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public interface TrainingPipelineOrBuilder extends MessageOrBuilderImplements
MessageOrBuilderMethods
containsLabels(String key)
public abstract boolean containsLabels(String key)The labels with user-defined metadata to organize TrainingPipelines. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
map<string, string> labels = 15;
| Name | Description |
| key | String |
| Type | Description |
| boolean |
getCreateTime()
public abstract Timestamp getCreateTime()Output only. Time when the TrainingPipeline was created.
.google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| Timestamp | The createTime. |
getCreateTimeOrBuilder()
public abstract TimestampOrBuilder getCreateTimeOrBuilder()Output only. Time when the TrainingPipeline was created.
.google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| TimestampOrBuilder |
getDisplayName()
public abstract String getDisplayName()Required. The user-defined name of this TrainingPipeline.
string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
| Type | Description |
| String | The displayName. |
getDisplayNameBytes()
public abstract ByteString getDisplayNameBytes()Required. The user-defined name of this TrainingPipeline.
string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
| Type | Description |
| ByteString | The bytes for displayName. |
getEncryptionSpec()
public abstract EncryptionSpec getEncryptionSpec()Customer-managed encryption key spec for a TrainingPipeline. If set, this TrainingPipeline will be secured by this key. Note: Model trained by this TrainingPipeline is also secured by this key if model_to_upload is not set separately.
.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;
| Type | Description |
| EncryptionSpec | The encryptionSpec. |
getEncryptionSpecOrBuilder()
public abstract EncryptionSpecOrBuilder getEncryptionSpecOrBuilder()Customer-managed encryption key spec for a TrainingPipeline. If set, this TrainingPipeline will be secured by this key. Note: Model trained by this TrainingPipeline is also secured by this key if model_to_upload is not set separately.
.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;
| Type | Description |
| EncryptionSpecOrBuilder |
getEndTime()
public abstract Timestamp getEndTime() Output only. Time when the TrainingPipeline entered any of the following states:
PIPELINE_STATE_SUCCEEDED, PIPELINE_STATE_FAILED,
PIPELINE_STATE_CANCELLED.
.google.protobuf.Timestamp end_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| Timestamp | The endTime. |
getEndTimeOrBuilder()
public abstract TimestampOrBuilder getEndTimeOrBuilder() Output only. Time when the TrainingPipeline entered any of the following states:
PIPELINE_STATE_SUCCEEDED, PIPELINE_STATE_FAILED,
PIPELINE_STATE_CANCELLED.
.google.protobuf.Timestamp end_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| TimestampOrBuilder |
getError()
public abstract Status getError() Output only. Only populated when the pipeline's state is PIPELINE_STATE_FAILED or
PIPELINE_STATE_CANCELLED.
.google.rpc.Status error = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| com.google.rpc.Status | The error. |
getErrorOrBuilder()
public abstract StatusOrBuilder getErrorOrBuilder() Output only. Only populated when the pipeline's state is PIPELINE_STATE_FAILED or
PIPELINE_STATE_CANCELLED.
.google.rpc.Status error = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| com.google.rpc.StatusOrBuilder |
getInputDataConfig()
public abstract InputDataConfig getInputDataConfig()Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's training_task_definition should make clear whether this config is used and if there are any special requirements on how it should be filled. If nothing about this config is mentioned in the training_task_definition, then it should be assumed that the TrainingPipeline does not depend on this configuration.
.google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3;
| Type | Description |
| InputDataConfig | The inputDataConfig. |
getInputDataConfigOrBuilder()
public abstract InputDataConfigOrBuilder getInputDataConfigOrBuilder()Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's training_task_definition should make clear whether this config is used and if there are any special requirements on how it should be filled. If nothing about this config is mentioned in the training_task_definition, then it should be assumed that the TrainingPipeline does not depend on this configuration.
.google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3;
| Type | Description |
| InputDataConfigOrBuilder |
getLabels()
public abstract Map<String,String> getLabels()Use #getLabelsMap() instead.
