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Creating a Training Job

Updated on 2025-03-14 GMT+08:00

Function

This API is used to create a training job.

Debugging

You can debug this API through automatic authentication in API Explorer or use the SDK sample code generated by API Explorer.

URI

POST /v2/{project_id}/training-jobs

Table 1 Path Parameters

Parameter

Mandatory

Type

Description

project_id

Yes

String

Project ID. For details, see Obtaining a Project ID and Name.

Request Parameters

Table 2 Request body parameters

Parameter

Mandatory

Type

Description

kind

Yes

String

Training job type. The default value is job, indicating a training job.

visualization_job: visualization job

metadata

Yes

JobMetadata object

Metadata of a training job.

algorithm

No

JobAlgorithm object

Algorithm used by a training job. The options are as follows:

  • id: Only the algorithm ID is used.

  • subscription_id+item_version_id: The subscription ID and version ID of the algorithm are used.

  • code_dir+boot_file: The code directory and boot file of the training job are used.

tasks

No

Array of Task objects

Task list. This function is not implemented currently.

spec

No

Spec object

Specifications of a training job. If this parameter is specified, leave the tasks parameter blank.

endpoints

No

JobEndpointsReq object

This section describes the configurations required for remotely accessing a training job.

Table 3 JobMetadata

Parameter

Mandatory

Type

Description

name

Yes

String

Name of a training job. The value must contain 1 to 64 characters consisting of only digits, letters, underscores (_), and hyphens (-).

workspace_id

No

String

Workspace where a job is located. The default value is 0.

description

No

String

Training job description. The value must contain 0 to 256 characters. The default value is NULL.

annotations

No

Map<String,String>

Advanced configurations of a training job. The options are as follows:

  • job_template: Template RL (heterogeneous job)

  • fault-tolerance/job-retry-num: 3 (number of retries upon a fault)

  • fault-tolerance/job-unconditional-retry: true (unconditional restart)

  • fault-tolerance/hang-retry: true (restart upon a suspension)

  • jupyter-lab/enable: true (JupyterLab training application)

  • tensorboard/enable: true (TensorBoard training application)

  • mindstudio-insight/enable: true (MindStudio Insight training application)

Table 4 JobAlgorithm

Parameter

Mandatory

Type

Description

id

No

String

Algorithm ID.

name

No

String

Algorithm name. Leave it blank.

subscription_id

No

String

Subscription ID of a subscribed algorithm, which must be used with item_version_id

item_version_id

No

String

Version ID of the subscribed algorithm, which must be used with subscription_id

code_dir

No

String

Code directory of a training job, for example, /usr/app/. This parameter must appear together with boot_file. If boot_file is set to id or subscription_id+item_version_id, you do not need to set this parameter.

boot_file

No

String

Boot file of a training job, which needs to be stored in the code directory, for example, /usr/app/boot.py. This parameter must be used together with code_dir. If code_dir is set to id or subscription_id+item_version_id, you do not need to set this parameter.

autosearch_config_path

No

String

YAML configuration path of auto search jobs. An OBS URL is required.

autosearch_framework_path

No

String

Framework code directory of auto search jobs. An OBS URL is required.

command

No

String

Command for starting the container of the custom image of a training job in the custom image scenario.

parameters

No

Array of Parameters objects

Running parameters of a training job.

policies

No

JobPolicies object

Policies supported by jobs, which are used for hyperparameter search.

inputs

No

Array of Input objects

Input of a training job.

outputs

No

Array of Output objects

Output of a training job.

engine

No

JobEngine object

Engine of a training job. Leave this parameter blank if the job is created using id of the algorithm in algorithm management, or subscription_id+item_version_id of the subscribed algorithm.

local_code_dir

No

String

Local directory to the training container to which the algorithm code directory is downloaded Rules:

  • The value must be a directory in /home.

  • In v1 compatibility mode, the current field does not take effect.

  • When code_dir is prefixed with file://, the current field does not take effect.

working_dir

No

String

Work directory where an algorithm is executed. Note that this parameter does not take effect in v1 compatibility mode.

environments

No

Map<String,String>

Environment variables of a training job, in the format of "key":"value". The key can contain a maximum of 8192 characters, and the value can contain a maximum of 4096 characters. A maximum of 100 key-value pairs are allowed. The variable name can contain only letters, digits, and underscores (), and must start with a letter or underscore ().

summary

No

Summary object

Visualization log summary.

Table 5 Parameters

Parameter

Mandatory

Type

Description

name

No

String

Parameter name.

value

No

String

Parameter value.

description

No

String

Parameter description.

constraint

No

ParametersConstraint object

Parameter constraint.

i18n_description

No

I18nDescription object

Internationalization description.

Table 6 ParametersConstraint

Parameter

Mandatory

Type

Description

type

No

String

Parameter type.

editable

No

Boolean

Whether the parameter is editable.

required

No

Boolean

Whether the parameter is mandatory.

sensitive

No

Boolean

Whether the parameter is sensitive. This function is not implemented currently.

valid_type

No

String

Valid type.

valid_range

No

Array of strings

Valid range.

