Package org.mlflow.api.proto

Class Service.SearchLoggedModels.Builder

    • Method Detail

      • getDescriptor

        public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

      • internalGetFieldAccessorTable

        protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
        Specified by:
        internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3.Builder<Service.SearchLoggedModels.Builder>

      • getDescriptorForType

        public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
        Specified by:
        getDescriptorForType in interface com.google.protobuf.Message.Builder
        Specified by:
        getDescriptorForType in interface com.google.protobuf.MessageOrBuilder
        Overrides:
        getDescriptorForType in class com.google.protobuf.GeneratedMessageV3.Builder<Service.SearchLoggedModels.Builder>

      • getDefaultInstanceForType

        public Service.SearchLoggedModels getDefaultInstanceForType()
        Specified by:
        getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
        Specified by:
        getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

      • build

        public Service.SearchLoggedModels build()
        Specified by:
        build in interface com.google.protobuf.Message.Builder
        Specified by:
        build in interface com.google.protobuf.MessageLite.Builder

      • buildPartial

        public Service.SearchLoggedModels buildPartial()
        Specified by:
        buildPartial in interface com.google.protobuf.Message.Builder
        Specified by:
        buildPartial in interface com.google.protobuf.MessageLite.Builder

      • setRepeatedField

        public Service.SearchLoggedModels.Builder setRepeatedField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                           int index,
                                                           java.lang.Object value)
        Specified by:
        setRepeatedField in interface com.google.protobuf.Message.Builder
        Overrides:
        setRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<Service.SearchLoggedModels.Builder>

      • addRepeatedField

        public Service.SearchLoggedModels.Builder addRepeatedField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                           java.lang.Object value)
        Specified by:
        addRepeatedField in interface com.google.protobuf.Message.Builder
        Overrides:
        addRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<Service.SearchLoggedModels.Builder>

      • isInitialized

        public final boolean isInitialized()
        Specified by:
        isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
        Overrides:
        isInitialized in class com.google.protobuf.GeneratedMessageV3.Builder<Service.SearchLoggedModels.Builder>

      • mergeFrom

        public Service.SearchLoggedModels.Builder mergeFrom​(com.google.protobuf.CodedInputStream input,
                                                    com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                                             throws java.io.IOException
        Specified by:
        mergeFrom in interface com.google.protobuf.Message.Builder
        Specified by:
        mergeFrom in interface com.google.protobuf.MessageLite.Builder
        Overrides:
        mergeFrom in class com.google.protobuf.AbstractMessage.Builder<Service.SearchLoggedModels.Builder>
        Throws:
        java.io.IOException

      • getExperimentIdsList

        public com.google.protobuf.ProtocolStringList getExperimentIdsList()
         IDs of the Experiments in which to search for Logged Models.
        repeated string experiment_ids = 1;
        Specified by:
        getExperimentIdsList in interface Service.SearchLoggedModelsOrBuilder
        Returns:
        A list containing the experimentIds.

      • getExperimentIdsCount

        public int getExperimentIdsCount()
         IDs of the Experiments in which to search for Logged Models.
        repeated string experiment_ids = 1;
        Specified by:
        getExperimentIdsCount in interface Service.SearchLoggedModelsOrBuilder
        Returns:
        The count of experimentIds.

      • getExperimentIds

        public java.lang.String getExperimentIds​(int index)
         IDs of the Experiments in which to search for Logged Models.
        repeated string experiment_ids = 1;
        Specified by:
        getExperimentIds in interface Service.SearchLoggedModelsOrBuilder
        Parameters:
        index - The index of the element to return.
        Returns:
        The experimentIds at the given index.

      • getExperimentIdsBytes

        public com.google.protobuf.ByteString getExperimentIdsBytes​(int index)
         IDs of the Experiments in which to search for Logged Models.
        repeated string experiment_ids = 1;
        Specified by:
        getExperimentIdsBytes in interface Service.SearchLoggedModelsOrBuilder
        Parameters:
        index - The index of the value to return.
        Returns:
        The bytes of the experimentIds at the given index.

