text: # -*- coding: utf-8 -*-
  # Generated by the protocol buffer compiler.  DO NOT EDIT!
  # source: google/cloud/automl_v1beta1/proto/model_evaluation.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.automl_v1beta1.proto import (
      classification_pb2 as google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_classification__pb2,
  )
  from google.cloud.automl_v1beta1.proto import (
      detection_pb2 as google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_detection__pb2,
  )
  from google.cloud.automl_v1beta1.proto import (
      regression_pb2 as google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_regression__pb2,
  )
  from google.cloud.automl_v1beta1.proto import (
      tables_pb2 as google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_tables__pb2,
  )
  from google.cloud.automl_v1beta1.proto import (
      text_extraction_pb2 as google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_text__extraction__pb2,
  )
  from google.cloud.automl_v1beta1.proto import (
      text_sentiment_pb2 as google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_text__sentiment__pb2,
  )
  from google.cloud.automl_v1beta1.proto import (
      translation_pb2 as google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_translation__pb2,
  )
  from google.protobuf import timestamp_pb2 as google_dot_protobuf_dot_timestamp__pb2
  from google.api import annotations_pb2 as google_dot_api_dot_annotations__pb2
  
  
  DESCRIPTOR = _descriptor.FileDescriptor(
      name="google/cloud/automl_v1beta1/proto/model_evaluation.proto",
      package="google.cloud.automl.v1beta1",
      syntax="proto3",
      serialized_options=_b(
          "\n\037com.google.cloud.automl.v1beta1P\001ZAgoogle.golang.org/genproto/googleapis/cloud/automl/v1beta1;automl\312\002\033Google\\Cloud\\AutoMl\\V1beta1"
      ),
      serialized_pb=_b(
          '\n8google/cloud/automl_v1beta1/proto/model_evaluation.proto\x12\x1bgoogle.cloud.automl.v1beta1\x1a\x36google/cloud/automl_v1beta1/proto/classification.proto\x1a\x31google/cloud/automl_v1beta1/proto/detection.proto\x1a\x32google/cloud/automl_v1beta1/proto/regression.proto\x1a.google/cloud/automl_v1beta1/proto/tables.proto\x1a\x37google/cloud/automl_v1beta1/proto/text_extraction.proto\x1a\x36google/cloud/automl_v1beta1/proto/text_sentiment.proto\x1a\x33google/cloud/automl_v1beta1/proto/translation.proto\x1a\x1fgoogle/protobuf/timestamp.proto\x1a\x1cgoogle/api/annotations.proto"\xa7\x07\n\x0fModelEvaluation\x12i\n!classification_evaluation_metrics\x18\x08 \x01(\x0b\x32<.google.cloud.automl.v1beta1.ClassificationEvaluationMetricsH\x00\x12\x61\n\x1dregression_evaluation_metrics\x18\x18 \x01(\x0b\x32\x38.google.cloud.automl.v1beta1.RegressionEvaluationMetricsH\x00\x12\x63\n\x1etranslation_evaluation_metrics\x18\t \x01(\x0b\x32\x39.google.cloud.automl.v1beta1.TranslationEvaluationMetricsH\x00\x12w\n)image_object_detection_evaluation_metrics\x18\x0c \x01(\x0b\x32\x42.google.cloud.automl.v1beta1.ImageObjectDetectionEvaluationMetricsH\x00\x12u\n(video_object_tracking_evaluation_metrics\x18\x0e \x01(\x0b\x32\x41.google.cloud.automl.v1beta1.VideoObjectTrackingEvaluationMetricsH\x00\x12h\n!text_sentiment_evaluation_metrics\x18\x0b \x01(\x0b\x32;.google.cloud.automl.v1beta1.TextSentimentEvaluationMetricsH\x00\x12j\n"text_extraction_evaluation_metrics\x18\r \x01(\x0b\x32<.google.cloud.automl.v1beta1.TextExtractionEvaluationMetricsH\x00\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x1a\n\x12\x61nnotation_spec_id\x18\x02 \x01(\t\x12\x14\n\x0c\x64isplay_name\x18\x0f \x01(\t\x12/\n\x0b\x63reate_time\x18\x05 \x01(\x0b\x32\x1a.google.protobuf.Timestamp\x12\x1f\n\x17\x65valuated_example_count\x18\x06 \x01(\x05\x42\t\n\x07metricsB\x84\x01\n\x1f\x63om.google.cloud.automl.v1beta1P\x01ZAgoogle.golang.org/genproto/googleapis/cloud/automl/v1beta1;automl\xca\x02\x1bGoogle\\Cloud\\AutoMl\\V1beta1b\x06proto3'
      ),
      dependencies=[
          google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_classification__pb2.DESCRIPTOR,
          google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_detection__pb2.DESCRIPTOR,