Table 7 I18nDescription

Parameter

Mandatory

Type

Description

language

No

String

Internationalization language.

description

No

String

Description.

Table 8 JobPolicies

Parameter

Mandatory

Type

Description

auto_search

No

AutoSearch object

Hyperparameter search configuration.

Table 9 AutoSearch

Parameter

Mandatory

Type

Description

skip_search_params

No

String

Hyperparameter parameters that need to be skipped.

reward_attrs

No

Array of RewardAttrs objects

Search metrics.

search_params

No

Array of SearchParams objects

Search parameters.

algo_configs

No

Array of AlgoConfigs objects

Search algorithm configurations.

Table 10 RewardAttrs

Parameter

Mandatory

Type

Description

name

No

String

Metric name.

mode

No

String

Search mode. - If max is specified, the larger the metric value, the better. - If min is specified, the smaller the metric value, the better.

regex

No

String

Regular expression of a metric.

Table 11 SearchParams

Parameter

Mandatory

Type

Description

name

No

String

Hyperparameter name.

param_type

No

String

Parameter type. - continuous: The hyperparameter is of the continuous type. When an algorithm is used in a training job, continuous hyperparameters are displayed as text boxes on the console. - discrete: The hyperparameter is of the discrete type. When an algorithm is used in a training job, discrete hyperparameters are displayed as drop-down lists on the console.

lower_bound

No

String

Lower bound of the hyperparameter.

upper_bound

No

String

Upper bound of the hyperparameter.

discrete_points_num

No

String

Number of discrete points of a hyperparameter with continuous values.

discrete_values

No

Array of strings

Discrete hyperparameter values.

Table 12 AlgoConfigs

Parameter

Mandatory

Type

Description

name

No

String

Name of the search algorithm.

params

No

Array of AutoSearchAlgoConfigParameter objects

Search algorithm parameters.

Table 13 AutoSearchAlgoConfigParameter

Parameter

Mandatory

Type

Description

key

No

String

Parameter key.

value

No

String

Parameter value.

type

No

String

Parameter type.

Table 14 JobEngine

Parameter

Mandatory

Type

Description

engine_id

No

String

Engine ID selected for a training job. The value can be engine_id, engine_name + engine_version, or image_url.

engine_name

No

String

Name of the engine selected for a training job. If engine_id has been set, you do not need to set this parameter.

engine_version

No

String

Version of the engine selected for a training job. If engine_id has been set, you do not need to set this parameter.

image_url

No

String

Custom image URL selected for a training job. The URL is obtained from SWR.

install_sys_packages

No

Boolean

Whether to install the MoXing version specified by the training platform. Value true means to install the specified MoXing version. This parameter is available only when engine_name, engine_version, and image_url are set.

Table 15 Summary

Parameter

Mandatory

Type

Description

log_type

No

String

Visualization log type of a training job. After this parameter is configured, the training job can be used as the data source of a visualization job. The options are as follows:

  • tensorboard

  • mindstudio-insight

log_dir

No

LogDir object

Visualization log output of a training job. This parameter is mandatory when log_type is not empty.

data_sources

No

Array of DataSource objects

Visualization log input of a visualization job or debug training job. This parameter is mandatory when tensorboard/enable or mindstudio-insight/enable is set to true for advanced training functions.

Table 16 LogDir

Parameter

Mandatory

Type

Description

pfs

Yes

PFSSummary object

Output of an OBS parallel file system.

Table 17 PFSSummary

Parameter

Mandatory

Type

Description

pfs_path

Yes

String

URL of an OBS parallel file system.

Table 18 DataSource

Parameter

Mandatory

Type

Description

job

Yes

JobSummary object

Job data source.

Table 19 JobSummary

Parameter

Mandatory

Type

Description

job_id

Yes

String

Training job ID.

Table 20 Task

Parameter

Mandatory

Type

Description

role

No

String

Task role. This function is not supported currently.

algorithm

No

algorithm object

Algorithm management and configuration.

task_resource

No

task_resource object

Resource flavors of a training job.

Table 21 algorithm

Parameter

Mandatory

Type

Description

job_config

No

job_config object

Algorithm configuration, such as the boot file.

code_dir

No

String

Algorithm code directory, for example, /usr/app/. This parameter must be used together with boot_file.

boot_file

No

String

Code boot file of the algorithm, which needs to be stored in the code directory, for example, /usr/app/boot.py. This parameter must be used together with code_dir.

engine

No

engine object

Engine of a heterogeneous job algorithm.

inputs

No

Array of inputs objects

Data input of an algorithm.

outputs

No

Array of outputs objects

Data output of an algorithm.

local_code_dir

No

String

Local directory of the training container to which the algorithm code directory is downloaded. The rules are as follows:

  • The directory must be under /home.

  • In v1 compatibility mode, the current field does not take effect.

