message,),
                    dict(
                        FeatureValue=_reflection.GeneratedProtocolMessageType(
                            "FeatureValue",
                            (_message.Message,),
                            dict(
                                CategoricalValue=_reflection.GeneratedProtocolMessageType(
                                    "CategoricalValue",
                                    (_message.Message,),
                                    dict(
                                        CategoryCount=_reflection.GeneratedProtocolMessageType(
                                            "CategoryCount",
                                            (_message.Message,),
                                            dict(
                                                DESCRIPTOR=_MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE_CATEGORICALVALUE_CATEGORYCOUNT,
                                                __module__="google.cloud.bigquery_v2.proto.model_pb2",
                                                __doc__="""Represents the count of a single category within the cluster.
            
            
            Attributes:
                category:
                    The name of category.
                count:
                    The count of training samples matching the category within the
                    cluster.
            """,
                                                # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue.CategoryCount)
                                            ),
                                        ),
                                        DESCRIPTOR=_MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE_CATEGORICALVALUE,
                                        __module__="google.cloud.bigquery_v2.proto.model_pb2",
                                        __doc__="""Representative value of a categorical feature.
          
          
          Attributes:
              category_counts:
                  Counts of all categories for the categorical feature. If there
                  are more than ten categories, we return top ten (by count) and
                  return one more CategoryCount with category ‘\ *OTHER*\ ’ and
                  count as aggregate counts of remaining categories.
          """,
                                        # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue)
                                    ),
                                ),
                                DESCRIPTOR=_MODEL_CLUSTERINGMETRICS_CLUSTER_FEATUREVALUE,
                                __module__="google.cloud.bigquery_v2.proto.model_pb2",
                                __doc__="""Representative value of a single feature within the cluster.
        
        
        Attributes:
            feature_column:
                The feature column name.
            numerical_value:
                The numerical feature value. This is the centroid value for
                this feature.
            categorical_value:
                The categorical feature value.
        """,
                                # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue)
                            ),
                        ),
                        DESCRIPTOR=_MODEL_CLUSTERINGMETRICS_CLUSTER,
                        __module__="google.cloud.bigquery_v2.proto.model_pb2",
                        __doc__="""Message containing the information about one cluster.
      
      
      Attributes:
          centroid_id:
              Centroid id.
          feature_values:
              Values of highly variant features for this cluster.
          count:
              Count of training data rows that were assigned to this
              cluster.
      """,
                        # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster)
                    ),
                ),
                DESCRIPTOR=_MODEL_CLUSTERINGMETRICS,
                __module__="google.cloud.bigquery_v2.proto.model_pb2",
                __doc__="""Evaluation metrics for clustering models.
    
    
    Attributes:
        davies_bouldin_index:
            Davies-Bouldin index.
        mean_squared_distance:
            Mean of squared distances between each sample to its cluster
            centroid.
        clusters:
            [Beta] Information for all clusters.
    """,
                # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.ClusteringMetrics)
            ),
        ),
        EvaluationMetrics=_reflection.GeneratedProtocolMessageType(
            "EvaluationMetrics",
            (_message.Message,),
            dict(
                DESCRIPTOR=_MODEL_EVALUATIONMETRICS,
                __module__="google.cloud.bigquery_v2.proto.model_pb2",
                __doc__="""Evaluation metrics of a model. These are either computed on all training
    data or just the eval data based on whether eval data was used during
    training. These are not present for imported models.
    
    
    Attributes:
        regression_metrics:
            Populated for regression models and explicit feedback type
            matrix factorization models.
        binary_classification_metrics:
            Populated for binary classification/classifier models.
        multi_class_classification_metrics:
            Populated for multi-class classification/classifier models.
        clustering_metrics:
            Populated for clustering models.
    """,
                # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.EvaluationMetrics)
            ),
        ),
        TrainingRun=_reflection.GeneratedProtocolMessageType(
            "TrainingRun",
            (_message.Message,),
            dict(
                TrainingOptions=_reflection.GeneratedProtocolMessageType(
                    "TrainingOptions",
                    (_message.Message,),
                    dict(
                        LabelClassWeightsEntry=_reflection.GeneratedProtocolMessageType(
                            "LabelClassWeightsEntry",
                            (_message.Message,),
                            dict(
                                DESCRIPTOR=_MODEL_TRAININGRUN_TRAININGOPTIONS_LABELCLASSWEIGHTSENTRY,
                                __module__="google.cloud.bigquery_v2.proto.model_pb2"
                                # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.LabelClassWeightsEntry)
                            ),
                        ),
                        DESCRIPTOR=_MODEL_TRAININGRUN_TRAININGOPTIONS,
                        __module__="google.cloud.bigquery_v2.proto.model_pb2",
                        __doc__="""Protocol buffer.

