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public static final class TrainingPipeline.Builder extends GeneratedMessageV3.Builder<TrainingPipeline.Builder> implements TrainingPipelineOrBuilder
The TrainingPipeline orchestrates tasks associated with training a Model. It always executes the training task, and optionally may also export data from Vertex AI's Dataset which becomes the training input, upload the Model to Vertex AI, and evaluate the Model.
Protobuf type google.cloud.aiplatform.v1.TrainingPipeline
Inheritance
Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > TrainingPipeline.BuilderImplements
TrainingPipelineOrBuilderStatic Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
Type | Description |
Descriptor |
Methods
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public TrainingPipeline.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Name | Description |
field | FieldDescriptor |
value | Object |
Type | Description |
TrainingPipeline.Builder |
build()
public TrainingPipeline build()
Type | Description |
TrainingPipeline |
buildPartial()
public TrainingPipeline buildPartial()
Type | Description |
TrainingPipeline |
clear()
public TrainingPipeline.Builder clear()
Type | Description |
TrainingPipeline.Builder |
clearCreateTime()
public TrainingPipeline.Builder clearCreateTime()
Output only. Time when the TrainingPipeline was created.
.google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
Type | Description |
TrainingPipeline.Builder |
clearDisplayName()
public TrainingPipeline.Builder clearDisplayName()
Required. The user-defined name of this TrainingPipeline.
string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
Type | Description |
TrainingPipeline.Builder | This builder for chaining. |
clearEncryptionSpec()
public TrainingPipeline.Builder clearEncryptionSpec()
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 |
TrainingPipeline.Builder |
clearEndTime()
public TrainingPipeline.Builder clearEndTime()
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 |
TrainingPipeline.Builder |
clearError()
public TrainingPipeline.Builder clearError()
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 |
TrainingPipeline.Builder |
clearField(Descriptors.FieldDescriptor field)
public TrainingPipeline.Builder clearField(Descriptors.FieldDescriptor field)
Name | Description |
field | FieldDescriptor |
Type | Description |
TrainingPipeline.Builder |
clearInputDataConfig()
public TrainingPipeline.Builder clearInputDataConfig()
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 |
TrainingPipeline.Builder |
clearLabels()
public TrainingPipeline.Builder clearLabels()
Type | Description |
TrainingPipeline.Builder |
clearModelId()
public TrainingPipeline.Builder clearModelId()
Optional. The ID to use for the uploaded Model, which will become the final
component of the model resource name.
This value may be up to 63 characters, and valid characters are
[a-z0-9_-]
. The first character cannot be a number or hyphen.
string model_id = 22 [(.google.api.field_behavior) = OPTIONAL];
Type | Description |
TrainingPipeline.Builder | This builder for chaining. |
clearModelToUpload()
public TrainingPipeline.Builder clearModelToUpload()
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 |
TrainingPipeline.Builder |
clearName()
public TrainingPipeline.Builder clearName()
Output only. Resource name of the TrainingPipeline.
string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
Type | Description |
TrainingPipeline.Builder | This builder for chaining. |
clearOneof(Descriptors.OneofDescriptor oneof)
public TrainingPipeline.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Name | Description |
oneof | OneofDescriptor |
Type | Description |
TrainingPipeline.Builder |
clearParentModel()
public TrainingPipeline.Builder clearParentModel()
Optional. When specify this field, the model_to_upload
will not be uploaded as a
new model, instead, it will become a new version of this parent_model
.
string parent_model = 21 [(.google.api.field_behavior) = OPTIONAL];
Type | Description |
TrainingPipeline.Builder | This builder for chaining. |
clearStartTime()
public TrainingPipeline.Builder clearStartTime()
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 |
TrainingPipeline.Builder |
clearState()
public TrainingPipeline.Builder clearState()
Output only. The detailed state of the pipeline.
.google.cloud.aiplatform.v1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];
Type | Description |
TrainingPipeline.Builder | This builder for chaining. |
clearTrainingTaskDefinition()
public TrainingPipeline.Builder clearTrainingTaskDefinition()
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 |
TrainingPipeline.Builder | This builder for chaining. |
clearTrainingTaskInputs()
public TrainingPipeline.Builder clearTrainingTaskInputs()
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 |
TrainingPipeline.Builder |
clearTrainingTaskMetadata()
public TrainingPipeline.Builder clearTrainingTaskMetadata()
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 |
TrainingPipeline.Builder |
clearUpdateTime()
public TrainingPipeline.Builder clearUpdateTime()
Output only. Time when the TrainingPipeline was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
Type | Description |
TrainingPipeline.Builder |
clone()
public TrainingPipeline.Builder clone()
Type | Description |
TrainingPipeline.Builder |
containsLabels(String key)
public 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 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. |
getCreateTimeBuilder()
public Timestamp.Builder getCreateTimeBuilder()
Output only. Time when the TrainingPipeline was created.