  • When code_dir is prefixed with file://, the current field does not take effect.

working_dir

No

String

Work directory where an algorithm is executed. Note that this parameter does not take effect in v1 compatibility mode.

Table 22 job_config

Parameter

Mandatory

Type

Description

parameters

No

Array of Parameter objects

Running parameter of an algorithm.

inputs

No

Array of Input objects

Data input of an algorithm.

outputs

No

Array of Output objects

Data output of an algorithm.

engine

No

engine object

Algorithm engine.

Table 23 Parameter

Parameter

Mandatory

Type

Description

name

No

String

Parameter name.

value

No

String

Parameter value.

description

No

String

Parameter description.

constraint

No

constraint object

Parameter constraint.

i18n_description

No

i18n_description object

Internationalization description.

Table 24 constraint

Parameter

Mandatory

Type

Description

type

No

String

Parameter type.

editable

No

Boolean

Whether the parameter is editable.

required

No

Boolean

Whether the parameter is mandatory.

sensitive

No

Boolean

Whether the parameter is sensitive This function is not implemented currently.

valid_type

No

String

Valid type.

valid_range

No

Array of strings

Valid range.

Table 25 i18n_description

Parameter

Mandatory

Type

Description

language

No

String

International language[. The options are as follows:

  • zh-cn (Chinese)

  • En-us] (tag:hc,hk)

description

No

String

Description of an international language.

Table 26 Input

Parameter

Mandatory

Type

Description

name

Yes

String

Name of the data input channel.

description

No

String

Description of the data input channel.

local_dir

No

String

Local directory of the container to which the data input channel is mapped Example: /home/ma-user/modelarts/inputs/data_url_0.

remote

Yes

InputDataInfo object

Information of the data input. Enums:

  • dataset: The data input is a dataset.

  • obs: The data input is an OBS path.

remote_constraint

No

Array of remote_constraint objects

Data input constraint

Table 27 InputDataInfo

Parameter

Mandatory

Type

Description

dataset

No

dataset object

Dataset as the data input.

obs

No

obs object

OBS in which data input and output stored.

Table 28 dataset

Parameter

Mandatory

Type

Description

id

Yes

String

Dataset ID of a training job.

version_id

Yes

String

Dataset version ID of a training job.

Table 29 obs

Parameter

Mandatory

Type

Description

obs_url

Yes

String

OBS URL of the dataset required by a training job. For example, /usr/data/.

Table 30 remote_constraint

Parameter

Mandatory

Type

Description

data_type

No

String

Data input type, including the data storage location and dataset.

attributes

No

String

Attributes if a dataset is used as the data input. Options:

  • data_format: Data format

  • data_segmentation: Data segmentation

  • dataset_type: Labeling type

Table 31 Output

Parameter

Mandatory

Type

Description

name

Yes

String

Name of the data output channel.

description

No

String

Description of the data output channel.

local_dir

No

String

Local directory of the container to which the data output channel is mapped.

remote

Yes

Remote object

Description of the actual data output.

Table 32 Remote

Parameter

Mandatory

Type

Description

obs

Yes

RemoteObs object

OBS to which data is actually exported.

Table 33 RemoteObs

Parameter

Mandatory

Type

Description

obs_url

Yes

String

OBS URL to which data is exported.

Table 34 engine

Parameter

Mandatory

Type

Description

engine_id

No

String

Engine ID selected for an algorithm.

engine_name

No

String

Engine version name selected for an algorithm. If engine_id is specified, leave this parameter blank.

engine_version

No

String

Engine version name selected for an algorithm. If engine_id is specified, leave this parameter blank.

image_url

No

String

Custom image URL selected by an algorithm.

Table 35 engine

Parameter

Mandatory

Type

Description

engine_id

No

String

Engine ID of a heterogeneous job, for example, caffe-1.0.0-python2.7.

engine_name

No

String

Engine name of a heterogeneous job, for example, Caffe.

engine_version

No

String

Engine version of a heterogeneous job.

image_url

No

String

Custom image URL selected by an algorithm.

Table 36 inputs

Parameter

Mandatory

Type

Description

name

Yes

String

Name of the data input channel.

description

No

String

Description of the data input channel.

local_dir

No

String

Local directory of the container to which the data input channel is mapped.

remote

Yes

remote object

Information of the data input. Enums:

  • dataset: The data input is a dataset.

  • obs: The data input is an OBS path.

Table 37 remote

Parameter

Mandatory

Type

Description

obs

No

obs object

OBS in which data input and output stored.

Table 38 obs

Parameter

Mandatory

Type

Description

obs_url

Yes

String

OBS URL of the dataset required by a training job. For example, /usr/data/.

Table 39 outputs

Parameter

Mandatory

Type

Description

name

Yes

String

Name of the data output channel.

description

No

String

Description of the data output channel.

local_dir

No

String

Local directory of the container to which the data output channel is mapped.

remote

Yes

remote object

Description of the actual data output.

Table 40 remote

Parameter

Mandatory

Type

Description

obs

Yes

obs object

OBS to which data is actually exported.