| Type | Description |
| Map<String,String> |
getLabelsCount()
public abstract int getLabelsCount()The labels with user-defined metadata to organize TrainingPipelines. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
map<string, string> labels = 15;
| Type | Description |
| int |
getLabelsMap()
public abstract Map<String,String> getLabelsMap()The labels with user-defined metadata to organize TrainingPipelines. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
map<string, string> labels = 15;
| Type | Description |
| Map<String,String> |
getLabelsOrDefault(String key, String defaultValue)
public abstract String getLabelsOrDefault(String key, String defaultValue)The labels with user-defined metadata to organize TrainingPipelines. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
map<string, string> labels = 15;
| Name | Description |
| key | String |
| defaultValue | String |
| Type | Description |
| String |
getLabelsOrThrow(String key)
public abstract String getLabelsOrThrow(String key)The labels with user-defined metadata to organize TrainingPipelines. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
map<string, string> labels = 15;
| Name | Description |
| key | String |
| Type | Description |
| String |
getModelToUpload()
public abstract Model getModelToUpload() Describes the Model that may be uploaded (via ModelService.UploadModel)
by this TrainingPipeline. The TrainingPipeline's
training_task_definition should make clear whether this Model
description should be populated, and if there are any special requirements
regarding how it should be filled. If nothing is mentioned in the
training_task_definition, then it should be assumed that this field
should not be filled and the training task either uploads the Model without
a need of this information, or that training task does not support
uploading a Model as part of the pipeline.
When the Pipeline's state becomes PIPELINE_STATE_SUCCEEDED and
the trained Model had been uploaded into Vertex AI, then the
model_to_upload's resource name is populated. The Model
is always uploaded into the Project and Location in which this pipeline
is.
.google.cloud.aiplatform.v1.Model model_to_upload = 7;
| Type | Description |
| Model | The modelToUpload. |
getModelToUploadOrBuilder()
public abstract ModelOrBuilder getModelToUploadOrBuilder() Describes the Model that may be uploaded (via ModelService.UploadModel)
by this TrainingPipeline. The TrainingPipeline's
training_task_definition should make clear whether this Model
description should be populated, and if there are any special requirements
regarding how it should be filled. If nothing is mentioned in the
training_task_definition, then it should be assumed that this field
should not be filled and the training task either uploads the Model without
a need of this information, or that training task does not support
uploading a Model as part of the pipeline.
When the Pipeline's state becomes PIPELINE_STATE_SUCCEEDED and
the trained Model had been uploaded into Vertex AI, then the
model_to_upload's resource name is populated. The Model
is always uploaded into the Project and Location in which this pipeline
is.
.google.cloud.aiplatform.v1.Model model_to_upload = 7;
| Type | Description |
| ModelOrBuilder |
getName()
public abstract String getName()Output only. Resource name of the TrainingPipeline.
string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| String | The name. |
getNameBytes()
public abstract ByteString getNameBytes()Output only. Resource name of the TrainingPipeline.
string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| ByteString | The bytes for name. |
getStartTime()
public abstract Timestamp getStartTime() Output only. Time when the TrainingPipeline for the first time entered the
PIPELINE_STATE_RUNNING state.
.google.protobuf.Timestamp start_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| Timestamp | The startTime. |
getStartTimeOrBuilder()
public abstract TimestampOrBuilder getStartTimeOrBuilder() Output only. Time when the TrainingPipeline for the first time entered the
PIPELINE_STATE_RUNNING state.
.google.protobuf.Timestamp start_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| TimestampOrBuilder |
getState()
public abstract PipelineState getState()Output only. The detailed state of the pipeline.
.google.cloud.aiplatform.v1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| PipelineState | The state. |
getStateValue()
public abstract int getStateValue()Output only. The detailed state of the pipeline.
.google.cloud.aiplatform.v1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| int | The enum numeric value on the wire for state. |
getTrainingTaskDefinition()
public abstract String getTrainingTaskDefinition()Required. A Google Cloud Storage path to the YAML file that defines the training task which is responsible for producing the model artifact, and may also include additional auxiliary work. The definition files that can be used here are found in gs://google-cloud-aiplatform/schema/trainingjob/definition/. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
string training_task_definition = 4 [(.google.api.field_behavior) = REQUIRED];
| Type | Description |
| String | The trainingTaskDefinition. |
getTrainingTaskDefinitionBytes()
public abstract ByteString getTrainingTaskDefinitionBytes()Required. A Google Cloud Storage path to the YAML file that defines the training task which is responsible for producing the model artifact, and may also include additional auxiliary work. The definition files that can be used here are found in gs://google-cloud-aiplatform/schema/trainingjob/definition/. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
string training_task_definition = 4 [(.google.api.field_behavior) = REQUIRED];
| Type | Description |
| ByteString | The bytes for trainingTaskDefinition. |
getTrainingTaskInputs()
public abstract Value getTrainingTaskInputs() Required. The training task's parameter(s), as specified in the
training_task_definition's inputs.
.google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];
| Type | Description |
| Value | The trainingTaskInputs. |
getTrainingTaskInputsOrBuilder()
public abstract ValueOrBuilder getTrainingTaskInputsOrBuilder() Required. The training task's parameter(s), as specified in the
training_task_definition's inputs.