.google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
Type | Description |
Builder |
getCreateTimeOrBuilder()
public 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 |
getDefaultInstanceForType()
public TrainingPipeline getDefaultInstanceForType()
Type | Description |
TrainingPipeline |
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()
Type | Description |
Descriptor |
getDisplayName()
public 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 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 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. |
getEncryptionSpecBuilder()
public EncryptionSpec.Builder getEncryptionSpecBuilder()
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.Builder |
getEncryptionSpecOrBuilder()
public 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 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. |
getEndTimeBuilder()
public Timestamp.Builder getEndTimeBuilder()
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 |
Builder |
getEndTimeOrBuilder()
public 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 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. |
getErrorBuilder()
public Status.Builder getErrorBuilder()
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.Builder |
getErrorOrBuilder()
public 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 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. |
getInputDataConfigBuilder()
public InputDataConfig.Builder getInputDataConfigBuilder()
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.Builder |
getInputDataConfigOrBuilder()
public 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 Map<String,String> getLabels()
Use #getLabelsMap() instead.
Type | Description |
Map<String,String> |
getLabelsCount()
public 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 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 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 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 |
getModelId()
public String getModelId()
Optional. The ID to use for the uploaded Model, which will become the final
component of the model resource name.
This value may be up to 63 characters, and valid characters are
[a-z0-9_-]
. The first character cannot be a number or hyphen.
string model_id = 22 [(.google.api.field_behavior) = OPTIONAL];
Type | Description |
String | The modelId. |
getModelIdBytes()
public ByteString getModelIdBytes()
Optional. The ID to use for the uploaded Model, which will become the final
component of the model resource name.
This value may be up to 63 characters, and valid characters are
[a-z0-9_-]
. The first character cannot be a number or hyphen.
string model_id = 22 [(.google.api.field_behavior) = OPTIONAL];
Type | Description |
ByteString | The bytes for modelId. |
getModelToUpload()
public 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. |
getModelToUploadBuilder()
public Model.Builder getModelToUploadBuilder()
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.Builder |
getModelToUploadOrBuilder()
public 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 |
getMutableLabels()
public Map<String,String> getMutableLabels()
Use alternate mutation accessors instead.
Type | Description |
Map<String,String> |
getName()
public 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 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. |
getParentModel()
public String getParentModel()
Optional. When specify this field, the model_to_upload
will not be uploaded as a
new model, instead, it will become a new version of this parent_model
.
string parent_model = 21 [(.google.api.field_behavior) = OPTIONAL];
Type | Description |
String | The parentModel. |
getParentModelBytes()
public ByteString getParentModelBytes()
Optional. When specify this field, the model_to_upload
will not be uploaded as a
new model, instead, it will become a new version of this parent_model
.
string parent_model = 21 [(.google.api.field_behavior) = OPTIONAL];
Type | Description |
ByteString | The bytes for parentModel. |
getStartTime()
public 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. |
getStartTimeBuilder()
public Timestamp.Builder getStartTimeBuilder()
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 |
Builder |
getStartTimeOrBuilder()
public 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 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 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 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 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 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. |
getTrainingTaskInputsBuilder()
public Value.Builder getTrainingTaskInputsBuilder()
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 |
Builder |
getTrainingTaskInputsOrBuilder()
public 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 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. |
getTrainingTaskMetadataBuilder()
public Value.Builder getTrainingTaskMetadataBuilder()
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 |
Builder |
getTrainingTaskMetadataOrBuilder()
public 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 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. |
getUpdateTimeBuilder()
public Timestamp.Builder getUpdateTimeBuilder()
Output only. Time when the TrainingPipeline was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
Type | Description |
Builder |
getUpdateTimeOrBuilder()
public 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 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 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 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 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 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 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 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 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 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 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. |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Type | Description |
FieldAccessorTable |
internalGetMapField(int number)
protected MapField internalGetMapField(int number)
Name | Description |
number | int |
Type | Description |
MapField |
internalGetMutableMapField(int number)
protected MapField internalGetMutableMapField(int number)
Name | Description |
number | int |
Type | Description |
MapField |
isInitialized()
public final boolean isInitialized()
Type | Description |
boolean |
mergeCreateTime(Timestamp value)
public TrainingPipeline.Builder mergeCreateTime(Timestamp value)
Output only. Time when the TrainingPipeline was created.