Table 41 obs

Parameter

Mandatory

Type

Description

obs_url

Yes

String

OBS URL to which data is exported.

Table 42 task_resource

Parameter

Mandatory

Type

Description

flavor_id

No

String

Resource flavor ID of a training job.

node_count

Yes

Integer

Number of resource replicas selected for a training job.

Table 43 Spec

Parameter

Mandatory

Type

Description

resource

No

SpecResource object

Resource flavors of a training job. Select either flavor_id or pool_id+[flavor_id].

volumes

No

Array of SpecVolumes objects

Volumes attached for a training job.

log_export_path

No

LogExportPath object

Export path of training job logs.

auto_stop

No

AutoStop object

Auto stop configuration of a training job.

schedule_policy

No

SchedulePolicy object

Training job scheduling policy.

notification

No

Notification object

Training event notification

custom_metrics

No

Array of CustomMetrics objects

Training metric collection configuration

Table 44 SpecResource

Parameter

Mandatory

Type

Description

flavor_id

No

String

ID of the resource flavor selected for a training job. flavor_id cannot be specified for dedicated resource pools with CPU specifications. The options for dedicated resource pools with GPU/Ascend specifications are as follows:

  • modelarts.pool.visual.xlarge (1 card)

  • modelarts.pool.visual.2xlarge (2 cards)

  • modelarts.pool.visual.4xlarge (4 cards)

  • modelarts.pool.visual.8xlarge (8 cards)

  • modelarts.pool.visual.16xlarge (16 cards, only for the 910A3 supernode resource pool)

node_count

No

Integer

Number of nodes used for creating a training job in a pool. By default, a single node is used.

pool_id

No

String

Dedicated resource pool ID.

Table 45 SpecVolumes

Parameter

Mandatory

Type

Description

nfs

No

Nfs object

NFS volumes attached for a training job.

pfs

No

Pfs object

obsfs volumes attached for a training job.

obs

No

Obs object

OBS volumes attached for a training job

Table 46 Nfs

Parameter

Mandatory

Type

Description

nfs_server_path

No

String

NFS server path, for example, 10.10.10.10:/example/path.

local_path

No

String

Path for attaching volumes to the training container, for example, /example/path.

read_only

No

Boolean

Whether the disks attached to the container in NFS mode are read-only.

Table 47 Pfs

Parameter

Mandatory

Type

Description

pfs_path

No

String

obsfs path, for example, /test-bucket/path.

local_path

No

String

Path for attaching volumes to the training container, for example, /example/path.

Table 48 Obs

Parameter

Mandatory

Type

Description

obs_path

No

String

OBS path to be attached, for example, /test-bucket/path

local_path

No

String

Path for attaching volumes to the training container, for example, /example/path

Table 49 LogExportPath

Parameter

Mandatory

Type

Description

obs_url

No

String

OBS path for storing training job logs, for example, obs://example/path.

host_path

No

String

Path of the host where training job logs are stored, for example, /example/path.

Table 50 AutoStop

Parameter

Mandatory

Type

Description

time_unit

Yes

String

Time unit. The options are as follows:

  • HOURS

duration

Yes

Integer

Running duration. The minimum value is 1.

Table 51 SchedulePolicy

Parameter

Mandatory

Type

Description

required_affinity

No

RequiredAffinity object

Affinity requirements for training jobs.

priority

No

Integer

Priority of the training job.

preemptible

No

Boolean

Whether preemption is allowed

Table 52 RequiredAffinity

Parameter

Mandatory

Type

Description

affinity_type

No

String

Affinity scheduling policy. Possible values are as follows:

  • cabinet: strong cabinet scheduling

  • hyperinstance: supernode affinity scheduling

affinity_group_size

No

Integer

Affinity group size. This parameter is mandatory when affinity_type is set to hyperinstance. In this case, the system schedules tasks specified by affinity_group_size to a supernode to form an affinity group.

When a user delivers a training job to the supernode resource pool, if the affinity group size is not set, the system sets the value to 1 by default.

Table 53 Notification

Parameter

Mandatory

Type

Description

topic_urn

No

String

URN of the selected topic in SMN

events

No

Array of strings

Training event that triggers message notification. The value can be:

JobStarted: The job is started.

JobCompleted: The job is completed.

JobFailed: The job is failed.

JobTerminated: The job is terminated.

JobRestarted: The job is restarted.

JobHanged: The job is suspended.

JobPreempted: The job is preempted.

Table 54 CustomMetrics

Parameter

Mandatory

Type

Description

metrics_url

No

String

URL for collecting metrics. Either configure all ports or leave all ports blank.

metrics_port

No

Integer

Port for collecting metrics. Either configure all ports or leave all ports blank.

Table 55 JobEndpointsReq

Parameter

Mandatory

Type

Description

ssh

No

SSHReq object

SSH connection information.

Table 56 SSHReq

Parameter

Mandatory

Type

Description

key_pair_names

No

Array of strings

Specifies the SSH key pair name, which can be created and viewed on the Key Pair page of the ECS console.

