Returns the operations Resource.
batchCancel(parent, body=None, x__xgafv=None)
Batch cancel PipelineJobs. Firstly the server will check if all the jobs are in non-terminal states, and skip the jobs that are already terminated. If the operation failed, none of the pipeline jobs are cancelled. The server will poll the states of all the pipeline jobs periodically to check the cancellation status. This operation will return an LRO.
batchDelete(parent, body=None, x__xgafv=None)
Batch deletes PipelineJobs The Operation is atomic. If it fails, none of the PipelineJobs are deleted. If it succeeds, all of the PipelineJobs are deleted.
cancel(name, body=None, x__xgafv=None)
Cancels a PipelineJob. Starts asynchronous cancellation on the PipelineJob. The server makes a best effort to cancel the pipeline, but success is not guaranteed. Clients can use PipelineService.GetPipelineJob or other methods to check whether the cancellation succeeded or whether the pipeline completed despite cancellation. On successful cancellation, the PipelineJob is not deleted; instead it becomes a pipeline with a PipelineJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and PipelineJob.state is set to `CANCELLED`.
Close httplib2 connections.
create(parent, body=None, pipelineJobId=None, x__xgafv=None)
Creates a PipelineJob. A PipelineJob will run immediately when created.
Deletes a PipelineJob.
Gets a PipelineJob.
list(parent, filter=None, orderBy=None, pageSize=None, pageToken=None, readMask=None, x__xgafv=None)
Lists PipelineJobs in a Location.
Retrieves the next page of results.
batchCancel(parent, body=None, x__xgafv=None)
Batch cancel PipelineJobs. Firstly the server will check if all the jobs are in non-terminal states, and skip the jobs that are already terminated. If the operation failed, none of the pipeline jobs are cancelled. The server will poll the states of all the pipeline jobs periodically to check the cancellation status. This operation will return an LRO.
Args:
parent: string, Required. The name of the PipelineJobs' parent resource. Format: `projects/{project}/locations/{location}` (required)
body: object, The request body.
The object takes the form of:
{ # Request message for PipelineService.BatchCancelPipelineJobs.
"names": [ # Required. The names of the PipelineJobs to cancel. A maximum of 32 PipelineJobs can be cancelled in a batch. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipelineJob}`
"A String",
],
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
"response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}
batchDelete(parent, body=None, x__xgafv=None)
Batch deletes PipelineJobs The Operation is atomic. If it fails, none of the PipelineJobs are deleted. If it succeeds, all of the PipelineJobs are deleted.
Args:
parent: string, Required. The name of the PipelineJobs' parent resource. Format: `projects/{project}/locations/{location}` (required)
body: object, The request body.
The object takes the form of:
{ # Request message for PipelineService.BatchDeletePipelineJobs.
"names": [ # Required. The names of the PipelineJobs to delete. A maximum of 32 PipelineJobs can be deleted in a batch. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipelineJob}`
"A String",
],
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
"response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}
cancel(name, body=None, x__xgafv=None)
Cancels a PipelineJob. Starts asynchronous cancellation on the PipelineJob. The server makes a best effort to cancel the pipeline, but success is not guaranteed. Clients can use PipelineService.GetPipelineJob or other methods to check whether the cancellation succeeded or whether the pipeline completed despite cancellation. On successful cancellation, the PipelineJob is not deleted; instead it becomes a pipeline with a PipelineJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and PipelineJob.state is set to `CANCELLED`.
Args:
name: string, Required. The name of the PipelineJob to cancel. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}` (required)
body: object, The request body.
The object takes the form of:
{ # Request message for PipelineService.CancelPipelineJob.
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }
}
close()
Close httplib2 connections.
create(parent, body=None, pipelineJobId=None, x__xgafv=None)
Creates a PipelineJob. A PipelineJob will run immediately when created.
Args:
parent: string, Required. The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}` (required)
body: object, The request body.
The object takes the form of:
{ # An instance of a machine learning PipelineJob.
"createTime": "A String", # Output only. Pipeline creation time.
"displayName": "A String", # The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
"kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
},
"endTime": "A String", # Output only. Pipeline end time.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"jobDetail": { # The runtime detail of PipelineJob. # Output only. The details of pipeline run. Not available in the list view.
"pipelineContext": { # Instance of a general context. # Output only. The context of the pipeline.
"createTime": "A String", # Output only. Timestamp when this Context was created.
"description": "A String", # Description of the Context
"displayName": "A String", # User provided display name of the Context. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Contexts. 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. No more than 64 user labels can be associated with one Context (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Immutable. The resource name of the Context.
"parentContexts": [ # Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
"A String",
],
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"updateTime": "A String", # Output only. Timestamp when this Context was last updated.
},
"pipelineRunContext": { # Instance of a general context. # Output only. The context of the current pipeline run.
"createTime": "A String", # Output only. Timestamp when this Context was created.
"description": "A String", # Description of the Context
"displayName": "A String", # User provided display name of the Context. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Contexts. 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. No more than 64 user labels can be associated with one Context (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Immutable. The resource name of the Context.
"parentContexts": [ # Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
"A String",
],
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"updateTime": "A String", # Output only. Timestamp when this Context was last updated.
},
"taskDetails": [ # Output only. The runtime details of the tasks under the pipeline.
{ # The runtime detail of a task execution.
"createTime": "A String", # Output only. Task create time.
"endTime": "A String", # Output only. Task end time.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"execution": { # Instance of a general execution. # Output only. The execution metadata of the task.
"createTime": "A String", # Output only. Timestamp when this Execution was created.
"description": "A String", # Description of the Execution
"displayName": "A String", # User provided display name of the Execution. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Executions. 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. No more than 64 user labels can be associated with one Execution (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Execution.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Execution was last updated.
},
"executorDetail": { # The runtime detail of a pipeline executor. # Output only. The detailed execution info.
"containerDetail": { # The detail of a container execution. It contains the job names of the lifecycle of a container execution. # Output only. The detailed info for a container executor.
"failedMainJobs": [ # Output only. The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order.
"A String",
],
"failedPreCachingCheckJobs": [ # Output only. The names of the previously failed CustomJob for the pre-caching-check container executions. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events. The list includes the all attempts in chronological order.
"A String",
],
"mainJob": "A String", # Output only. The name of the CustomJob for the main container execution.
"preCachingCheckJob": "A String", # Output only. The name of the CustomJob for the pre-caching-check container execution. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events.