      • setExperimentIds

        public Service.SearchLoggedModels.Builder setExperimentIds​(int index,
                                                           java.lang.String value)
         IDs of the Experiments in which to search for Logged Models.
        repeated string experiment_ids = 1;
        Parameters:
        index - The index to set the value at.
        value - The experimentIds to set.
        Returns:
        This builder for chaining.

      • addExperimentIds

        public Service.SearchLoggedModels.Builder addExperimentIds​(java.lang.String value)
         IDs of the Experiments in which to search for Logged Models.
        repeated string experiment_ids = 1;
        Parameters:
        value - The experimentIds to add.
        Returns:
        This builder for chaining.

      • addAllExperimentIds

        public Service.SearchLoggedModels.Builder addAllExperimentIds​(java.lang.Iterable<java.lang.String> values)
         IDs of the Experiments in which to search for Logged Models.
        repeated string experiment_ids = 1;
        Parameters:
        values - The experimentIds to add.
        Returns:
        This builder for chaining.

      • clearExperimentIds

        public Service.SearchLoggedModels.Builder clearExperimentIds()
         IDs of the Experiments in which to search for Logged Models.
        repeated string experiment_ids = 1;
        Returns:
        This builder for chaining.

      • addExperimentIdsBytes

        public Service.SearchLoggedModels.Builder addExperimentIdsBytes​(com.google.protobuf.ByteString value)
         IDs of the Experiments in which to search for Logged Models.
        repeated string experiment_ids = 1;
        Parameters:
        value - The bytes of the experimentIds to add.
        Returns:
        This builder for chaining.

      • hasFilter

        public boolean hasFilter()
         A filter expression over Logged Model info and data that allows returning a subset of
 Logged Models. The syntax is a subset of SQL that supports ANDing together binary operations
 Example: ``params.alpha < 0.3 AND metrics.accuracy > 0.9``.
        optional string filter = 2;
        Specified by:
        hasFilter in interface Service.SearchLoggedModelsOrBuilder
        Returns:
        Whether the filter field is set.

      • getFilter

        public java.lang.String getFilter()
         A filter expression over Logged Model info and data that allows returning a subset of
 Logged Models. The syntax is a subset of SQL that supports ANDing together binary operations
 Example: ``params.alpha < 0.3 AND metrics.accuracy > 0.9``.
        optional string filter = 2;
        Specified by:
        getFilter in interface Service.SearchLoggedModelsOrBuilder
        Returns:
        The filter.

      • getFilterBytes

        public com.google.protobuf.ByteString getFilterBytes()
         A filter expression over Logged Model info and data that allows returning a subset of
 Logged Models. The syntax is a subset of SQL that supports ANDing together binary operations
 Example: ``params.alpha < 0.3 AND metrics.accuracy > 0.9``.
        optional string filter = 2;
        Specified by:
        getFilterBytes in interface Service.SearchLoggedModelsOrBuilder
        Returns:
        The bytes for filter.

      • setFilter

        public Service.SearchLoggedModels.Builder setFilter​(java.lang.String value)
         A filter expression over Logged Model info and data that allows returning a subset of
 Logged Models. The syntax is a subset of SQL that supports ANDing together binary operations
 Example: ``params.alpha < 0.3 AND metrics.accuracy > 0.9``.
        optional string filter = 2;
        Parameters:
        value - The filter to set.
        Returns:
        This builder for chaining.

      • clearFilter

        public Service.SearchLoggedModels.Builder clearFilter()
         A filter expression over Logged Model info and data that allows returning a subset of
 Logged Models. The syntax is a subset of SQL that supports ANDing together binary operations
 Example: ``params.alpha < 0.3 AND metrics.accuracy > 0.9``.
        optional string filter = 2;
        Returns:
        This builder for chaining.

      • setFilterBytes

        public Service.SearchLoggedModels.Builder setFilterBytes​(com.google.protobuf.ByteString value)
         A filter expression over Logged Model info and data that allows returning a subset of
 Logged Models. The syntax is a subset of SQL that supports ANDing together binary operations
 Example: ``params.alpha < 0.3 AND metrics.accuracy > 0.9``.
        optional string filter = 2;
        Parameters:
        value - The bytes for filter to set.
        Returns:
        This builder for chaining.