Response Parameters

Status code: 201

Table 57 Response body parameters

Parameter

Type

Description

kind

String

Training job type, which is job by default. Options:

  • job: training job

metadata

JobMetadata object

Metadata of a training job.

status

Status object

Status of a training job. You do not need to set this parameter when creating a job.

algorithm

JobAlgorithmResponse object

Algorithm used by a training job. The options are as follows:

  • id: Only the algorithm ID is used.

  • subscription_id+item_version_id: The subscription ID and version ID of the algorithm are used.

  • code_dir+boot_file: The code directory and boot file of the training job are used.

tasks

Array of TaskResponse objects

List of tasks in heterogeneous training jobs.

spec

SpecResponce object

Specifications of a training job.

endpoints

JobEndpointsResp object

This section describes the configurations required for remotely accessing a training job.

Table 58 JobMetadata

Parameter

Type

Description

id

String

Training job ID, which is generated and returned by ModelArts after the training job is created.

name

String

Name of a training job. The value must contain 1 to 64 characters consisting of only digits, letters, underscores (_), and hyphens (-).

workspace_id

String

Workspace where a job is located. The default value is 0.

description

String

Training job description. The value must contain 0 to 256 characters. The default value is NULL.

create_time

Long

Time when a training job was created, in milliseconds. The value is generated and returned by ModelArts after a training job is created.

user_name

String

Username for creating a training job. The username is generated and returned by ModelArts after a training job is created.

annotations

Map<String,String>

Advanced configurations of a training job. The options are as follows:

  • job_template: Template RL (heterogeneous job)

  • fault-tolerance/job-retry-num: 3 (number of retries upon a fault)

  • fault-tolerance/job-unconditional-retry: true (unconditional restart)

  • fault-tolerance/hang-retry: true (restart upon a suspension)

  • jupyter-lab/enable: true (JupyterLab training application)

  • tensorboard/enable: true (TensorBoard training application)

  • mindstudio-insight/enable: true (MindStudio Insight training application)

Table 59 Status

Parameter

Type

Description

phase

String

Level-1 status of a training job. The options are:

  • Creating: The gateway is being created.

  • Pending: waiting

  • Running

  • Failed: The task fails to be executed.

  • Completed: completed

  • Terminating: The task is being stopped.

  • Terminated: stopped

  • Abnormal: abnormal

secondary_phase

String

The level-2 status of a training job is an internal detailed status, which may be added, modified, or deleted. Dependency is not recommended. The options are:

  • Creating: The gateway is being created.

  • Queuing: queuing

  • Running

  • Failed: The task fails to be executed.

  • Completed: completed

  • Terminating: The task is being stopped.

  • Terminated: stopped

  • CreateFailed: The creation fails.

  • TerminatedFailed: The service fails to be stopped.

  • Unknown: unknown status

  • Lost: abnormal

duration

Long

Running duration of a training job, in milliseconds

node_count_metrics

Array<Array<Integer>>

Node count changes during the training job running period.

tasks

Array of strings

Tasks of a training job.

start_time

Long

Start time of a training job. The value is in timestamp format.

task_statuses

Array of TaskStatuses objects

Status of a training job task.

running_records

Array of RunningRecord objects

Running and fault recovery records of a training job

Table 60 TaskStatuses

Parameter

Type

Description

task

String

Task of a training job.

exit_code

Integer

Exit code of a training job task.

message

String

Error message of a training job task.

Table 61 RunningRecord

Parameter

Type

Description

start_at

Integer

Unix timestamp of the start time in the current running record, in seconds.

end_at

Integer

Unix timestamp of the end time in the current running record, in seconds.

start_type

String

Startup mode of the current running record.

  • init_or_rescheduled: This startup is the first running after scheduling, including the first startup and the running after scheduling recovery.

  • restarted: This startup is not the first running after scheduling but the running after a process restart.

end_reason

String

Reason why the current running record ends.

end_related_task

String

ID of the task worker that causes the end of the current running record, for example, worker-0.

end_recover

String

Fault tolerance policy used after the current running record ends. The enums are as follows:

  • npu_proc_restart: NPU in-place hot recovery

  • gpu_proc_restart: GPU in-place hot recovery

  • proc_restart: Process in-place recovery

  • pod_reschedule: Pod-level rescheduling

  • job_reschedule: Job-level rescheduling

  • job_reschedule_with_taint: Isolated job-level rescheduling

end_recover_before_downgrade

String

Tolerance policy used after the current running record ends and before the fault tolerance policy is degraded. The options are the same as those of end_recover.

Table 62 JobAlgorithmResponse

Parameter

Type

Description

id

String

Algorithm used by a training job. The options are as follows:

  • id: Only the algorithm ID is used.

  • subscription_id+item_version_id: The subscription ID and version ID of the algorithm are used.