},
"customJobDetail": { # The detailed info for a custom job executor. # Output only. The detailed info for a custom job executor.
"failedJobs": [ # Output only. The names of the previously failed CustomJob. The list includes the all attempts in chronological order.
"A String",
],
"job": "A String", # Output only. The name of the CustomJob.
},
},
"inputs": { # Output only. The runtime input artifacts of the task.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Output only. A list of artifact metadata.
{ # Instance of a general artifact.
"createTime": "A String", # Output only. Timestamp when this Artifact was created.
"description": "A String", # Description of the Artifact
"displayName": "A String", # User provided display name of the Artifact. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Artifacts. 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. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Artifact.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Artifact was last updated.
"uri": "A String", # The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
},
],
},
},
"outputs": { # Output only. The runtime output artifacts of the task.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Output only. A list of artifact metadata.
{ # Instance of a general artifact.
"createTime": "A String", # Output only. Timestamp when this Artifact was created.
"description": "A String", # Description of the Artifact
"displayName": "A String", # User provided display name of the Artifact. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Artifacts. 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. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Artifact.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Artifact was last updated.
"uri": "A String", # The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
},
],
},
},
"parentTaskId": "A String", # Output only. The id of the parent task if the task is within a component scope. Empty if the task is at the root level.
"pipelineTaskStatus": [ # Output only. A list of task status. This field keeps a record of task status evolving over time.
{ # A single record of the task status.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during the state. May be set when the state is any of the non-final state (PENDING/RUNNING/CANCELLING) or FAILED state. If the state is FAILED, the error here is final and not going to be retried. If the state is a non-final state, the error indicates a system-error being retried.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"state": "A String", # Output only. The state of the task.
"updateTime": "A String", # Output only. Update time of this status.
},
],
"startTime": "A String", # Output only. Task start time.
"state": "A String", # Output only. State of the task.
"taskId": "A String", # Output only. The system generated ID of the task.
"taskName": "A String", # Output only. The user specified name of the task that is defined in pipeline_spec.
},
],
},
"labels": { # The labels with user-defined metadata to organize PipelineJob. 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. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.
"a_key": "A String",
},
"name": "A String", # Output only. The resource name of the PipelineJob.
"network": "A String", # The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.
"originalPipelineJobId": "A String", # Optional. The original pipeline job id if this pipeline job is a rerun of a previous pipeline job.
"pipelineSpec": { # The spec of the pipeline.
"a_key": "", # Properties of the object.
},
"pipelineTaskRerunConfigs": [ # Optional. The rerun configs for each task in the pipeline job. By default, the rerun will: 1. Use the same input artifacts as the original run. 2. Use the same input parameters as the original run. 3. Skip all the tasks that are already succeeded in the original run. 4. Rerun all the tasks that are not succeeded in the original run. By providing this field, users can override the default behavior and specify the rerun config for each task.
{ # User provided rerun config to submit a rerun pipelinejob. This includes 1. Which task to rerun 2. User override input parameters and artifacts.
"inputs": { # Runtime inputs data of the task. # Optional. The runtime input of the task overridden by the user.
"artifacts": { # Optional. Input artifacts.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Optional. A list of artifact metadata.
{ # The definition of a runtime artifact.
"customProperties": { # The custom properties of the artifact. Deprecated. Use RuntimeArtifact.metadata instead.
"a_key": { # Value is the value of the field.
"doubleValue": 3.14, # A double value.
"intValue": "A String", # An integer value.
"stringValue": "A String", # A string value.
},
},
"metadata": { # Properties of the Artifact.
"a_key": "", # Properties of the object.
},
"name": "A String", # The name of an artifact.
"properties": { # The properties of the artifact. Deprecated. Use RuntimeArtifact.metadata instead.
"a_key": { # Value is the value of the field.
"doubleValue": 3.14, # A double value.
"intValue": "A String", # An integer value.
"stringValue": "A String", # A string value.
},
},
"type": { # The definition of a artifact type in MLMD. # The type of the artifact.
"instanceSchema": "A String", # Contains a raw YAML string, describing the format of the properties of the type.
"schemaTitle": "A String", # The name of the type. The format of the title must be: `.`. Examples: - `aiplatform.Model` - `acme.CustomModel` When this field is set, the type must be pre-registered in the MLMD store.
"schemaUri": "A String", # Points to a YAML file stored on Cloud Storage describing the format. Deprecated. Use PipelineArtifactTypeSchema.schema_title or PipelineArtifactTypeSchema.instance_schema instead.
"schemaVersion": "A String", # The schema version of the artifact. If the value is not set, it defaults to the latest version in the system.
},
"uri": "A String", # The URI of the artifact.
},
],
},
},
"parameterValues": { # Optional. Input parameters.
"a_key": "",
},
},
"skipDownstreamTasks": True or False, # Optional. Whether to skip downstream tasks. Default value is False.
"skipTask": True or False, # Optional. Whether to skip this task. Default value is False.
"taskId": "A String", # Optional. The system generated ID of the task. Retrieved from original run.
"taskName": "A String", # Optional. The name of the task.
},
],
"preflightValidations": True or False, # Optional. Whether to do component level validations before job creation.
"pscInterfaceConfig": { # Configuration for PSC-I. # Optional. Configuration for PSC-I for PipelineJob.
"networkAttachment": "A String", # Optional. The name of the Compute Engine [network attachment](https://cloud.google.com/vpc/docs/about-network-attachments) to attach to the resource within the region and user project. To specify this field, you must have already [created a network attachment] (https://cloud.google.com/vpc/docs/create-manage-network-attachments#create-network-attachments). This field is only used for resources using PSC-I.
},
"reservedIpRanges": [ # A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
"A String",
],
"runtimeConfig": { # The runtime config of a PipelineJob. # Runtime config of the pipeline.
"defaultRuntime": { # The default runtime for the PipelineJob. # Optional. The default runtime for the PipelineJob. If not provided, Vertex Custom Job(on demand) is used as the runtime. For Vertex Custom Job, please refer to https://cloud.google.com/vertex-ai/docs/training/overview.
"persistentResourceRuntimeDetail": { # Persistent resource based runtime detail. For more information, refer to https://cloud.google.com/vertex-ai/docs/training/persistent-resource-overview # Persistent resource based runtime detail.