  Attributes:
          max_iterations:
              The maximum number of iterations in training. Used only for
              iterative training algorithms.
          loss_type:
              Type of loss function used during training run.
          learn_rate:
              Learning rate in training. Used only for iterative training
              algorithms.
          l1_regularization:
              L1 regularization coefficient.
          l2_regularization:
              L2 regularization coefficient.
          min_relative_progress:
              When early\_stop is true, stops training when accuracy
              improvement is less than 'min\_relative\_progress'. Used only
              for iterative training algorithms.
          warm_start:
              Whether to train a model from the last checkpoint.
          early_stop:
              Whether to stop early when the loss doesn't improve
              significantly any more (compared to min\_relative\_progress).
              Used only for iterative training algorithms.
          input_label_columns:
              Name of input label columns in training data.
          data_split_method:
              The data split type for training and evaluation, e.g. RANDOM.
          data_split_eval_fraction:
              The fraction of evaluation data over the whole input data. The
              rest of data will be used as training data. The format should
              be double. Accurate to two decimal places. Default value is
              0.2.
          data_split_column:
              The column to split data with. This column won't be used as a
              feature. 1. When data\_split\_method is CUSTOM, the
              corresponding column should be boolean. The rows with true
              value tag are eval data, and the false are training data. 2.
              When data\_split\_method is SEQ, the first
              DATA\_SPLIT\_EVAL\_FRACTION rows (from smallest to largest) in
              the corresponding column are used as training data, and the
              rest are eval data. It respects the order in Orderable data
              types:
              https://cloud.google.com/bigquery/docs/reference/standard-
              sql/data-types#data-type-properties
          learn_rate_strategy:
              The strategy to determine learn rate for the current
              iteration.
          initial_learn_rate:
              Specifies the initial learning rate for the line search learn
              rate strategy.
          label_class_weights:
              Weights associated with each label class, for rebalancing the
              training data. Only applicable for classification models.
          distance_type:
              Distance type for clustering models.
          num_clusters:
              Number of clusters for clustering models.
          model_uri:
              [Beta] Google Cloud Storage URI from which the model was
              imported. Only applicable for imported models.
          optimization_strategy:
              Optimization strategy for training linear regression models.
          kmeans_initialization_method:
              The method used to initialize the centroids for kmeans
              algorithm.
          kmeans_initialization_column:
              The column used to provide the initial centroids for kmeans
              algorithm when kmeans\_initialization\_method is CUSTOM.
      """,
                        # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions)
                    ),
                ),
                IterationResult=_reflection.GeneratedProtocolMessageType(
                    "IterationResult",
                    (_message.Message,),
                    dict(
                        ClusterInfo=_reflection.GeneratedProtocolMessageType(
                            "ClusterInfo",
                            (_message.Message,),
                            dict(
                                DESCRIPTOR=_MODEL_TRAININGRUN_ITERATIONRESULT_CLUSTERINFO,
                                __module__="google.cloud.bigquery_v2.proto.model_pb2",
                                __doc__="""Information about a single cluster for clustering model.
        
        
        Attributes:
            centroid_id:
                Centroid id.
            cluster_radius:
                Cluster radius, the average distance from centroid to each
                point assigned to the cluster.
            cluster_size:
                Cluster size, the total number of points assigned to the
                cluster.
        """,
                                # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ClusterInfo)
                            ),
                        ),
                        DESCRIPTOR=_MODEL_TRAININGRUN_ITERATIONRESULT,
                        __module__="google.cloud.bigquery_v2.proto.model_pb2",
                        __doc__="""Information about a single iteration of the training run.
      
      
      Attributes:
          index:
              Index of the iteration, 0 based.
          duration_ms:
              Time taken to run the iteration in milliseconds.
          training_loss:
              Loss computed on the training data at the end of iteration.
          eval_loss:
              Loss computed on the eval data at the end of iteration.
          learn_rate:
              Learn rate used for this iteration.
          cluster_infos:
              Information about top clusters for clustering models.
      """,
                        # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.TrainingRun.IterationResult)
                    ),
                ),
                DESCRIPTOR=_MODEL_TRAININGRUN,
                __module__="google.cloud.bigquery_v2.proto.model_pb2",
                __doc__="""Information about a single training query run for the model.
    
    
    Attributes:
        training_options:
            Options that were used for this training run, includes user
            specified and default options that were used.
        start_time:
            The start time of this training run.
        results:
            Output of each iteration run, results.size() <=
            max\_iterations.
        evaluation_metrics:
            The evaluation metrics over training/eval data that were
            computed at the end of training.
    """,
                # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.TrainingRun)
            ),
        ),
        LabelsEntry=_reflection.GeneratedProtocolMessageType(
            "LabelsEntry",
            (_message.Message,),
            dict(
                DESCRIPTOR=_MODEL_LABELSENTRY,
                __module__="google.cloud.bigquery_v2.proto.model_pb2"
                # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model.LabelsEntry)
            ),
        ),
        DESCRIPTOR=_MODEL,
        __module__="google.cloud.bigquery_v2.proto.model_pb2",
        __doc__="""Protocol buffer.

