Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::CustomJobSpec.
Represents the spec of a CustomJob. Next Id: 14
Inherits
- Object
Extended By
- Google::Protobuf::MessageExts::ClassMethods
Includes
- Google::Protobuf::MessageExts
Methods
#base_output_directory
def base_output_directory() -> ::Google::Cloud::AIPlatform::V1::GcsDestination
-
(::Google::Cloud::AIPlatform::V1::GcsDestination) —
The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory.
The following Vertex AI environment variables will be passed to containers or python modules when this field is set:
For CustomJob:
- AIP_MODEL_DIR =
<base_output_directory>/model/
- AIP_CHECKPOINT_DIR =
<base_output_directory>/checkpoints/
- AIP_TENSORBOARD_LOG_DIR =
<base_output_directory>/logs/
For CustomJob backing a Trial of HyperparameterTuningJob:
- AIP_MODEL_DIR =
<base_output_directory>/<trial_id>/model/
- AIP_CHECKPOINT_DIR =
<base_output_directory>/<trial_id>/checkpoints/
- AIP_TENSORBOARD_LOG_DIR =
<base_output_directory>/<trial_id>/logs/
- AIP_MODEL_DIR =
#base_output_directory=
def base_output_directory=(value) -> ::Google::Cloud::AIPlatform::V1::GcsDestination
-
value (::Google::Cloud::AIPlatform::V1::GcsDestination) —
The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory.
The following Vertex AI environment variables will be passed to containers or python modules when this field is set:
For CustomJob:
- AIP_MODEL_DIR =
<base_output_directory>/model/
- AIP_CHECKPOINT_DIR =
<base_output_directory>/checkpoints/
- AIP_TENSORBOARD_LOG_DIR =
<base_output_directory>/logs/
For CustomJob backing a Trial of HyperparameterTuningJob:
- AIP_MODEL_DIR =
<base_output_directory>/<trial_id>/model/
- AIP_CHECKPOINT_DIR =
<base_output_directory>/<trial_id>/checkpoints/
- AIP_TENSORBOARD_LOG_DIR =
<base_output_directory>/<trial_id>/logs/
- AIP_MODEL_DIR =
-
(::Google::Cloud::AIPlatform::V1::GcsDestination) —
The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory.
The following Vertex AI environment variables will be passed to containers or python modules when this field is set:
For CustomJob:
- AIP_MODEL_DIR =
<base_output_directory>/model/
- AIP_CHECKPOINT_DIR =
<base_output_directory>/checkpoints/
- AIP_TENSORBOARD_LOG_DIR =
<base_output_directory>/logs/
For CustomJob backing a Trial of HyperparameterTuningJob:
- AIP_MODEL_DIR =
<base_output_directory>/<trial_id>/model/
- AIP_CHECKPOINT_DIR =
<base_output_directory>/<trial_id>/checkpoints/
- AIP_TENSORBOARD_LOG_DIR =
<base_output_directory>/<trial_id>/logs/
- AIP_MODEL_DIR =
#enable_web_access
def enable_web_access() -> ::Boolean
-
(::Boolean) — Optional. Whether you want Vertex AI to enable interactive shell
access
to training containers.
If set to
true
, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
#enable_web_access=
def enable_web_access=(value) -> ::Boolean
-
value (::Boolean) — Optional. Whether you want Vertex AI to enable interactive shell
access
to training containers.
If set to
true
, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
-
(::Boolean) — Optional. Whether you want Vertex AI to enable interactive shell
access
to training containers.
If set to
true
, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
#network
def network() -> ::String
-
(::String) — The full name of the Compute Engine
network to which the Job
should be peered. For example,
projects/12345/global/networks/myVPC
. Format is of the formprojects/{project}/global/networks/{network}
. Where {project} is a project number, as in12345
, and {network} is a network name.To specify this field, you must have already configured VPC Network Peering for Vertex AI.
If this field is left unspecified, the job is not peered with any network.
#network=
def network=(value) -> ::String
-
value (::String) — The full name of the Compute Engine
network to which the Job
should be peered. For example,
projects/12345/global/networks/myVPC
. Format is of the formprojects/{project}/global/networks/{network}
. Where {project} is a project number, as in12345
, and {network} is a network name.To specify this field, you must have already configured VPC Network Peering for Vertex AI.
If this field is left unspecified, the job is not peered with any network.
-
(::String) — The full name of the Compute Engine
network to which the Job
should be peered. For example,
projects/12345/global/networks/myVPC
. Format is of the formprojects/{project}/global/networks/{network}
. Where {project} is a project number, as in12345
, and {network} is a network name.To specify this field, you must have already configured VPC Network Peering for Vertex AI.
If this field is left unspecified, the job is not peered with any network.
#scheduling
def scheduling() -> ::Google::Cloud::AIPlatform::V1::Scheduling
- (::Google::Cloud::AIPlatform::V1::Scheduling) — Scheduling options for a CustomJob.
#scheduling=
def scheduling=(value) -> ::Google::Cloud::AIPlatform::V1::Scheduling
- value (::Google::Cloud::AIPlatform::V1::Scheduling) — Scheduling options for a CustomJob.
- (::Google::Cloud::AIPlatform::V1::Scheduling) — Scheduling options for a CustomJob.
#service_account
def service_account() -> ::String
- (::String) — Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the Vertex AI Custom Code Service Agent for the CustomJob's project is used.
#service_account=
def service_account=(value) -> ::String
- value (::String) — Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the Vertex AI Custom Code Service Agent for the CustomJob's project is used.
- (::String) — Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the Vertex AI Custom Code Service Agent for the CustomJob's project is used.
#tensorboard
def tensorboard() -> ::String
-
(::String) — Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob
will upload Tensorboard logs.
Format:
projects/{project}/locations/{location}/tensorboards/{tensorboard}
#tensorboard=
def tensorboard=(value) -> ::String
-
value (::String) — Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob
will upload Tensorboard logs.
Format:
projects/{project}/locations/{location}/tensorboards/{tensorboard}
-
(::String) — Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob
will upload Tensorboard logs.
Format:
projects/{project}/locations/{location}/tensorboards/{tensorboard}
#worker_pool_specs
def worker_pool_specs() -> ::Array<::Google::Cloud::AIPlatform::V1::WorkerPoolSpec>
- (::Array<::Google::Cloud::AIPlatform::V1::WorkerPoolSpec>) — Required. The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
#worker_pool_specs=
def worker_pool_specs=(value) -> ::Array<::Google::Cloud::AIPlatform::V1::WorkerPoolSpec>
- value (::Array<::Google::Cloud::AIPlatform::V1::WorkerPoolSpec>) — Required. The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
- (::Array<::Google::Cloud::AIPlatform::V1::WorkerPoolSpec>) — Required. The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.