"persistentResourceName": "A String", # Persistent resource name. Format: `projects/{project}/locations/{location}/persistentResources/{persistent_resource}`
"taskResourceUnavailableTimeoutBehavior": "A String", # Specifies the behavior to take if the timeout is reached.
"taskResourceUnavailableWaitTimeMs": "A String", # The max time a pipeline task waits for the required CPU, memory, or accelerator resource to become available from the specified persistent resource. Default wait time is 0.
},
},
"failurePolicy": "A String", # Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.
"gcsOutputDirectory": "A String", # Required. A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.
"inputArtifacts": { # The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
"a_key": { # The type of an input artifact.
"artifactId": "A String", # Artifact resource id from MLMD. Which is the last portion of an artifact resource name: `projects/{project}/locations/{location}/metadataStores/default/artifacts/{artifact_id}`. The artifact must stay within the same project, location and default metadatastore as the pipeline.
},
},
"parameterValues": { # The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL.
"a_key": "",
},
"parameters": { # Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.
"a_key": { # Value is the value of the field.
"doubleValue": 3.14, # A double value.
"intValue": "A String", # An integer value.
"stringValue": "A String", # A string value.
},
},
},
"satisfiesPzi": True or False, # Output only. Reserved for future use.
"satisfiesPzs": True or False, # Output only. Reserved for future use.
"scheduleName": "A String", # Output only. The schedule resource name. Only returned if the Pipeline is created by Schedule API.
"serviceAccount": "A String", # The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.
"startTime": "A String", # Output only. Pipeline start time.
"state": "A String", # Output only. The detailed state of the job.
"templateMetadata": { # Pipeline template metadata if PipelineJob.template_uri is from supported template registry. Currently, the only supported registry is Artifact Registry. # Output only. Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.
"version": "A String", # The version_name in artifact registry. Will always be presented in output if the PipelineJob.template_uri is from supported template registry. Format is "sha256:abcdef123456...".
},
"templateUri": "A String", # A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.
"updateTime": "A String", # Output only. Timestamp when this PipelineJob was most recently updated.
}
pipelineJobId: string, The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # An instance of a machine learning PipelineJob.
"createTime": "A String", # Output only. Pipeline creation time.
"displayName": "A String", # The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
"kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
},
"endTime": "A String", # Output only. Pipeline end time.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"jobDetail": { # The runtime detail of PipelineJob. # Output only. The details of pipeline run. Not available in the list view.
"pipelineContext": { # Instance of a general context. # Output only. The context of the pipeline.
"createTime": "A String", # Output only. Timestamp when this Context was created.
"description": "A String", # Description of the Context
"displayName": "A String", # User provided display name of the Context. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Contexts. 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. No more than 64 user labels can be associated with one Context (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Immutable. The resource name of the Context.
"parentContexts": [ # Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
"A String",
],
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"updateTime": "A String", # Output only. Timestamp when this Context was last updated.
},
"pipelineRunContext": { # Instance of a general context. # Output only. The context of the current pipeline run.
"createTime": "A String", # Output only. Timestamp when this Context was created.
"description": "A String", # Description of the Context
"displayName": "A String", # User provided display name of the Context. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Contexts. 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. No more than 64 user labels can be associated with one Context (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Immutable. The resource name of the Context.
"parentContexts": [ # Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
"A String",
],
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"updateTime": "A String", # Output only. Timestamp when this Context was last updated.
},
"taskDetails": [ # Output only. The runtime details of the tasks under the pipeline.
{ # The runtime detail of a task execution.
"createTime": "A String", # Output only. Task create time.
"endTime": "A String", # Output only. Task end time.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"execution": { # Instance of a general execution. # Output only. The execution metadata of the task.
"createTime": "A String", # Output only. Timestamp when this Execution was created.
"description": "A String", # Description of the Execution
"displayName": "A String", # User provided display name of the Execution. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Executions. 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. No more than 64 user labels can be associated with one Execution (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Execution.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Execution was last updated.
},
"executorDetail": { # The runtime detail of a pipeline executor. # Output only. The detailed execution info.
"containerDetail": { # The detail of a container execution. It contains the job names of the lifecycle of a container execution. # Output only. The detailed info for a container executor.
"failedMainJobs": [ # Output only. The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order.
"A String",
],
"failedPreCachingCheckJobs": [ # Output only. The names of the previously failed CustomJob for the pre-caching-check container executions. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events. The list includes the all attempts in chronological order.
"A String",
],
"mainJob": "A String", # Output only. The name of the CustomJob for the main container execution.
"preCachingCheckJob": "A String", # Output only. The name of the CustomJob for the pre-caching-check container execution. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events.
},
"customJobDetail": { # The detailed info for a custom job executor. # Output only. The detailed info for a custom job executor.
"failedJobs": [ # Output only. The names of the previously failed CustomJob. The list includes the all attempts in chronological order.
"A String",
],
"job": "A String", # Output only. The name of the CustomJob.
},
},
"inputs": { # Output only. The runtime input artifacts of the task.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Output only. A list of artifact metadata.
{ # Instance of a general artifact.
"createTime": "A String", # Output only. Timestamp when this Artifact was created.
"description": "A String", # Description of the Artifact
"displayName": "A String", # User provided display name of the Artifact. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Artifacts. 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. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Artifact.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Artifact was last updated.
"uri": "A String", # The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
},
],
},
},
"outputs": { # Output only. The runtime output artifacts of the task.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Output only. A list of artifact metadata.
{ # Instance of a general artifact.
"createTime": "A String", # Output only. Timestamp when this Artifact was created.
"description": "A String", # Description of the Artifact
"displayName": "A String", # User provided display name of the Artifact. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Artifacts. 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. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Artifact.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Artifact was last updated.
"uri": "A String", # The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
},
],
},
},
"parentTaskId": "A String", # Output only. The id of the parent task if the task is within a component scope. Empty if the task is at the root level.
"pipelineTaskStatus": [ # Output only. A list of task status. This field keeps a record of task status evolving over time.
{ # A single record of the task status.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during the state. May be set when the state is any of the non-final state (PENDING/RUNNING/CANCELLING) or FAILED state. If the state is FAILED, the error here is final and not going to be retried. If the state is a non-final state, the error indicates a system-error being retried.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"state": "A String", # Output only. The state of the task.
"updateTime": "A String", # Output only. Update time of this status.
},
],
"startTime": "A String", # Output only. Task start time.
"state": "A String", # Output only. State of the task.