  • code_dir+boot_file: The code directory and boot file of the training job are used.

name

String

Algorithm name.

subscription_id

String

Subscription ID of a subscribed algorithm, which must be used with item_version_id

item_version_id

String

Version ID of the subscribed algorithm, which must be used with subscription_id

code_dir

String

Code directory of a training job, for example, /usr/app/. This parameter must be set together with boot_file. If id or subscription_id+item_version_id has been set for boot_file, you do not need to set this parameter.

boot_file

String

Boot file of a training job, which needs to be stored in the code directory. for example, /usr/app/boot.py. This parameter must be used together with code_dir. If id or subscription_id+item_version_id has been set for code_dir, you do not need to set this parameter.

autosearch_config_path

String

YAML configuration path of an auto search job. An OBS URL is required. For example, obs://bucket/file.yaml.

autosearch_framework_path

String

Framework code directory of auto search jobs. An OBS URL is required. For example, obs://bucket/files/.

command

String

Boot command for starting the container of a custom image for a training job. For example, python train.py.

parameters

Array of Parameter objects

Running parameters of a training job.

policies

policies object

Policies supported by jobs.

inputs

Array of Input objects

Input of a training job.

outputs

Array of Output objects

Output of a training job.

engine

JobEngine object

Engine of a training job. Leave this parameter blank if the job is created using id of the algorithm in algorithm management, or subscription_id+item_version_id of the subscribed algorithm.

local_code_dir

String

Local directory of the training container to which the algorithm code directory is downloaded. The rules are as follows:

  • The directory must be under /home.

  • In v1 compatibility mode, the current field does not take effect.

  • When code_dir is prefixed with file://, the current field does not take effect.

working_dir

String

Work directory where an algorithm is executed. Note that this parameter does not take effect in v1 compatibility mode.

environments

Array of Map<String,String> objects

Environment variables of a training job. The format is key:value. Leave this parameter blank.

summary

Summary object

Visualization log summary.

Table 63 Parameter

Parameter

Type

Description

name

String

Parameter name.

value

String

Parameter value.

description

String

Parameter description.

constraint

constraint object

Parameter constraint.

i18n_description

i18n_description object

Internationalization description.

Table 64 constraint

Parameter

Type

Description

type

String

Parameter type.

editable

Boolean

Whether the parameter is editable.

required

Boolean

Whether the parameter is mandatory.

sensitive

Boolean

Whether the parameter is sensitive This function is not implemented currently.

valid_type

String

Valid type.

valid_range

Array of strings

Valid range.

Table 65 i18n_description

Parameter

Type

Description

language

String

International language[. The options are as follows:

  • zh-cn (Chinese)

  • En-us] (tag:hc,hk)

description

String

Description of an international language.

Table 66 policies

Parameter

Type

Description

auto_search

auto_search object

Hyperparameter search configuration.

Table 68 reward_attrs

Parameter

Type

Description

name

String

Metric name.

mode

String

Search mode.

  • max: A larger metric value is preferred.

  • min: A smaller metric value is preferred.

regex

String

Regular expression of a metric.

Table 69 search_params

Parameter

Type

Description

name

String

Hyperparameter name.

param_type

String

Parameter type.

  • continuous: The hyperparameter is of the continuous type. When an algorithm is used in a training job, continuous hyperparameters are displayed as text boxes on the console.

  • discrete: The hyperparameter is of the discrete type. When an algorithm is used in a training job, discrete hyperparameters are displayed as drop-down lists on the console.

lower_bound

String

Lower bound of the hyperparameter.

upper_bound

String

Upper bound of the hyperparameter.

discrete_points_num

String

Number of discrete points of a continuous hyperparameter.

discrete_values

Array of strings

List of discrete hyperparameter values.

Table 70 algo_configs

Parameter

Type

Description

name

String

Name of the search algorithm.

params

Array of AutoSearchAlgoConfigParameter objects

Search algorithm parameters.

Table 71 AutoSearchAlgoConfigParameter

Parameter

Type

Description

key

String

Parameter key.

value

String

Parameter value.

type

String

Parameter type.

Table 72 Input

Parameter

Type

Description

name

String

Name of the data input channel.

description

String

Description of the data input channel.

local_dir

String

Local directory of the container to which the data input channel is mapped Example: /home/ma-user/modelarts/inputs/data_url_0.

remote

InputDataInfo object

Information of the data input. Enums:

  • dataset: The data input is a dataset.

  • obs: The data input is an OBS path.

remote_constraint

Array of remote_constraint objects

Data input constraint

Table 73 InputDataInfo

Parameter

Type

Description

dataset

dataset object

Dataset as the data input.

obs

obs object

OBS in which data input and output stored.

Table 74 dataset

Parameter

Type

Description

id

String

Dataset ID of a training job.

version_id

String

Dataset version ID of a training job.

obs_url

String

OBS URL of the dataset for a training job. It is automatically parsed by ModelArts based on the dataset ID and dataset version ID. For example, /usr/data/.

Table 75 obs

Parameter

Type

Description

obs_url

String

OBS URL of the dataset required by a training job. For example, /usr/data/.