.google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
Name | Description |
value | Timestamp |
Type | Description |
TrainingPipeline.Builder |
mergeEncryptionSpec(EncryptionSpec value)
public TrainingPipeline.Builder mergeEncryptionSpec(EncryptionSpec value)
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;
Name | Description |
value | EncryptionSpec |
Type | Description |
TrainingPipeline.Builder |
mergeEndTime(Timestamp value)
public TrainingPipeline.Builder mergeEndTime(Timestamp value)
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];
Name | Description |
value | Timestamp |
Type | Description |
TrainingPipeline.Builder |
mergeError(Status value)
public TrainingPipeline.Builder mergeError(Status value)
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];
Name | Description |
value | com.google.rpc.Status |
Type | Description |
TrainingPipeline.Builder |
mergeFrom(TrainingPipeline other)
public TrainingPipeline.Builder mergeFrom(TrainingPipeline other)
Name | Description |
other | TrainingPipeline |
Type | Description |
TrainingPipeline.Builder |
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public TrainingPipeline.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Name | Description |
input | CodedInputStream |
extensionRegistry | ExtensionRegistryLite |
Type | Description |
TrainingPipeline.Builder |
Type | Description |
IOException |
mergeFrom(Message other)
public TrainingPipeline.Builder mergeFrom(Message other)
Name | Description |
other | Message |
Type | Description |
TrainingPipeline.Builder |
mergeInputDataConfig(InputDataConfig value)
public TrainingPipeline.Builder mergeInputDataConfig(InputDataConfig value)
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;
Name | Description |
value | InputDataConfig |
Type | Description |
TrainingPipeline.Builder |
mergeModelToUpload(Model value)
public TrainingPipeline.Builder mergeModelToUpload(Model value)
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;
Name | Description |
value | Model |
Type | Description |
TrainingPipeline.Builder |
mergeStartTime(Timestamp value)
public TrainingPipeline.Builder mergeStartTime(Timestamp value)
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];
Name | Description |
value | Timestamp |
Type | Description |
TrainingPipeline.Builder |
mergeTrainingTaskInputs(Value value)
public TrainingPipeline.Builder mergeTrainingTaskInputs(Value value)
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];
Name | Description |
value | Value |
Type | Description |
TrainingPipeline.Builder |
mergeTrainingTaskMetadata(Value value)
public TrainingPipeline.Builder mergeTrainingTaskMetadata(Value value)
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];
Name | Description |
value | Value |
Type | Description |
TrainingPipeline.Builder |
mergeUnknownFields(UnknownFieldSet unknownFields)
public final TrainingPipeline.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Name | Description |
unknownFields | UnknownFieldSet |
Type | Description |
TrainingPipeline.Builder |
mergeUpdateTime(Timestamp value)
public TrainingPipeline.Builder mergeUpdateTime(Timestamp value)
Output only. Time when the TrainingPipeline was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
Name | Description |
value | Timestamp |
Type | Description |
TrainingPipeline.Builder |
putAllLabels(Map<String,String> values)
public TrainingPipeline.Builder putAllLabels(Map<String,String> values)
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 |
values | Map<String,String> |
Type | Description |
TrainingPipeline.Builder |
putLabels(String key, String value)
public TrainingPipeline.Builder putLabels(String key, String value)
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 |
value | String |
Type | Description |
TrainingPipeline.Builder |
removeLabels(String key)
public TrainingPipeline.Builder removeLabels(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 |
TrainingPipeline.Builder |
setCreateTime(Timestamp value)
public TrainingPipeline.Builder setCreateTime(Timestamp value)
Output only. Time when the TrainingPipeline was created.
.google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
Name | Description |
value | Timestamp |
Type | Description |
TrainingPipeline.Builder |
setCreateTime(Timestamp.Builder builderForValue)
public TrainingPipeline.Builder setCreateTime(Timestamp.Builder builderForValue)
Output only. Time when the TrainingPipeline was created.