  Attributes:
      etag:
          Output only. A hash of this resource.
      model_reference:
          Required. Unique identifier for this model.
      creation_time:
          Output only. The time when this model was created, in
          millisecs since the epoch.
      last_modified_time:
          Output only. The time when this model was last modified, in
          millisecs since the epoch.
      description:
          [Optional] A user-friendly description of this model.
      friendly_name:
          [Optional] A descriptive name for this model.
      labels:
          [Optional] The labels associated with this model. You can use
          these to organize and group your models. Label keys and values
          can be no longer than 63 characters, can only contain
          lowercase letters, numeric characters, underscores and dashes.
          International characters are allowed. Label values are
          optional. Label keys must start with a letter and each label
          in the list must have a different key.
      expiration_time:
          [Optional] The time when this model expires, in milliseconds
          since the epoch. If not present, the model will persist
          indefinitely. Expired models will be deleted and their storage
          reclaimed. The defaultTableExpirationMs property of the
          encapsulating dataset can be used to set a default
          expirationTime on newly created models.
      location:
          Output only. The geographic location where the model resides.
          This value is inherited from the dataset.
      model_type:
          Output only. Type of the model resource.
      training_runs:
          Output only. Information for all training runs in increasing
          order of start\_time.
      feature_columns:
          Output only. Input feature columns that were used to train
          this model.
      label_columns:
          Output only. Label columns that were used to train this model.
          The output of the model will have a "predicted\_" prefix to
          these columns.
  """,
        # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.Model)
    ),
)
_sym_db.RegisterMessage(Model)
_sym_db.RegisterMessage(Model.KmeansEnums)
_sym_db.RegisterMessage(Model.RegressionMetrics)
_sym_db.RegisterMessage(Model.AggregateClassificationMetrics)
_sym_db.RegisterMessage(Model.BinaryClassificationMetrics)
_sym_db.RegisterMessage(Model.BinaryClassificationMetrics.BinaryConfusionMatrix)
_sym_db.RegisterMessage(Model.MultiClassClassificationMetrics)
_sym_db.RegisterMessage(Model.MultiClassClassificationMetrics.ConfusionMatrix)
_sym_db.RegisterMessage(Model.MultiClassClassificationMetrics.ConfusionMatrix.Entry)
_sym_db.RegisterMessage(Model.MultiClassClassificationMetrics.ConfusionMatrix.Row)
_sym_db.RegisterMessage(Model.ClusteringMetrics)
_sym_db.RegisterMessage(Model.ClusteringMetrics.Cluster)
_sym_db.RegisterMessage(Model.ClusteringMetrics.Cluster.FeatureValue)
_sym_db.RegisterMessage(Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue)
_sym_db.RegisterMessage(
    Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue.CategoryCount
)
_sym_db.RegisterMessage(Model.EvaluationMetrics)
_sym_db.RegisterMessage(Model.TrainingRun)
_sym_db.RegisterMessage(Model.TrainingRun.TrainingOptions)
_sym_db.RegisterMessage(Model.TrainingRun.TrainingOptions.LabelClassWeightsEntry)
_sym_db.RegisterMessage(Model.TrainingRun.IterationResult)
_sym_db.RegisterMessage(Model.TrainingRun.IterationResult.ClusterInfo)
_sym_db.RegisterMessage(Model.LabelsEntry)

GetModelRequest = _reflection.GeneratedProtocolMessageType(
    "GetModelRequest",
    (_message.Message,),
    dict(
        DESCRIPTOR=_GETMODELREQUEST,
        __module__="google.cloud.bigquery_v2.proto.model_pb2",
        __doc__="""Protocol buffer.

  Attributes:
      project_id:
          Project ID of the requested model.
      dataset_id:
          Dataset ID of the requested model.
      model_id:
          Model ID of the requested model.
  """,
        # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.GetModelRequest)
    ),
)
_sym_db.RegisterMessage(GetModelRequest)

PatchModelRequest = _reflection.GeneratedProtocolMessageType(
    "PatchModelRequest",
    (_message.Message,),
    dict(
        DESCRIPTOR=_PATCHMODELREQUEST,
        __module__="google.cloud.bigquery_v2.proto.model_pb2",
        __doc__="""Protocol buffer.