"taskId": "A String", # Output only. The system generated ID of the task.
"taskName": "A String", # Output only. The user specified name of the task that is defined in pipeline_spec.
},
],
},
"labels": { # The labels with user-defined metadata to organize PipelineJob. 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. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.
"a_key": "A String",
},
"name": "A String", # Output only. The resource name of the PipelineJob.
"network": "A String", # The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.
"originalPipelineJobId": "A String", # Optional. The original pipeline job id if this pipeline job is a rerun of a previous pipeline job.
"pipelineSpec": { # The spec of the pipeline.
"a_key": "", # Properties of the object.
},
"pipelineTaskRerunConfigs": [ # Optional. The rerun configs for each task in the pipeline job. By default, the rerun will: 1. Use the same input artifacts as the original run. 2. Use the same input parameters as the original run. 3. Skip all the tasks that are already succeeded in the original run. 4. Rerun all the tasks that are not succeeded in the original run. By providing this field, users can override the default behavior and specify the rerun config for each task.
{ # User provided rerun config to submit a rerun pipelinejob. This includes 1. Which task to rerun 2. User override input parameters and artifacts.
"inputs": { # Runtime inputs data of the task. # Optional. The runtime input of the task overridden by the user.
"artifacts": { # Optional. Input artifacts.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Optional. A list of artifact metadata.
{ # The definition of a runtime artifact.
"customProperties": { # The custom properties of the artifact. Deprecated. Use RuntimeArtifact.metadata instead.
"a_key": { # Value is the value of the field.
"doubleValue": 3.14, # A double value.
"intValue": "A String", # An integer value.
"stringValue": "A String", # A string value.
},
},
"metadata": { # Properties of the Artifact.
"a_key": "", # Properties of the object.
},
"name": "A String", # The name of an artifact.
"properties": { # The properties of the artifact. Deprecated. Use RuntimeArtifact.metadata instead.
"a_key": { # Value is the value of the field.
"doubleValue": 3.14, # A double value.
"intValue": "A String", # An integer value.
"stringValue": "A String", # A string value.
},
},
"type": { # The definition of a artifact type in MLMD. # The type of the artifact.
"instanceSchema": "A String", # Contains a raw YAML string, describing the format of the properties of the type.
"schemaTitle": "A String", # The name of the type. The format of the title must be: `.`. Examples: - `aiplatform.Model` - `acme.CustomModel` When this field is set, the type must be pre-registered in the MLMD store.
"schemaUri": "A String", # Points to a YAML file stored on Cloud Storage describing the format. Deprecated. Use PipelineArtifactTypeSchema.schema_title or PipelineArtifactTypeSchema.instance_schema instead.
"schemaVersion": "A String", # The schema version of the artifact. If the value is not set, it defaults to the latest version in the system.
},
"uri": "A String", # The URI of the artifact.
},
],
},
},
"parameterValues": { # Optional. Input parameters.
"a_key": "",
},
},
"skipDownstreamTasks": True or False, # Optional. Whether to skip downstream tasks. Default value is False.
"skipTask": True or False, # Optional. Whether to skip this task. Default value is False.
"taskId": "A String", # Optional. The system generated ID of the task. Retrieved from original run.
"taskName": "A String", # Optional. The name of the task.
},
],
"preflightValidations": True or False, # Optional. Whether to do component level validations before job creation.
"pscInterfaceConfig": { # Configuration for PSC-I. # Optional. Configuration for PSC-I for PipelineJob.
"networkAttachment": "A String", # Optional. The name of the Compute Engine [network attachment](https://cloud.google.com/vpc/docs/about-network-attachments) to attach to the resource within the region and user project. To specify this field, you must have already [created a network attachment] (https://cloud.google.com/vpc/docs/create-manage-network-attachments#create-network-attachments). This field is only used for resources using PSC-I.
},
"reservedIpRanges": [ # A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
"A String",
],
"runtimeConfig": { # The runtime config of a PipelineJob. # Runtime config of the pipeline.
"defaultRuntime": { # The default runtime for the PipelineJob. # Optional. The default runtime for the PipelineJob. If not provided, Vertex Custom Job(on demand) is used as the runtime. For Vertex Custom Job, please refer to https://cloud.google.com/vertex-ai/docs/training/overview.
"persistentResourceRuntimeDetail": { # Persistent resource based runtime detail. For more information, refer to https://cloud.google.com/vertex-ai/docs/training/persistent-resource-overview # Persistent resource based runtime detail.
"persistentResourceName": "A String", # Persistent resource name. Format: `projects/{project}/locations/{location}/persistentResources/{persistent_resource}`
"taskResourceUnavailableTimeoutBehavior": "A String", # Specifies the behavior to take if the timeout is reached.
"taskResourceUnavailableWaitTimeMs": "A String", # The max time a pipeline task waits for the required CPU, memory, or accelerator resource to become available from the specified persistent resource. Default wait time is 0.
},
},
"failurePolicy": "A String", # Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.
"gcsOutputDirectory": "A String", # Required. A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.
"inputArtifacts": { # The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
"a_key": { # The type of an input artifact.
"artifactId": "A String", # Artifact resource id from MLMD. Which is the last portion of an artifact resource name: `projects/{project}/locations/{location}/metadataStores/default/artifacts/{artifact_id}`. The artifact must stay within the same project, location and default metadatastore as the pipeline.
},
},
"parameterValues": { # The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL.
"a_key": "",
},
"parameters": { # Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.
"a_key": { # Value is the value of the field.
"doubleValue": 3.14, # A double value.
"intValue": "A String", # An integer value.
"stringValue": "A String", # A string value.
},
},
},
"satisfiesPzi": True or False, # Output only. Reserved for future use.
"satisfiesPzs": True or False, # Output only. Reserved for future use.
"scheduleName": "A String", # Output only. The schedule resource name. Only returned if the Pipeline is created by Schedule API.
"serviceAccount": "A String", # The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.
"startTime": "A String", # Output only. Pipeline start time.
"state": "A String", # Output only. The detailed state of the job.
"templateMetadata": { # Pipeline template metadata if PipelineJob.template_uri is from supported template registry. Currently, the only supported registry is Artifact Registry. # Output only. Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.
"version": "A String", # The version_name in artifact registry. Will always be presented in output if the PipelineJob.template_uri is from supported template registry. Format is "sha256:abcdef123456...".
},
"templateUri": "A String", # A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.