          google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_regression__pb2.DESCRIPTOR,
          google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_tables__pb2.DESCRIPTOR,
          google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_text__extraction__pb2.DESCRIPTOR,
          google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_text__sentiment__pb2.DESCRIPTOR,
          google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_translation__pb2.DESCRIPTOR,
          google_dot_protobuf_dot_timestamp__pb2.DESCRIPTOR,
          google_dot_api_dot_annotations__pb2.DESCRIPTOR,
      ],
  )
  
  
  _MODELEVALUATION = _descriptor.Descriptor(
      name="ModelEvaluation",
      full_name="google.cloud.automl.v1beta1.ModelEvaluation",
      filename=None,
      file=DESCRIPTOR,
      containing_type=None,
      fields=[
          _descriptor.FieldDescriptor(
              name="classification_evaluation_metrics",
              full_name="google.cloud.automl.v1beta1.ModelEvaluation.classification_evaluation_metrics",
              index=0,
              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="regression_evaluation_metrics",
              full_name="google.cloud.automl.v1beta1.ModelEvaluation.regression_evaluation_metrics",
              index=1,
              number=24,
              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="translation_evaluation_metrics",
              full_name="google.cloud.automl.v1beta1.ModelEvaluation.translation_evaluation_metrics",
              index=2,
              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,
          ),
          _descriptor.FieldDescriptor(
              name="image_object_detection_evaluation_metrics",
              full_name="google.cloud.automl.v1beta1.ModelEvaluation.image_object_detection_evaluation_metrics",
              index=3,
              number=12,
              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="video_object_tracking_evaluation_metrics",
              full_name="google.cloud.automl.v1beta1.ModelEvaluation.video_object_tracking_evaluation_metrics",
              index=4,
              number=14,
              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="text_sentiment_evaluation_metrics",
              full_name="google.cloud.automl.v1beta1.ModelEvaluation.text_sentiment_evaluation_metrics",
              index=5,
              number=11,
              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="text_extraction_evaluation_metrics",
              full_name="google.cloud.automl.v1beta1.ModelEvaluation.text_extraction_evaluation_metrics",
              index=6,
              number=13,
              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="name",
              full_name="google.cloud.automl.v1beta1.ModelEvaluation.name",
              index=7,
              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="annotation_spec_id",
              full_name="google.cloud.automl.v1beta1.ModelEvaluation.annotation_spec_id",
              index=8,
              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="display_name",
              full_name="google.cloud.automl.v1beta1.ModelEvaluation.display_name",
              index=9,
              number=15,
              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="create_time",
              full_name="google.cloud.automl.v1beta1.ModelEvaluation.create_time",
              index=10,
              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="evaluated_example_count",
              full_name="google.cloud.automl.v1beta1.ModelEvaluation.evaluated_example_count",
              index=11,
              number=6,
              type=5,
              cpp_type=1,
              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,
          ),
      ],
      extensions=[],
      nested_types=[],
      enum_types=[],
      serialized_options=None,
      is_extendable=False,
      syntax="proto3",
      extension_ranges=[],