.google.protobuf.Timestamp create_time = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
Name | Description |
builderForValue | Builder |
Type | Description |
TrainingPipeline.Builder |
setDisplayName(String value)
public TrainingPipeline.Builder setDisplayName(String value)
Required. The user-defined name of this TrainingPipeline.
string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
Name | Description |
value | String The displayName to set. |
Type | Description |
TrainingPipeline.Builder | This builder for chaining. |
setDisplayNameBytes(ByteString value)
public TrainingPipeline.Builder setDisplayNameBytes(ByteString value)
Required. The user-defined name of this TrainingPipeline.
string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
Name | Description |
value | ByteString The bytes for displayName to set. |
Type | Description |
TrainingPipeline.Builder | This builder for chaining. |
setEncryptionSpec(EncryptionSpec value)
public TrainingPipeline.Builder setEncryptionSpec(EncryptionSpec value)
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;
Name | Description |
value | EncryptionSpec |
Type | Description |
TrainingPipeline.Builder |
setEncryptionSpec(EncryptionSpec.Builder builderForValue)
public TrainingPipeline.Builder setEncryptionSpec(EncryptionSpec.Builder builderForValue)
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;
Name | Description |
builderForValue | EncryptionSpec.Builder |
Type | Description |
TrainingPipeline.Builder |
setEndTime(Timestamp value)
public TrainingPipeline.Builder setEndTime(Timestamp value)
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];
Name | Description |
value | Timestamp |
Type | Description |
TrainingPipeline.Builder |
setEndTime(Timestamp.Builder builderForValue)
public TrainingPipeline.Builder setEndTime(Timestamp.Builder builderForValue)
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];
Name | Description |
builderForValue | Builder |
Type | Description |
TrainingPipeline.Builder |
setError(Status value)
public TrainingPipeline.Builder setError(Status value)
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];
Name | Description |
value | com.google.rpc.Status |
Type | Description |
TrainingPipeline.Builder |
setError(Status.Builder builderForValue)
public TrainingPipeline.Builder setError(Status.Builder builderForValue)
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];
Name | Description |
builderForValue | com.google.rpc.Status.Builder |
Type | Description |
TrainingPipeline.Builder |
setField(Descriptors.FieldDescriptor field, Object value)
public TrainingPipeline.Builder setField(Descriptors.FieldDescriptor field, Object value)
Name | Description |
field | FieldDescriptor |
value | Object |
Type | Description |
TrainingPipeline.Builder |
setInputDataConfig(InputDataConfig value)
public TrainingPipeline.Builder setInputDataConfig(InputDataConfig value)
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;
Name | Description |
value | InputDataConfig |
Type | Description |
TrainingPipeline.Builder |
setInputDataConfig(InputDataConfig.Builder builderForValue)
public TrainingPipeline.Builder setInputDataConfig(InputDataConfig.Builder builderForValue)
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;
Name | Description |
builderForValue | InputDataConfig.Builder |
Type | Description |
TrainingPipeline.Builder |
setModelId(String value)
public TrainingPipeline.Builder setModelId(String value)
Optional. The ID to use for the uploaded Model, which will become the final
component of the model resource name.
This value may be up to 63 characters, and valid characters are
[a-z0-9_-]
. The first character cannot be a number or hyphen.
string model_id = 22 [(.google.api.field_behavior) = OPTIONAL];
Name | Description |
value | String The modelId to set. |
Type | Description |
TrainingPipeline.Builder | This builder for chaining. |
setModelIdBytes(ByteString value)
public TrainingPipeline.Builder setModelIdBytes(ByteString value)
Optional. The ID to use for the uploaded Model, which will become the final
component of the model resource name.
This value may be up to 63 characters, and valid characters are
[a-z0-9_-]
. The first character cannot be a number or hyphen.
string model_id = 22 [(.google.api.field_behavior) = OPTIONAL];
Name | Description |
value | ByteString The bytes for modelId to set. |
Type | Description |
TrainingPipeline.Builder | This builder for chaining. |
setModelToUpload(Model value)
public TrainingPipeline.Builder setModelToUpload(Model value)
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;
Name | Description |
value | Model |
Type | Description |
TrainingPipeline.Builder |
setModelToUpload(Model.Builder builderForValue)
public TrainingPipeline.Builder setModelToUpload(Model.Builder builderForValue)
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;
Name | Description |
builderForValue | Model.Builder |
Type | Description |
TrainingPipeline.Builder |
setName(String value)
public TrainingPipeline.Builder setName(String value)
Output only. Resource name of the TrainingPipeline.
string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
Name | Description |
value | String The name to set. |
Type | Description |
TrainingPipeline.Builder | This builder for chaining. |
setNameBytes(ByteString value)
public TrainingPipeline.Builder setNameBytes(ByteString value)
Output only. Resource name of the TrainingPipeline.
string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
Name | Description |
value | ByteString The bytes for name to set. |
Type | Description |
TrainingPipeline.Builder | This builder for chaining. |
setParentModel(String value)
public TrainingPipeline.Builder setParentModel(String value)
Optional. When specify this field, the model_to_upload
will not be uploaded as a
new model, instead, it will become a new version of this parent_model
.