"updateTime": "A String", # Output only. Timestamp when this PipelineJob was most recently updated.
}
delete(name, x__xgafv=None)
Deletes a PipelineJob.
Args:
name: string, Required. The name of the PipelineJob resource to be deleted. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}` (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
"response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}
get(name, x__xgafv=None)
Gets a PipelineJob.
Args:
name: string, Required. The name of the PipelineJob resource. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}` (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # An instance of a machine learning PipelineJob.
"createTime": "A String", # Output only. Pipeline creation time.
"displayName": "A String", # The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
"kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
},
"endTime": "A String", # Output only. Pipeline end time.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"jobDetail": { # The runtime detail of PipelineJob. # Output only. The details of pipeline run. Not available in the list view.
"pipelineContext": { # Instance of a general context. # Output only. The context of the pipeline.
"createTime": "A String", # Output only. Timestamp when this Context was created.
"description": "A String", # Description of the Context
"displayName": "A String", # User provided display name of the Context. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Contexts. 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. No more than 64 user labels can be associated with one Context (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Immutable. The resource name of the Context.
"parentContexts": [ # Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
"A String",
],
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"updateTime": "A String", # Output only. Timestamp when this Context was last updated.
},
"pipelineRunContext": { # Instance of a general context. # Output only. The context of the current pipeline run.
"createTime": "A String", # Output only. Timestamp when this Context was created.
"description": "A String", # Description of the Context
"displayName": "A String", # User provided display name of the Context. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Contexts. 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. No more than 64 user labels can be associated with one Context (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Immutable. The resource name of the Context.
"parentContexts": [ # Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
"A String",
],
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"updateTime": "A String", # Output only. Timestamp when this Context was last updated.
},
"taskDetails": [ # Output only. The runtime details of the tasks under the pipeline.
{ # The runtime detail of a task execution.
"createTime": "A String", # Output only. Task create time.
"endTime": "A String", # Output only. Task end time.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"execution": { # Instance of a general execution. # Output only. The execution metadata of the task.
"createTime": "A String", # Output only. Timestamp when this Execution was created.
"description": "A String", # Description of the Execution
"displayName": "A String", # User provided display name of the Execution. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Executions. 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. No more than 64 user labels can be associated with one Execution (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Execution.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Execution was last updated.
},
"executorDetail": { # The runtime detail of a pipeline executor. # Output only. The detailed execution info.
"containerDetail": { # The detail of a container execution. It contains the job names of the lifecycle of a container execution. # Output only. The detailed info for a container executor.
"failedMainJobs": [ # Output only. The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order.
"A String",
],
"failedPreCachingCheckJobs": [ # Output only. The names of the previously failed CustomJob for the pre-caching-check container executions. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events. The list includes the all attempts in chronological order.
"A String",
],
"mainJob": "A String", # Output only. The name of the CustomJob for the main container execution.
"preCachingCheckJob": "A String", # Output only. The name of the CustomJob for the pre-caching-check container execution. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events.
},
"customJobDetail": { # The detailed info for a custom job executor. # Output only. The detailed info for a custom job executor.
"failedJobs": [ # Output only. The names of the previously failed CustomJob. The list includes the all attempts in chronological order.
"A String",
],
"job": "A String", # Output only. The name of the CustomJob.
},
},
"inputs": { # Output only. The runtime input artifacts of the task.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Output only. A list of artifact metadata.
{ # Instance of a general artifact.
"createTime": "A String", # Output only. Timestamp when this Artifact was created.
"description": "A String", # Description of the Artifact
"displayName": "A String", # User provided display name of the Artifact. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Artifacts. 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. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Artifact.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Artifact was last updated.
"uri": "A String", # The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
},
],
},
},
"outputs": { # Output only. The runtime output artifacts of the task.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Output only. A list of artifact metadata.
{ # Instance of a general artifact.
"createTime": "A String", # Output only. Timestamp when this Artifact was created.
"description": "A String", # Description of the Artifact
"displayName": "A String", # User provided display name of the Artifact. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Artifacts. 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. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Artifact.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Artifact was last updated.
"uri": "A String", # The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
},
],
},
},
"parentTaskId": "A String", # Output only. The id of the parent task if the task is within a component scope. Empty if the task is at the root level.
"pipelineTaskStatus": [ # Output only. A list of task status. This field keeps a record of task status evolving over time.
{ # A single record of the task status.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during the state. May be set when the state is any of the non-final state (PENDING/RUNNING/CANCELLING) or FAILED state. If the state is FAILED, the error here is final and not going to be retried. If the state is a non-final state, the error indicates a system-error being retried.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"state": "A String", # Output only. The state of the task.
"updateTime": "A String", # Output only. Update time of this status.
},
],
"startTime": "A String", # Output only. Task start time.
"state": "A String", # Output only. State of the task.
"taskId": "A String", # Output only. The system generated ID of the task.
"taskName": "A String", # Output only. The user specified name of the task that is defined in pipeline_spec.
},
],
},
"labels": { # The labels with user-defined metadata to organize PipelineJob. 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. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.
"a_key": "A String",
},
"name": "A String", # Output only. The resource name of the PipelineJob.
"network": "A String", # The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.
"originalPipelineJobId": "A String", # Optional. The original pipeline job id if this pipeline job is a rerun of a previous pipeline job.
"pipelineSpec": { # The spec of the pipeline.
"a_key": "", # Properties of the object.
},
"pipelineTaskRerunConfigs": [ # Optional. The rerun configs for each task in the pipeline job. By default, the rerun will: 1. Use the same input artifacts as the original run. 2. Use the same input parameters as the original run. 3. Skip all the tasks that are already succeeded in the original run. 4. Rerun all the tasks that are not succeeded in the original run. By providing this field, users can override the default behavior and specify the rerun config for each task.
{ # User provided rerun config to submit a rerun pipelinejob. This includes 1. Which task to rerun 2. User override input parameters and artifacts.
"inputs": { # Runtime inputs data of the task. # Optional. The runtime input of the task overridden by the user.
"artifacts": { # Optional. Input artifacts.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Optional. A list of artifact metadata.
{ # The definition of a runtime artifact.
"customProperties": { # The custom properties of the artifact. Deprecated. Use RuntimeArtifact.metadata instead.
"a_key": { # Value is the value of the field.
"doubleValue": 3.14, # A double value.
"intValue": "A String", # An integer value.