      oneofs=[
          _descriptor.OneofDescriptor(
              name="metrics",
              full_name="google.cloud.automl.v1beta1.ModelEvaluation.metrics",
              index=0,
              containing_type=None,
              fields=[],
          )
      ],
      serialized_start=526,
      serialized_end=1461,
  )
  
  _MODELEVALUATION.fields_by_name[
      "classification_evaluation_metrics"
  ].message_type = (
      google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_classification__pb2._CLASSIFICATIONEVALUATIONMETRICS
  )
  _MODELEVALUATION.fields_by_name[
      "regression_evaluation_metrics"
  ].message_type = (
      google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_regression__pb2._REGRESSIONEVALUATIONMETRICS
  )
  _MODELEVALUATION.fields_by_name[
      "translation_evaluation_metrics"
  ].message_type = (
      google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_translation__pb2._TRANSLATIONEVALUATIONMETRICS
  )
  _MODELEVALUATION.fields_by_name[
      "image_object_detection_evaluation_metrics"
  ].message_type = (
      google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_detection__pb2._IMAGEOBJECTDETECTIONEVALUATIONMETRICS
  )
  _MODELEVALUATION.fields_by_name[
      "video_object_tracking_evaluation_metrics"
  ].message_type = (
      google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_detection__pb2._VIDEOOBJECTTRACKINGEVALUATIONMETRICS
  )
  _MODELEVALUATION.fields_by_name[
      "text_sentiment_evaluation_metrics"
  ].message_type = (
      google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_text__sentiment__pb2._TEXTSENTIMENTEVALUATIONMETRICS
  )
  _MODELEVALUATION.fields_by_name[
      "text_extraction_evaluation_metrics"
  ].message_type = (
      google_dot_cloud_dot_automl__v1beta1_dot_proto_dot_text__extraction__pb2._TEXTEXTRACTIONEVALUATIONMETRICS
  )
  _MODELEVALUATION.fields_by_name[
      "create_time"
  ].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
  _MODELEVALUATION.oneofs_by_name["metrics"].fields.append(
      _MODELEVALUATION.fields_by_name["classification_evaluation_metrics"]
  )
  _MODELEVALUATION.fields_by_name[
      "classification_evaluation_metrics"
  ].containing_oneof = _MODELEVALUATION.oneofs_by_name["metrics"]
  _MODELEVALUATION.oneofs_by_name["metrics"].fields.append(
      _MODELEVALUATION.fields_by_name["regression_evaluation_metrics"]
  )
  _MODELEVALUATION.fields_by_name[
      "regression_evaluation_metrics"
  ].containing_oneof = _MODELEVALUATION.oneofs_by_name["metrics"]
  _MODELEVALUATION.oneofs_by_name["metrics"].fields.append(
      _MODELEVALUATION.fields_by_name["translation_evaluation_metrics"]
  )
  _MODELEVALUATION.fields_by_name[
      "translation_evaluation_metrics"
  ].containing_oneof = _MODELEVALUATION.oneofs_by_name["metrics"]
  _MODELEVALUATION.oneofs_by_name["metrics"].fields.append(
      _MODELEVALUATION.fields_by_name["image_object_detection_evaluation_metrics"]
  )
  _MODELEVALUATION.fields_by_name[
      "image_object_detection_evaluation_metrics"
  ].containing_oneof = _MODELEVALUATION.oneofs_by_name["metrics"]
  _MODELEVALUATION.oneofs_by_name["metrics"].fields.append(
      _MODELEVALUATION.fields_by_name["video_object_tracking_evaluation_metrics"]
  )
  _MODELEVALUATION.fields_by_name[
      "video_object_tracking_evaluation_metrics"
  ].containing_oneof = _MODELEVALUATION.oneofs_by_name["metrics"]
  _MODELEVALUATION.oneofs_by_name["metrics"].fields.append(
      _MODELEVALUATION.fields_by_name["text_sentiment_evaluation_metrics"]
  )
  _MODELEVALUATION.fields_by_name[
      "text_sentiment_evaluation_metrics"
  ].containing_oneof = _MODELEVALUATION.oneofs_by_name["metrics"]
  _MODELEVALUATION.oneofs_by_name["metrics"].fields.append(
      _MODELEVALUATION.fields_by_name["text_extraction_evaluation_metrics"]
  )
  _MODELEVALUATION.fields_by_name[
      "text_extraction_evaluation_metrics"
  ].containing_oneof = _MODELEVALUATION.oneofs_by_name["metrics"]
  DESCRIPTOR.message_types_by_name["ModelEvaluation"] = _MODELEVALUATION
  _sym_db.RegisterFileDescriptor(DESCRIPTOR)
  