string parent_model = 21 [(.google.api.field_behavior) = OPTIONAL];
Name | Description |
value | String The parentModel to set. |
Type | Description |
TrainingPipeline.Builder | This builder for chaining. |
setParentModelBytes(ByteString value)
public TrainingPipeline.Builder setParentModelBytes(ByteString value)
Optional. When specify this field, the model_to_upload
will not be uploaded as a
new model, instead, it will become a new version of this parent_model
.
string parent_model = 21 [(.google.api.field_behavior) = OPTIONAL];
Name | Description |
value | ByteString The bytes for parentModel to set. |
Type | Description |
TrainingPipeline.Builder | This builder for chaining. |
setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
public TrainingPipeline.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Name | Description |
field | FieldDescriptor |
index | int |
value | Object |
Type | Description |
TrainingPipeline.Builder |
setStartTime(Timestamp value)
public TrainingPipeline.Builder setStartTime(Timestamp value)
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];
Name | Description |
value | Timestamp |
Type | Description |
TrainingPipeline.Builder |
setStartTime(Timestamp.Builder builderForValue)
public TrainingPipeline.Builder setStartTime(Timestamp.Builder builderForValue)
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];
Name | Description |
builderForValue | Builder |
Type | Description |
TrainingPipeline.Builder |
setState(PipelineState value)
public TrainingPipeline.Builder setState(PipelineState value)
Output only. The detailed state of the pipeline.
.google.cloud.aiplatform.v1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];
Name | Description |
value | PipelineState The state to set. |
Type | Description |
TrainingPipeline.Builder | This builder for chaining. |
setStateValue(int value)
public TrainingPipeline.Builder setStateValue(int value)
Output only. The detailed state of the pipeline.
.google.cloud.aiplatform.v1.PipelineState state = 9 [(.google.api.field_behavior) = OUTPUT_ONLY];
Name | Description |
value | int The enum numeric value on the wire for state to set. |
Type | Description |
TrainingPipeline.Builder | This builder for chaining. |
setTrainingTaskDefinition(String value)
public TrainingPipeline.Builder setTrainingTaskDefinition(String value)
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];
Name | Description |
value | String The trainingTaskDefinition to set. |
Type | Description |
TrainingPipeline.Builder | This builder for chaining. |
setTrainingTaskDefinitionBytes(ByteString value)
public TrainingPipeline.Builder setTrainingTaskDefinitionBytes(ByteString value)
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];
Name | Description |
value | ByteString The bytes for trainingTaskDefinition to set. |
Type | Description |
TrainingPipeline.Builder | This builder for chaining. |
setTrainingTaskInputs(Value value)
public TrainingPipeline.Builder setTrainingTaskInputs(Value value)
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];
Name | Description |
value | Value |
Type | Description |
TrainingPipeline.Builder |
setTrainingTaskInputs(Value.Builder builderForValue)
public TrainingPipeline.Builder setTrainingTaskInputs(Value.Builder builderForValue)
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];
Name | Description |
builderForValue | Builder |
Type | Description |
TrainingPipeline.Builder |
setTrainingTaskMetadata(Value value)
public TrainingPipeline.Builder setTrainingTaskMetadata(Value value)
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];
Name | Description |
value | Value |
Type | Description |
TrainingPipeline.Builder |
setTrainingTaskMetadata(Value.Builder builderForValue)
public TrainingPipeline.Builder setTrainingTaskMetadata(Value.Builder builderForValue)
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];
Name | Description |
builderForValue | Builder |
Type | Description |
TrainingPipeline.Builder |
setUnknownFields(UnknownFieldSet unknownFields)
public final TrainingPipeline.Builder setUnknownFields(UnknownFieldSet unknownFields)
Name | Description |
unknownFields | UnknownFieldSet |
Type | Description |
TrainingPipeline.Builder |
setUpdateTime(Timestamp value)
public TrainingPipeline.Builder setUpdateTime(Timestamp value)
Output only. Time when the TrainingPipeline was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
Name | Description |
value | Timestamp |
Type | Description |
TrainingPipeline.Builder |
setUpdateTime(Timestamp.Builder builderForValue)
public TrainingPipeline.Builder setUpdateTime(Timestamp.Builder builderForValue)
Output only. Time when the TrainingPipeline was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
Name | Description |
builderForValue | Builder |
Type | Description |
TrainingPipeline.Builder |