      • getDatasetsList

        public java.util.List<Service.SearchLoggedModels.Dataset> getDatasetsList()
         List of datasets on which to apply the metrics filter clauses.
 For example, a filter with `metrics.accuracy > 0.9` and dataset info with name "test_dataset"
 means we will return all logged models with accuracy > 0.9 on the test_dataset.
 Metric values from ANY dataset matching the criteria are considered.
 If no datasets are specified, then metrics across all datasets are considered in the filter.
        repeated .mlflow.SearchLoggedModels.Dataset datasets = 6;
        Specified by:
        getDatasetsList in interface Service.SearchLoggedModelsOrBuilder

      • getDatasetsCount

        public int getDatasetsCount()
         List of datasets on which to apply the metrics filter clauses.
 For example, a filter with `metrics.accuracy > 0.9` and dataset info with name "test_dataset"
 means we will return all logged models with accuracy > 0.9 on the test_dataset.
 Metric values from ANY dataset matching the criteria are considered.
 If no datasets are specified, then metrics across all datasets are considered in the filter.
        repeated .mlflow.SearchLoggedModels.Dataset datasets = 6;
        Specified by:
        getDatasetsCount in interface Service.SearchLoggedModelsOrBuilder

      • getDatasets

        public Service.SearchLoggedModels.Dataset getDatasets​(int index)
         List of datasets on which to apply the metrics filter clauses.
 For example, a filter with `metrics.accuracy > 0.9` and dataset info with name "test_dataset"
 means we will return all logged models with accuracy > 0.9 on the test_dataset.
 Metric values from ANY dataset matching the criteria are considered.
 If no datasets are specified, then metrics across all datasets are considered in the filter.
        repeated .mlflow.SearchLoggedModels.Dataset datasets = 6;
        Specified by:
        getDatasets in interface Service.SearchLoggedModelsOrBuilder

      • setDatasets

        public Service.SearchLoggedModels.Builder setDatasets​(int index,
                                                      Service.SearchLoggedModels.Dataset value)
         List of datasets on which to apply the metrics filter clauses.
 For example, a filter with `metrics.accuracy > 0.9` and dataset info with name "test_dataset"
 means we will return all logged models with accuracy > 0.9 on the test_dataset.
 Metric values from ANY dataset matching the criteria are considered.
 If no datasets are specified, then metrics across all datasets are considered in the filter.
        repeated .mlflow.SearchLoggedModels.Dataset datasets = 6;

      • setDatasets

        public Service.SearchLoggedModels.Builder setDatasets​(int index,
                                                      Service.SearchLoggedModels.Dataset.Builder builderForValue)
         List of datasets on which to apply the metrics filter clauses.
 For example, a filter with `metrics.accuracy > 0.9` and dataset info with name "test_dataset"
 means we will return all logged models with accuracy > 0.9 on the test_dataset.
 Metric values from ANY dataset matching the criteria are considered.
 If no datasets are specified, then metrics across all datasets are considered in the filter.
        repeated .mlflow.SearchLoggedModels.Dataset datasets = 6;

      • addDatasets

        public Service.SearchLoggedModels.Builder addDatasets​(Service.SearchLoggedModels.Dataset value)
         List of datasets on which to apply the metrics filter clauses.
 For example, a filter with `metrics.accuracy > 0.9` and dataset info with name "test_dataset"
 means we will return all logged models with accuracy > 0.9 on the test_dataset.
 Metric values from ANY dataset matching the criteria are considered.
 If no datasets are specified, then metrics across all datasets are considered in the filter.
        repeated .mlflow.SearchLoggedModels.Dataset datasets = 6;