"stringValue": "A String", # A string value.
},
},
"metadata": { # Properties of the Artifact.
"a_key": "", # Properties of the object.
},
"name": "A String", # The name of an artifact.
"properties": { # The properties of the artifact. Deprecated. Use RuntimeArtifact.metadata instead.
"a_key": { # Value is the value of the field.
"doubleValue": 3.14, # A double value.
"intValue": "A String", # An integer value.
"stringValue": "A String", # A string value.
},
},
"type": { # The definition of a artifact type in MLMD. # The type of the artifact.
"instanceSchema": "A String", # Contains a raw YAML string, describing the format of the properties of the type.
"schemaTitle": "A String", # The name of the type. The format of the title must be: `.`. Examples: - `aiplatform.Model` - `acme.CustomModel` When this field is set, the type must be pre-registered in the MLMD store.
"schemaUri": "A String", # Points to a YAML file stored on Cloud Storage describing the format. Deprecated. Use PipelineArtifactTypeSchema.schema_title or PipelineArtifactTypeSchema.instance_schema instead.
"schemaVersion": "A String", # The schema version of the artifact. If the value is not set, it defaults to the latest version in the system.
},
"uri": "A String", # The URI of the artifact.
},
],
},
},
"parameterValues": { # Optional. Input parameters.
"a_key": "",
},
},
"skipDownstreamTasks": True or False, # Optional. Whether to skip downstream tasks. Default value is False.
"skipTask": True or False, # Optional. Whether to skip this task. Default value is False.
"taskId": "A String", # Optional. The system generated ID of the task. Retrieved from original run.
"taskName": "A String", # Optional. The name of the task.
},
],
"preflightValidations": True or False, # Optional. Whether to do component level validations before job creation.
"pscInterfaceConfig": { # Configuration for PSC-I. # Optional. Configuration for PSC-I for PipelineJob.
"networkAttachment": "A String", # Optional. The name of the Compute Engine [network attachment](https://cloud.google.com/vpc/docs/about-network-attachments) to attach to the resource within the region and user project. To specify this field, you must have already [created a network attachment] (https://cloud.google.com/vpc/docs/create-manage-network-attachments#create-network-attachments). This field is only used for resources using PSC-I.
},
"reservedIpRanges": [ # A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
"A String",
],
"runtimeConfig": { # The runtime config of a PipelineJob. # Runtime config of the pipeline.
"defaultRuntime": { # The default runtime for the PipelineJob. # Optional. The default runtime for the PipelineJob. If not provided, Vertex Custom Job(on demand) is used as the runtime. For Vertex Custom Job, please refer to https://cloud.google.com/vertex-ai/docs/training/overview.
"persistentResourceRuntimeDetail": { # Persistent resource based runtime detail. For more information, refer to https://cloud.google.com/vertex-ai/docs/training/persistent-resource-overview # Persistent resource based runtime detail.
"persistentResourceName": "A String", # Persistent resource name. Format: `projects/{project}/locations/{location}/persistentResources/{persistent_resource}`
"taskResourceUnavailableTimeoutBehavior": "A String", # Specifies the behavior to take if the timeout is reached.
"taskResourceUnavailableWaitTimeMs": "A String", # The max time a pipeline task waits for the required CPU, memory, or accelerator resource to become available from the specified persistent resource. Default wait time is 0.
},
},
"failurePolicy": "A String", # Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.
"gcsOutputDirectory": "A String", # Required. A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.
"inputArtifacts": { # The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
"a_key": { # The type of an input artifact.
"artifactId": "A String", # Artifact resource id from MLMD. Which is the last portion of an artifact resource name: `projects/{project}/locations/{location}/metadataStores/default/artifacts/{artifact_id}`. The artifact must stay within the same project, location and default metadatastore as the pipeline.
},
},
"parameterValues": { # The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL.
"a_key": "",
},
"parameters": { # Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.
"a_key": { # Value is the value of the field.
"doubleValue": 3.14, # A double value.
"intValue": "A String", # An integer value.
"stringValue": "A String", # A string value.
},
},
},
"satisfiesPzi": True or False, # Output only. Reserved for future use.
"satisfiesPzs": True or False, # Output only. Reserved for future use.
"scheduleName": "A String", # Output only. The schedule resource name. Only returned if the Pipeline is created by Schedule API.
"serviceAccount": "A String", # The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.
"startTime": "A String", # Output only. Pipeline start time.
"state": "A String", # Output only. The detailed state of the job.
"templateMetadata": { # Pipeline template metadata if PipelineJob.template_uri is from supported template registry. Currently, the only supported registry is Artifact Registry. # Output only. Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.
"version": "A String", # The version_name in artifact registry. Will always be presented in output if the PipelineJob.template_uri is from supported template registry. Format is "sha256:abcdef123456...".
},
"templateUri": "A String", # A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.
"updateTime": "A String", # Output only. Timestamp when this PipelineJob was most recently updated.
}
list(parent, filter=None, orderBy=None, pageSize=None, pageToken=None, readMask=None, x__xgafv=None)
Lists PipelineJobs in a Location.
Args:
parent: string, Required. The resource name of the Location to list the PipelineJobs from. Format: `projects/{project}/locations/{location}` (required)
filter: string, Lists the PipelineJobs that match the filter expression. The following fields are supported: * `pipeline_name`: Supports `=` and `!=` comparisons. * `display_name`: Supports `=`, `!=` comparisons, and `:` wildcard. * `pipeline_job_user_id`: Supports `=`, `!=` comparisons, and `:` wildcard. for example, can check if pipeline's display_name contains *step* by doing display_name:\"*step*\" * `state`: Supports `=` and `!=` comparisons. * `create_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be in RFC 3339 format. * `end_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality and key presence. * `template_uri`: Supports `=`, `!=` comparisons, and `:` wildcard. * `template_metadata.version`: Supports `=`, `!=` comparisons, and `:` wildcard. Filter expressions can be combined together using logical operators (`AND` & `OR`). For example: `pipeline_name="test" AND create_time>"2020-05-18T13:30:00Z"`. The syntax to define filter expression is based on https://google.aip.dev/160. Examples: * `create_time>"2021-05-18T00:00:00Z" OR update_time>"2020-05-18T00:00:00Z"` PipelineJobs created or updated after 2020-05-18 00:00:00 UTC. * `labels.env = "prod"` PipelineJobs with label "env" set to "prod".
orderBy: string, A comma-separated list of fields to order by. The default sort order is in ascending order. Use "desc" after a field name for descending. You can have multiple order_by fields provided e.g. "create_time desc, end_time", "end_time, start_time, update_time" For example, using "create_time desc, end_time" will order results by create time in descending order, and if there are multiple jobs having the same create time, order them by the end time in ascending order. if order_by is not specified, it will order by default order is create time in descending order. Supported fields: * `create_time` * `update_time` * `end_time` * `start_time`
pageSize: integer, The standard list page size.
pageToken: string, The standard list page token. Typically obtained via ListPipelineJobsResponse.next_page_token of the previous PipelineService.ListPipelineJobs call.
readMask: string, Mask specifying which fields to read.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # Response message for PipelineService.ListPipelineJobs
"nextPageToken": "A String", # A token to retrieve the next page of results. Pass to ListPipelineJobsRequest.page_token to obtain that page.