.google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];
| Type | Description |
| ValueOrBuilder |
getTrainingTaskMetadata()
public abstract Value getTrainingTaskMetadata() Output only. The metadata information as specified in the training_task_definition's
metadata. This metadata is an auxiliary runtime and final information
about the training task. While the pipeline is running this information is
populated only at a best effort basis. Only present if the
pipeline's training_task_definition contains metadata object.
.google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| Value | The trainingTaskMetadata. |
getTrainingTaskMetadataOrBuilder()
public abstract ValueOrBuilder getTrainingTaskMetadataOrBuilder() Output only. The metadata information as specified in the training_task_definition's
metadata. This metadata is an auxiliary runtime and final information
about the training task. While the pipeline is running this information is
populated only at a best effort basis. Only present if the
pipeline's training_task_definition contains metadata object.
.google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| ValueOrBuilder |
getUpdateTime()
public abstract Timestamp getUpdateTime()Output only. Time when the TrainingPipeline was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| Timestamp | The updateTime. |
getUpdateTimeOrBuilder()
public abstract TimestampOrBuilder getUpdateTimeOrBuilder()Output only. Time when the TrainingPipeline was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| TimestampOrBuilder |
hasCreateTime()
public abstract boolean hasCreateTime()Output only. Time when the TrainingPipeline was created.
.google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| boolean | Whether the createTime field is set. |
hasEncryptionSpec()
public abstract boolean hasEncryptionSpec()Customer-managed encryption key spec for a TrainingPipeline. If set, this TrainingPipeline will be secured by this key. Note: Model trained by this TrainingPipeline is also secured by this key if model_to_upload is not set separately.
.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 18;
| Type | Description |
| boolean | Whether the encryptionSpec field is set. |
hasEndTime()
public abstract boolean hasEndTime() Output only. Time when the TrainingPipeline entered any of the following states:
PIPELINE_STATE_SUCCEEDED, PIPELINE_STATE_FAILED,
PIPELINE_STATE_CANCELLED.
.google.protobuf.Timestamp end_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| boolean | Whether the endTime field is set. |
hasError()
public abstract boolean hasError() Output only. Only populated when the pipeline's state is PIPELINE_STATE_FAILED or
PIPELINE_STATE_CANCELLED.
.google.rpc.Status error = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| boolean | Whether the error field is set. |
hasInputDataConfig()
public abstract boolean hasInputDataConfig()Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's training_task_definition should make clear whether this config is used and if there are any special requirements on how it should be filled. If nothing about this config is mentioned in the training_task_definition, then it should be assumed that the TrainingPipeline does not depend on this configuration.
.google.cloud.aiplatform.v1.InputDataConfig input_data_config = 3;
| Type | Description |
| boolean | Whether the inputDataConfig field is set. |
hasModelToUpload()
public abstract boolean hasModelToUpload() Describes the Model that may be uploaded (via ModelService.UploadModel)
by this TrainingPipeline. The TrainingPipeline's
training_task_definition should make clear whether this Model
description should be populated, and if there are any special requirements
regarding how it should be filled. If nothing is mentioned in the
training_task_definition, then it should be assumed that this field
should not be filled and the training task either uploads the Model without
a need of this information, or that training task does not support
uploading a Model as part of the pipeline.
When the Pipeline's state becomes PIPELINE_STATE_SUCCEEDED and
the trained Model had been uploaded into Vertex AI, then the
model_to_upload's resource name is populated. The Model
is always uploaded into the Project and Location in which this pipeline
is.
.google.cloud.aiplatform.v1.Model model_to_upload = 7;
| Type | Description |
| boolean | Whether the modelToUpload field is set. |
hasStartTime()
public abstract boolean hasStartTime() Output only. Time when the TrainingPipeline for the first time entered the
PIPELINE_STATE_RUNNING state.
.google.protobuf.Timestamp start_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| boolean | Whether the startTime field is set. |
hasTrainingTaskInputs()
public abstract boolean hasTrainingTaskInputs() Required. The training task's parameter(s), as specified in the
training_task_definition's inputs.
.google.protobuf.Value training_task_inputs = 5 [(.google.api.field_behavior) = REQUIRED];
| Type | Description |
| boolean | Whether the trainingTaskInputs field is set. |
hasTrainingTaskMetadata()
public abstract boolean hasTrainingTaskMetadata() Output only. The metadata information as specified in the training_task_definition's
metadata. This metadata is an auxiliary runtime and final information
about the training task. While the pipeline is running this information is
populated only at a best effort basis. Only present if the
pipeline's training_task_definition contains metadata object.
.google.protobuf.Value training_task_metadata = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| boolean | Whether the trainingTaskMetadata field is set. |
hasUpdateTime()
public abstract boolean hasUpdateTime()Output only. Time when the TrainingPipeline was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
| Type | Description |
| boolean | Whether the updateTime field is set. |