      • addDatasets

        public Service.SearchLoggedModels.Builder addDatasets​(int index,
                                                      Service.SearchLoggedModels.Dataset value)
         List of datasets on which to apply the metrics filter clauses.
 For example, a filter with `metrics.accuracy > 0.9` and dataset info with name "test_dataset"
 means we will return all logged models with accuracy > 0.9 on the test_dataset.
 Metric values from ANY dataset matching the criteria are considered.
 If no datasets are specified, then metrics across all datasets are considered in the filter.
        repeated .mlflow.SearchLoggedModels.Dataset datasets = 6;

      • addDatasets

        public Service.SearchLoggedModels.Builder addDatasets​(Service.SearchLoggedModels.Dataset.Builder builderForValue)
         List of datasets on which to apply the metrics filter clauses.
 For example, a filter with `metrics.accuracy > 0.9` and dataset info with name "test_dataset"
 means we will return all logged models with accuracy > 0.9 on the test_dataset.
 Metric values from ANY dataset matching the criteria are considered.
 If no datasets are specified, then metrics across all datasets are considered in the filter.
        repeated .mlflow.SearchLoggedModels.Dataset datasets = 6;

      • addDatasets

        public Service.SearchLoggedModels.Builder addDatasets​(int index,
                                                      Service.SearchLoggedModels.Dataset.Builder builderForValue)
         List of datasets on which to apply the metrics filter clauses.
 For example, a filter with `metrics.accuracy > 0.9` and dataset info with name "test_dataset"
 means we will return all logged models with accuracy > 0.9 on the test_dataset.
 Metric values from ANY dataset matching the criteria are considered.
 If no datasets are specified, then metrics across all datasets are considered in the filter.
        repeated .mlflow.SearchLoggedModels.Dataset datasets = 6;

      • addAllDatasets

        public Service.SearchLoggedModels.Builder addAllDatasets​(java.lang.Iterable<? extends Service.SearchLoggedModels.Dataset> values)
         List of datasets on which to apply the metrics filter clauses.
 For example, a filter with `metrics.accuracy > 0.9` and dataset info with name "test_dataset"
 means we will return all logged models with accuracy > 0.9 on the test_dataset.
 Metric values from ANY dataset matching the criteria are considered.
 If no datasets are specified, then metrics across all datasets are considered in the filter.
        repeated .mlflow.SearchLoggedModels.Dataset datasets = 6;

      • clearDatasets

        public Service.SearchLoggedModels.Builder clearDatasets()
         List of datasets on which to apply the metrics filter clauses.
 For example, a filter with `metrics.accuracy > 0.9` and dataset info with name "test_dataset"
 means we will return all logged models with accuracy > 0.9 on the test_dataset.
 Metric values from ANY dataset matching the criteria are considered.
 If no datasets are specified, then metrics across all datasets are considered in the filter.
        repeated .mlflow.SearchLoggedModels.Dataset datasets = 6;

      • removeDatasets

        public Service.SearchLoggedModels.Builder removeDatasets​(int index)
         List of datasets on which to apply the metrics filter clauses.
 For example, a filter with `metrics.accuracy > 0.9` and dataset info with name "test_dataset"
 means we will return all logged models with accuracy > 0.9 on the test_dataset.
 Metric values from ANY dataset matching the criteria are considered.
 If no datasets are specified, then metrics across all datasets are considered in the filter.
        repeated .mlflow.SearchLoggedModels.Dataset datasets = 6;

      • getDatasetsBuilder

        public Service.SearchLoggedModels.Dataset.Builder getDatasetsBuilder​(int index)
         List of datasets on which to apply the metrics filter clauses.
 For example, a filter with `metrics.accuracy > 0.9` and dataset info with name "test_dataset"
 means we will return all logged models with accuracy > 0.9 on the test_dataset.
 Metric values from ANY dataset matching the criteria are considered.
 If no datasets are specified, then metrics across all datasets are considered in the filter.
        repeated .mlflow.SearchLoggedModels.Dataset datasets = 6;

      • getDatasetsOrBuilder

        public Service.SearchLoggedModels.DatasetOrBuilder getDatasetsOrBuilder​(int index)
         List of datasets on which to apply the metrics filter clauses.
 For example, a filter with `metrics.accuracy > 0.9` and dataset info with name "test_dataset"
 means we will return all logged models with accuracy > 0.9 on the test_dataset.
 Metric values from ANY dataset matching the criteria are considered.
 If no datasets are specified, then metrics across all datasets are considered in the filter.
        repeated .mlflow.SearchLoggedModels.Dataset datasets = 6;
        Specified by:
        getDatasetsOrBuilder in interface Service.SearchLoggedModelsOrBuilder