"pipelineJobs": [ # List of PipelineJobs in the requested page.
{ # An instance of a machine learning PipelineJob.
"createTime": "A String", # Output only. Pipeline creation time.
"displayName": "A String", # The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
"encryptionSpec": { # Represents a customer-managed encryption key spec that can be applied to a top-level resource. # Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
"kmsKeyName": "A String", # Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
},
"endTime": "A String", # Output only. Pipeline end time.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"jobDetail": { # The runtime detail of PipelineJob. # Output only. The details of pipeline run. Not available in the list view.
"pipelineContext": { # Instance of a general context. # Output only. The context of the pipeline.
"createTime": "A String", # Output only. Timestamp when this Context was created.
"description": "A String", # Description of the Context
"displayName": "A String", # User provided display name of the Context. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Contexts. 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. No more than 64 user labels can be associated with one Context (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Immutable. The resource name of the Context.
"parentContexts": [ # Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
"A String",
],
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"updateTime": "A String", # Output only. Timestamp when this Context was last updated.
},
"pipelineRunContext": { # Instance of a general context. # Output only. The context of the current pipeline run.
"createTime": "A String", # Output only. Timestamp when this Context was created.
"description": "A String", # Description of the Context
"displayName": "A String", # User provided display name of the Context. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Contexts. 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. No more than 64 user labels can be associated with one Context (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Immutable. The resource name of the Context.
"parentContexts": [ # Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
"A String",
],
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"updateTime": "A String", # Output only. Timestamp when this Context was last updated.
},
"taskDetails": [ # Output only. The runtime details of the tasks under the pipeline.
{ # The runtime detail of a task execution.
"createTime": "A String", # Output only. Task create time.
"endTime": "A String", # Output only. Task end time.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"execution": { # Instance of a general execution. # Output only. The execution metadata of the task.
"createTime": "A String", # Output only. Timestamp when this Execution was created.
"description": "A String", # Description of the Execution
"displayName": "A String", # User provided display name of the Execution. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Executions. 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. No more than 64 user labels can be associated with one Execution (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Execution.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Execution was last updated.
},
"executorDetail": { # The runtime detail of a pipeline executor. # Output only. The detailed execution info.
"containerDetail": { # The detail of a container execution. It contains the job names of the lifecycle of a container execution. # Output only. The detailed info for a container executor.
"failedMainJobs": [ # Output only. The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order.
"A String",
],
"failedPreCachingCheckJobs": [ # Output only. The names of the previously failed CustomJob for the pre-caching-check container executions. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events. The list includes the all attempts in chronological order.
"A String",
],
"mainJob": "A String", # Output only. The name of the CustomJob for the main container execution.
"preCachingCheckJob": "A String", # Output only. The name of the CustomJob for the pre-caching-check container execution. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events.
},
"customJobDetail": { # The detailed info for a custom job executor. # Output only. The detailed info for a custom job executor.
"failedJobs": [ # Output only. The names of the previously failed CustomJob. The list includes the all attempts in chronological order.
"A String",
],
"job": "A String", # Output only. The name of the CustomJob.
},
},
"inputs": { # Output only. The runtime input artifacts of the task.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Output only. A list of artifact metadata.
{ # Instance of a general artifact.
"createTime": "A String", # Output only. Timestamp when this Artifact was created.
"description": "A String", # Description of the Artifact
"displayName": "A String", # User provided display name of the Artifact. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Artifacts. 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. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Artifact.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Artifact was last updated.
"uri": "A String", # The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
},
],
},
},
"outputs": { # Output only. The runtime output artifacts of the task.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Output only. A list of artifact metadata.
{ # Instance of a general artifact.
"createTime": "A String", # Output only. Timestamp when this Artifact was created.
"description": "A String", # Description of the Artifact
"displayName": "A String", # User provided display name of the Artifact. May be up to 128 Unicode characters.
"etag": "A String", # An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
"labels": { # The labels with user-defined metadata to organize your Artifacts. 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. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
"a_key": "A String",
},
"metadata": { # Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
"a_key": "", # Properties of the object.
},
"name": "A String", # Output only. The resource name of the Artifact.
"schemaTitle": "A String", # The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"schemaVersion": "A String", # The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
"state": "A String", # The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
"updateTime": "A String", # Output only. Timestamp when this Artifact was last updated.
"uri": "A String", # The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
},
],
},
},
"parentTaskId": "A String", # Output only. The id of the parent task if the task is within a component scope. Empty if the task is at the root level.
"pipelineTaskStatus": [ # Output only. A list of task status. This field keeps a record of task status evolving over time.
{ # A single record of the task status.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. The error that occurred during the state. May be set when the state is any of the non-final state (PENDING/RUNNING/CANCELLING) or FAILED state. If the state is FAILED, the error here is final and not going to be retried. If the state is a non-final state, the error indicates a system-error being retried.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"state": "A String", # Output only. The state of the task.
"updateTime": "A String", # Output only. Update time of this status.
},
],
"startTime": "A String", # Output only. Task start time.
"state": "A String", # Output only. State of the task.
"taskId": "A String", # Output only. The system generated ID of the task.
"taskName": "A String", # Output only. The user specified name of the task that is defined in pipeline_spec.
},
],
},
"labels": { # The labels with user-defined metadata to organize PipelineJob. 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. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.
"a_key": "A String",
},
"name": "A String", # Output only. The resource name of the PipelineJob.
"network": "A String", # The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.