Table 76 remote_constraint

Parameter

Type

Description

data_type

String

Data input type, including the data storage location and dataset.

attributes

String

Attributes if a dataset is used as the data input. Options:

  • data_format: Data format

  • data_segmentation: Data segmentation

  • dataset_type: Labeling type

Table 77 Output

Parameter

Type

Description

name

String

Name of the data output channel.

description

String

Description of the data output channel.

local_dir

String

Local directory of the container to which the data output channel is mapped.

remote

Remote object

Description of the actual data output.

Table 78 JobEngine

Parameter

Type

Description

engine_id

String

Engine ID selected for a training job. The value can be engine_id, engine_name + engine_version, or image_url.

engine_name

String

Name of the engine selected for a training job. If engine_id has been set, you do not need to set this parameter.

engine_version

String

Version of the engine selected for a training job. If engine_id has been set, you do not need to set this parameter.

image_url

String

Custom image URL selected for a training job. The URL is obtained from SWR.

install_sys_packages

Boolean

Whether to install the MoXing version specified by the training platform. Value true means to install the specified MoXing version. This parameter is available only when engine_name, engine_version, and image_url are set.

Table 79 Summary

Parameter

Type

Description

log_type

String

Visualization log type of a training job. After this parameter is configured, the training job can be used as the data source of a visualization job. The options are as follows:

  • tensorboard

  • mindstudio-insight

log_dir

LogDir object

Visualization log output of a training job. This parameter is mandatory when log_type is not empty.

data_sources

Array of DataSource objects

Visualization log input of a visualization job or debug training job. This parameter is mandatory when tensorboard/enable or mindstudio-insight/enable is set to true for advanced training functions.

Table 80 LogDir

Parameter

Type

Description

pfs

PFSSummary object

Output of an OBS parallel file system.

Table 81 PFSSummary

Parameter

Type

Description

pfs_path

String

URL of an OBS parallel file system.

Table 82 DataSource

Parameter

Type

Description

job

JobSummary object

Job data source.

Table 83 JobSummary

Parameter

Type

Description

job_id

String

Training job ID.

Table 84 TaskResponse

Parameter

Type

Description

role

String

Task role. This function is not supported currently.

algorithm

TaskResponseAlgorithm object

Algorithm management and configuration.

task_resource

FlavorResponse object

Flavors of a training job or an algorithm.

Table 85 TaskResponseAlgorithm

Parameter

Type

Description

code_dir

String

Absolute path of the directory where the algorithm boot file is stored.

boot_file

String

Absolute path of the algorithm boot file.

inputs

AlgorithmInput object

Algorithm input channel.

outputs

AlgorithmOutput object

Algorithm output channel.

engine

AlgorithmEngine object

Engine on which a heterogeneous job depends.

local_code_dir

String

Local directory of the training container to which the algorithm code directory is downloaded. The rules are as follows:

  • The directory must be under /home.

  • In v1 compatibility mode, the current field does not take effect.

  • When code_dir is prefixed with file://, the current field does not take effect.

working_dir

String

Work directory where an algorithm is executed. Note that this parameter does not take effect in v1 compatibility mode.

Table 86 AlgorithmInput

Parameter

Type

Description

name

String

Name of the data input channel.

local_dir

String

Local path of the container to which the data input and output channels are mapped.

remote

AlgorithmRemote object

Actual data input, which can only be OBS for heterogeneous jobs.

Table 87 AlgorithmRemote

Parameter

Type

Description

obs

RemoteObs object

OBS in which data input and output are stored.

Table 88 AlgorithmOutput

Parameter

Type

Description

name

String

Name of the data output channel.

local_dir

String

Local directory of the container to which the data output channel is mapped.

remote

Remote object

Description of the actual data output.

mode

String

Data transmission mode. The default value is upload_periodically.

period

String

Data transmission period. The default value is 30s.

Table 89 Remote

Parameter

Type

Description

obs

RemoteObs object

OBS to which data is actually exported.

Table 90 RemoteObs

Parameter

Type

Description

obs_url

String

OBS URL to which data is exported.

Table 91 AlgorithmEngine

Parameter

Type

Description

engine_id

String

Engine ID, for example, caffe-1.0.0-python2.7.

engine_name

String

Engine name, for example, Caffe.

engine_version

String

Engine version. Engines with the same name have multiple versions, for example, Caffe-1.0.0-python2.7 of Python 2.7.

v1_compatible

Boolean

Whether the v1 compatibility mode is used.

run_user

String

User UID started by default by the engine.

image_url

String

Custom image URL selected for an algorithm.

Table 92 FlavorResponse

Parameter

Type

Description

flavor_id

String

ID of the resource flavor.

flavor_name

String

Name of the resource flavor.

max_num

Integer

Maximum number of nodes in a resource flavor.

flavor_type

String

Resource flavor type. Options:

  • CPU

  • GPU

  • Ascend

billing

BillingInfo object

Billing information of a resource flavor.

flavor_info

FlavorInfoResponse object

Resource flavor details.

attributes

Map<String,String>

Other specification attributes.