      • getDatasetsOrBuilderList

        public java.util.List<? extends Service.SearchLoggedModels.DatasetOrBuilder> getDatasetsOrBuilderList()
         List of datasets on which to apply the metrics filter clauses.
 For example, a filter with `metrics.accuracy > 0.9` and dataset info with name "test_dataset"
 means we will return all logged models with accuracy > 0.9 on the test_dataset.
 Metric values from ANY dataset matching the criteria are considered.
 If no datasets are specified, then metrics across all datasets are considered in the filter.
        repeated .mlflow.SearchLoggedModels.Dataset datasets = 6;
        Specified by:
        getDatasetsOrBuilderList in interface Service.SearchLoggedModelsOrBuilder

      • addDatasetsBuilder

        public Service.SearchLoggedModels.Dataset.Builder addDatasetsBuilder()
         List of datasets on which to apply the metrics filter clauses.
 For example, a filter with `metrics.accuracy > 0.9` and dataset info with name "test_dataset"
 means we will return all logged models with accuracy > 0.9 on the test_dataset.
 Metric values from ANY dataset matching the criteria are considered.
 If no datasets are specified, then metrics across all datasets are considered in the filter.
        repeated .mlflow.SearchLoggedModels.Dataset datasets = 6;

      • addDatasetsBuilder

        public Service.SearchLoggedModels.Dataset.Builder addDatasetsBuilder​(int index)
         List of datasets on which to apply the metrics filter clauses.
 For example, a filter with `metrics.accuracy > 0.9` and dataset info with name "test_dataset"
 means we will return all logged models with accuracy > 0.9 on the test_dataset.
 Metric values from ANY dataset matching the criteria are considered.
 If no datasets are specified, then metrics across all datasets are considered in the filter.
        repeated .mlflow.SearchLoggedModels.Dataset datasets = 6;

      • getDatasetsBuilderList

        public java.util.List<Service.SearchLoggedModels.Dataset.Builder> getDatasetsBuilderList()
         List of datasets on which to apply the metrics filter clauses.
 For example, a filter with `metrics.accuracy > 0.9` and dataset info with name "test_dataset"
 means we will return all logged models with accuracy > 0.9 on the test_dataset.
 Metric values from ANY dataset matching the criteria are considered.
 If no datasets are specified, then metrics across all datasets are considered in the filter.
        repeated .mlflow.SearchLoggedModels.Dataset datasets = 6;

      • hasMaxResults

        public boolean hasMaxResults()
         Maximum number of Logged Models to return. Max threshold is 50.
        optional int32 max_results = 3 [default = 50];
        Specified by:
        hasMaxResults in interface Service.SearchLoggedModelsOrBuilder
        Returns:
        Whether the maxResults field is set.

      • getMaxResults

        public int getMaxResults()
         Maximum number of Logged Models to return. Max threshold is 50.
        optional int32 max_results = 3 [default = 50];
        Specified by:
        getMaxResults in interface Service.SearchLoggedModelsOrBuilder
        Returns:
        The maxResults.

      • setMaxResults

        public Service.SearchLoggedModels.Builder setMaxResults​(int value)
         Maximum number of Logged Models to return. Max threshold is 50.
        optional int32 max_results = 3 [default = 50];
        Parameters:
        value - The maxResults to set.
        Returns:
        This builder for chaining.

      • clearMaxResults

        public Service.SearchLoggedModels.Builder clearMaxResults()
         Maximum number of Logged Models to return. Max threshold is 50.
        optional int32 max_results = 3 [default = 50];
        Returns:
        This builder for chaining.