"originalPipelineJobId": "A String", # Optional. The original pipeline job id if this pipeline job is a rerun of a previous pipeline job.
"pipelineSpec": { # The spec of the pipeline.
"a_key": "", # Properties of the object.
},
"pipelineTaskRerunConfigs": [ # Optional. The rerun configs for each task in the pipeline job. By default, the rerun will: 1. Use the same input artifacts as the original run. 2. Use the same input parameters as the original run. 3. Skip all the tasks that are already succeeded in the original run. 4. Rerun all the tasks that are not succeeded in the original run. By providing this field, users can override the default behavior and specify the rerun config for each task.
{ # User provided rerun config to submit a rerun pipelinejob. This includes 1. Which task to rerun 2. User override input parameters and artifacts.
"inputs": { # Runtime inputs data of the task. # Optional. The runtime input of the task overridden by the user.
"artifacts": { # Optional. Input artifacts.
"a_key": { # A list of artifact metadata.
"artifacts": [ # Optional. A list of artifact metadata.
{ # The definition of a runtime artifact.
"customProperties": { # The custom properties of the artifact. Deprecated. Use RuntimeArtifact.metadata instead.
"a_key": { # Value is the value of the field.
"doubleValue": 3.14, # A double value.
"intValue": "A String", # An integer value.
"stringValue": "A String", # A string value.
},
},
"metadata": { # Properties of the Artifact.
"a_key": "", # Properties of the object.
},
"name": "A String", # The name of an artifact.
"properties": { # The properties of the artifact. Deprecated. Use RuntimeArtifact.metadata instead.
"a_key": { # Value is the value of the field.
"doubleValue": 3.14, # A double value.
"intValue": "A String", # An integer value.
"stringValue": "A String", # A string value.
},
},
"type": { # The definition of a artifact type in MLMD. # The type of the artifact.
"instanceSchema": "A String", # Contains a raw YAML string, describing the format of the properties of the type.
"schemaTitle": "A String", # The name of the type. The format of the title must be: `.`. Examples: - `aiplatform.Model` - `acme.CustomModel` When this field is set, the type must be pre-registered in the MLMD store.
"schemaUri": "A String", # Points to a YAML file stored on Cloud Storage describing the format. Deprecated. Use PipelineArtifactTypeSchema.schema_title or PipelineArtifactTypeSchema.instance_schema instead.
"schemaVersion": "A String", # The schema version of the artifact. If the value is not set, it defaults to the latest version in the system.
},
"uri": "A String", # The URI of the artifact.
},
],
},
},
"parameterValues": { # Optional. Input parameters.
"a_key": "",
},
},
"skipDownstreamTasks": True or False, # Optional. Whether to skip downstream tasks. Default value is False.
"skipTask": True or False, # Optional. Whether to skip this task. Default value is False.
"taskId": "A String", # Optional. The system generated ID of the task. Retrieved from original run.
"taskName": "A String", # Optional. The name of the task.
},
],
"preflightValidations": True or False, # Optional. Whether to do component level validations before job creation.
"pscInterfaceConfig": { # Configuration for PSC-I. # Optional. Configuration for PSC-I for PipelineJob.
"networkAttachment": "A String", # Optional. The name of the Compute Engine [network attachment](https://cloud.google.com/vpc/docs/about-network-attachments) to attach to the resource within the region and user project. To specify this field, you must have already [created a network attachment] (https://cloud.google.com/vpc/docs/create-manage-network-attachments#create-network-attachments). This field is only used for resources using PSC-I.
},
"reservedIpRanges": [ # A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
"A String",
],
"runtimeConfig": { # The runtime config of a PipelineJob. # Runtime config of the pipeline.
"defaultRuntime": { # The default runtime for the PipelineJob. # Optional. The default runtime for the PipelineJob. If not provided, Vertex Custom Job(on demand) is used as the runtime. For Vertex Custom Job, please refer to https://cloud.google.com/vertex-ai/docs/training/overview.
"persistentResourceRuntimeDetail": { # Persistent resource based runtime detail. For more information, refer to https://cloud.google.com/vertex-ai/docs/training/persistent-resource-overview # Persistent resource based runtime detail.
"persistentResourceName": "A String", # Persistent resource name. Format: `projects/{project}/locations/{location}/persistentResources/{persistent_resource}`
"taskResourceUnavailableTimeoutBehavior": "A String", # Specifies the behavior to take if the timeout is reached.
"taskResourceUnavailableWaitTimeMs": "A String", # The max time a pipeline task waits for the required CPU, memory, or accelerator resource to become available from the specified persistent resource. Default wait time is 0.
},
},
"failurePolicy": "A String", # Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.
"gcsOutputDirectory": "A String", # Required. A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.
"inputArtifacts": { # The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
"a_key": { # The type of an input artifact.
"artifactId": "A String", # Artifact resource id from MLMD. Which is the last portion of an artifact resource name: `projects/{project}/locations/{location}/metadataStores/default/artifacts/{artifact_id}`. The artifact must stay within the same project, location and default metadatastore as the pipeline.
},
},
"parameterValues": { # The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL.
"a_key": "",
},
"parameters": { # Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.
"a_key": { # Value is the value of the field.
"doubleValue": 3.14, # A double value.
"intValue": "A String", # An integer value.
"stringValue": "A String", # A string value.
},
},
},
"satisfiesPzi": True or False, # Output only. Reserved for future use.
"satisfiesPzs": True or False, # Output only. Reserved for future use.
"scheduleName": "A String", # Output only. The schedule resource name. Only returned if the Pipeline is created by Schedule API.
"serviceAccount": "A String", # The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.
"startTime": "A String", # Output only. Pipeline start time.
"state": "A String", # Output only. The detailed state of the job.
"templateMetadata": { # Pipeline template metadata if PipelineJob.template_uri is from supported template registry. Currently, the only supported registry is Artifact Registry. # Output only. Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.
"version": "A String", # The version_name in artifact registry. Will always be presented in output if the PipelineJob.template_uri is from supported template registry. Format is "sha256:abcdef123456...".
},
"templateUri": "A String", # A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.
"updateTime": "A String", # Output only. Timestamp when this PipelineJob was most recently updated.
},
],
}
list_next()
Retrieves the next page of results.
Args:
previous_request: The request for the previous page. (required)
previous_response: The response from the request for the previous page. (required)
Returns:
A request object that you can call 'execute()' on to request the next
page. Returns None if there are no more items in the collection.