  ModelEvaluation = _reflection.GeneratedProtocolMessageType(
      "ModelEvaluation",
      (_message.Message,),
      dict(
          DESCRIPTOR=_MODELEVALUATION,
          __module__="google.cloud.automl_v1beta1.proto.model_evaluation_pb2",
          __doc__="""Evaluation results of a model.
    
    
    Attributes:
        metrics:
            Output only. Problem type specific evaluation metrics.
        classification_evaluation_metrics:
            Model evaluation metrics for image, text, video and tables
            classification. Tables problem is considered a classification
            when the target column is CATEGORY DataType.
        regression_evaluation_metrics:
            Model evaluation metrics for Tables regression. Tables problem
            is considered a regression when the target column has FLOAT64
            DataType.
        translation_evaluation_metrics:
            Model evaluation metrics for translation.
        image_object_detection_evaluation_metrics:
            Model evaluation metrics for image object detection.
        video_object_tracking_evaluation_metrics:
            Model evaluation metrics for video object tracking.
        text_sentiment_evaluation_metrics:
            Evaluation metrics for text sentiment models.
        text_extraction_evaluation_metrics:
            Evaluation metrics for text extraction models.
        name:
            Output only. Resource name of the model evaluation. Format:  `
            `projects/{project_id}/locations/{location_id}/models/{model_i
            d}/modelEvaluations/{model_evaluation_id}``
        annotation_spec_id:
            Output only. The ID of the annotation spec that the model
            evaluation applies to. The The ID is empty for the overall
            model evaluation. For Tables annotation specs in the dataset
            do not exist and this ID is always not set, but for
            CLASSIFICATION  [prediction\_type-s][google.cloud.automl.v1bet
            a1.TablesModelMetadata.prediction\_type] the [display\_name][g
            oogle.cloud.automl.v1beta1.ModelEvaluation.display\_name]
            field is used.
        display_name:
            Output only. The value of [display\_name][google.cloud.automl.
            v1beta1.AnnotationSpec.dispay\_name] at the moment when the
            model was trained. Because this field returns a value at model
            training time, for different models trained from the same
            dataset, the values may differ, since display names could had
            been changed between the two model's trainings. For Tables
            CLASSIFICATION  [prediction\_type-s][google.cloud.automl.v1bet
            a1.TablesModelMetadata.prediction\_type] distinct values of
            the target column at the moment of the model evaluation are
            populated here. The display\_name is empty for the overall
            model evaluation.
        create_time:
            Output only. Timestamp when this model evaluation was created.
        evaluated_example_count:
            Output only. The number of examples used for model evaluation,
            i.e. for which ground truth from time of model creation is
            compared against the predicted annotations created by the
            model. For overall ModelEvaluation (i.e. with
            annotation\_spec\_id not set) this is the total number of all
            examples used for evaluation. Otherwise, this is the count of
            examples that according to the ground truth were annotated by
            the  [annotation\_spec\_id][google.cloud.automl.v1beta1.ModelE
            valuation.annotation\_spec\_id].
    """,
          # @@protoc_insertion_point(class_scope:google.cloud.automl.v1beta1.ModelEvaluation)
      ),
  )
  _sym_db.RegisterMessage(ModelEvaluation)
  
  
  DESCRIPTOR._options = None
  # @@protoc_insertion_point(module_scope)
  