  Attributes:
      project_id:
          Project ID of the model to patch.
      dataset_id:
          Dataset ID of the model to patch.
      model_id:
          Model ID of the model to patch.
      model:
          Patched model. Follows RFC5789 patch semantics. Missing fields
          are not updated. To clear a field, explicitly set to default
          value.
  """,
        # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.PatchModelRequest)
    ),
)
_sym_db.RegisterMessage(PatchModelRequest)

DeleteModelRequest = _reflection.GeneratedProtocolMessageType(
    "DeleteModelRequest",
    (_message.Message,),
    dict(
        DESCRIPTOR=_DELETEMODELREQUEST,
        __module__="google.cloud.bigquery_v2.proto.model_pb2",
        __doc__="""Protocol buffer.

  Attributes:
      project_id:
          Project ID of the model to delete.
      dataset_id:
          Dataset ID of the model to delete.
      model_id:
          Model ID of the model to delete.
  """,
        # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.DeleteModelRequest)
    ),
)
_sym_db.RegisterMessage(DeleteModelRequest)

ListModelsRequest = _reflection.GeneratedProtocolMessageType(
    "ListModelsRequest",
    (_message.Message,),
    dict(
        DESCRIPTOR=_LISTMODELSREQUEST,
        __module__="google.cloud.bigquery_v2.proto.model_pb2",
        __doc__="""Protocol buffer.

  Attributes:
      project_id:
          Project ID of the models to list.
      dataset_id:
          Dataset ID of the models to list.
      max_results:
          The maximum number of results to return in a single response
          page. Leverage the page tokens to iterate through the entire
          collection.
      page_token:
          Page token, returned by a previous call to request the next
          page of results
  """,
        # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.ListModelsRequest)
    ),
)
_sym_db.RegisterMessage(ListModelsRequest)

ListModelsResponse = _reflection.GeneratedProtocolMessageType(
    "ListModelsResponse",
    (_message.Message,),
    dict(
        DESCRIPTOR=_LISTMODELSRESPONSE,
        __module__="google.cloud.bigquery_v2.proto.model_pb2",
        __doc__="""Protocol buffer.

  Attributes:
      models:
          Models in the requested dataset. Only the following fields are
          populated: model\_reference, model\_type, creation\_time,
          last\_modified\_time and labels.
      next_page_token:
          A token to request the next page of results.
  """,
        # @@protoc_insertion_point(class_scope:google.cloud.bigquery.v2.ListModelsResponse)
    ),
)
_sym_db.RegisterMessage(ListModelsResponse)


DESCRIPTOR._options = None
_MODEL_TRAININGRUN_TRAININGOPTIONS_LABELCLASSWEIGHTSENTRY._options = None
_MODEL_LABELSENTRY._options = None

_MODELSERVICE = _descriptor.ServiceDescriptor(
    name="ModelService",
    full_name="google.cloud.bigquery.v2.ModelService",
    file=DESCRIPTOR,
    index=0,
    serialized_options=_b(
        "\312A\027bigquery.googleapis.com\322A\302\001https://www.googleapis.com/auth/bigquery,https://www.googleapis.com/auth/bigquery.readonly,https://www.googleapis.com/auth/cloud-platform,https://www.googleapis.com/auth/cloud-platform.read-only"
    ),
    serialized_start=7509,
    serialized_end=8128,
    methods=[
        _descriptor.MethodDescriptor(
            name="GetModel",
            full_name="google.cloud.bigquery.v2.ModelService.GetModel",
            index=0,
            containing_service=None,
            input_type=_GETMODELREQUEST,
            output_type=_MODEL,
            serialized_options=None,
        ),
        _descriptor.MethodDescriptor(
            name="ListModels",
            full_name="google.cloud.bigquery.v2.ModelService.ListModels",
            index=1,
            containing_service=None,
            input_type=_LISTMODELSREQUEST,
            output_type=_LISTMODELSRESPONSE,
            serialized_options=None,
        ),
        _descriptor.MethodDescriptor(
            name="PatchModel",
            full_name="google.cloud.bigquery.v2.ModelService.PatchModel",
            index=2,
            containing_service=None,
            input_type=_PATCHMODELREQUEST,
            output_type=_MODEL,
            serialized_options=None,
        ),
        _descriptor.MethodDescriptor(
            name="DeleteModel",
            full_name="google.cloud.bigquery.v2.ModelService.DeleteModel",
            index=3,
            containing_service=None,
            input_type=_DELETEMODELREQUEST,
            output_type=google_dot_protobuf_dot_empty__pb2._EMPTY,
            serialized_options=None,
        ),
    ],
)
_sym_db.RegisterServiceDescriptor(_MODELSERVICE)

DESCRIPTOR.services_by_name["ModelService"] = _MODELSERVICE

# @@protoc_insertion_point(module_scope)