      • getOrderByCount

        public int getOrderByCount()
         List of columns for ordering the results, with additional fields for sorting criteria.
        repeated .mlflow.SearchLoggedModels.OrderBy order_by = 4;
        Specified by:
        getOrderByCount in interface Service.SearchLoggedModelsOrBuilder

      • clearOrderBy

        public Service.SearchLoggedModels.Builder clearOrderBy()
         List of columns for ordering the results, with additional fields for sorting criteria.
        repeated .mlflow.SearchLoggedModels.OrderBy order_by = 4;

      • removeOrderBy

        public Service.SearchLoggedModels.Builder removeOrderBy​(int index)
         List of columns for ordering the results, with additional fields for sorting criteria.
        repeated .mlflow.SearchLoggedModels.OrderBy order_by = 4;

      • getOrderByBuilder

        public Service.SearchLoggedModels.OrderBy.Builder getOrderByBuilder​(int index)
         List of columns for ordering the results, with additional fields for sorting criteria.
        repeated .mlflow.SearchLoggedModels.OrderBy order_by = 4;

      • addOrderByBuilder

        public Service.SearchLoggedModels.OrderBy.Builder addOrderByBuilder()
         List of columns for ordering the results, with additional fields for sorting criteria.
        repeated .mlflow.SearchLoggedModels.OrderBy order_by = 4;

      • addOrderByBuilder

        public Service.SearchLoggedModels.OrderBy.Builder addOrderByBuilder​(int index)
         List of columns for ordering the results, with additional fields for sorting criteria.
        repeated .mlflow.SearchLoggedModels.OrderBy order_by = 4;

      • getOrderByBuilderList

        public java.util.List<Service.SearchLoggedModels.OrderBy.Builder> getOrderByBuilderList()
         List of columns for ordering the results, with additional fields for sorting criteria.
        repeated .mlflow.SearchLoggedModels.OrderBy order_by = 4;

      • hasPageToken

        public boolean hasPageToken()
         Token indicating the page of Logged Models to fetch.
        optional string page_token = 5;
        Specified by:
        hasPageToken in interface Service.SearchLoggedModelsOrBuilder
        Returns:
        Whether the pageToken field is set.

      • getPageToken

        public java.lang.String getPageToken()
         Token indicating the page of Logged Models to fetch.
        optional string page_token = 5;
        Specified by:
        getPageToken in interface Service.SearchLoggedModelsOrBuilder
        Returns:
        The pageToken.

      • getPageTokenBytes

        public com.google.protobuf.ByteString getPageTokenBytes()
         Token indicating the page of Logged Models to fetch.
        optional string page_token = 5;
        Specified by:
        getPageTokenBytes in interface Service.SearchLoggedModelsOrBuilder
        Returns:
        The bytes for pageToken.

      • setPageToken

        public Service.SearchLoggedModels.Builder setPageToken​(java.lang.String value)
         Token indicating the page of Logged Models to fetch.
        optional string page_token = 5;
        Parameters:
        value - The pageToken to set.
        Returns:
        This builder for chaining.

      • clearPageToken

        public Service.SearchLoggedModels.Builder clearPageToken()
         Token indicating the page of Logged Models to fetch.
        optional string page_token = 5;
        Returns:
        This builder for chaining.

      • setPageTokenBytes

        public Service.SearchLoggedModels.Builder setPageTokenBytes​(com.google.protobuf.ByteString value)
         Token indicating the page of Logged Models to fetch.
        optional string page_token = 5;
        Parameters:
        value - The bytes for pageToken to set.
        Returns:
        This builder for chaining.

      • setUnknownFields

        public final Service.SearchLoggedModels.Builder setUnknownFields​(com.google.protobuf.UnknownFieldSet unknownFields)
        Specified by:
        setUnknownFields in interface com.google.protobuf.Message.Builder
        Overrides:
        setUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<Service.SearchLoggedModels.Builder>

      • mergeUnknownFields

        public final Service.SearchLoggedModels.Builder mergeUnknownFields​(com.google.protobuf.UnknownFieldSet unknownFields)
        Specified by:
        mergeUnknownFields in interface com.google.protobuf.Message.Builder
        Overrides:
        mergeUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<Service.SearchLoggedModels.Builder>