Table 93 FlavorInfoResponse

Parameter

Type

Description

max_num

Integer

Maximum number of nodes that can be selected. The value 1 indicates that the distributed mode is not supported.

cpu

Cpu object

CPU specifications.

gpu

Gpu object

GPU specifications.

npu

Npu object

Ascend specifications.

memory

Memory object

Memory information.

disk

DiskResponse object

Disk information.

Table 94 DiskResponse

Parameter

Type

Description

size

Integer

Disk size.

unit

String

Unit of the disk size.

Table 95 SpecResponce

Parameter

Type

Description

resource

Resource object

Resource flavors of a training job. Select either flavor_id or pool_id+[flavor_id].

volumes

Array of JobVolume objects

Volumes attached for a training job.

log_export_path

LogExportPath object

Export path of training job logs.

schedule_policy

SchedulePolicy object

Training job scheduling policy.

custom_metrics

Array of CustomMetrics objects

Metric collection configuration

Table 96 Resource

Parameter

Type

Description

policy

String

Resource specification mode of a training job. The value can be regular, indicating the standard mode.

flavor_id

String

ID of the resource flavor selected for a training job. flavor_id cannot be specified for dedicated resource pools with CPU specifications. The options for dedicated resource pools with GPU/Ascend specifications are as follows:

  • modelarts.pool.visual.xlarge (1 card)

  • modelarts.pool.visual.2xlarge (2 cards)

  • modelarts.pool.visual.4xlarge (4 cards)

  • modelarts.pool.visual.8xlarge (8 cards)

flavor_name

String

Read-only flavor name returned by ModelArts when flavor_id is used.

node_count

Integer

Number of resource replicas selected for a training job.

pool_id

String

Resource pool ID selected for a training job.

flavor_detail

FlavorDetail object

Flavor details of a training job or algorithm. This parameter is available only for public resource pools.

Table 97 FlavorDetail

Parameter

Type

Description

flavor_type

String

Resource flavor type. The options are as follows:

  • CPU

  • GPU

  • Ascend

billing

BillingInfo object

Billing information of a resource flavor.

flavor_info

FlavorInfo object

Resource flavor details.

Table 98 BillingInfo

Parameter

Type

Description

code

String

Billing code.

unit_num

Integer

Billing unit.

Table 99 FlavorInfo

Parameter

Type

Description

max_num

Integer

Maximum number of nodes that can be selected. The value 1 indicates that the distributed mode is not supported.

cpu

Cpu object

CPU specifications.

gpu

Gpu object

GPU specifications.

npu

Npu object

Ascend specifications.

memory

Memory object

Memory information.

disk

Disk object

Disk information.

Table 100 Cpu

Parameter

Type

Description

arch

String

CPU architecture.

core_num

Integer

Number of cores.

Table 101 Gpu

Parameter

Type

Description

unit_num

Integer

Number of GPUs.

product_name

String

Product name.

memory

String

Memory.

Table 102 Npu

Parameter

Type

Description

unit_num

String

Number of NPUs.

product_name

String

Product name.

memory

String

Memory.

Table 103 Memory

Parameter

Type

Description

size

Integer

Memory size.

unit

String

Number of memory units.

Table 104 Disk

Parameter

Type

Description

size

String

Disk size.

unit

String

Unit of the disk size, which is GB generally.

Table 105 JobVolume

Parameter

Type

Description

nfs

Nfs object

Volumes attached in NFS mode.

Table 106 Nfs

Parameter

Type

Description

nfs_server_path

String

NFS server path, for example, 10.10.10.10:/example/path.

local_path

String

Path for attaching volumes to the training container, for example, /example/path.

read_only

Boolean

Whether the disks attached to the container in NFS mode are read-only.

Table 107 LogExportPath

Parameter

Type

Description

obs_url

String

OBS path for storing training job logs, for example, obs://example/path.

host_path

String

Path of the host where training job logs are stored, for example, /example/path.

Table 108 SchedulePolicy

Parameter

Type

Description

required_affinity

RequiredAffinity object

Affinity requirements for training jobs.

priority

Integer

Priority of the training job.

preemptible

Boolean

Whether preemption is allowed

Table 109 RequiredAffinity

Parameter

Type

Description

affinity_type

String

Affinity scheduling policy. Possible values are as follows:

  • cabinet: strong cabinet scheduling

  • hyperinstance: supernode affinity scheduling

affinity_group_size

Integer

Affinity group size. This parameter is mandatory when affinity_type is set to hyperinstance. In this case, the system schedules tasks specified by affinity_group_size to a supernode to form an affinity group.

When a user delivers a training job to the supernode resource pool, if the affinity group size is not set, the system sets the value to 1 by default.

Table 110 CustomMetrics

Parameter

Type

Description

metrics_url

String

URL for collecting metrics. Either configure all ports or leave all ports blank.

metrics_port

Integer

Port for collecting metrics. Either configure all ports or leave all ports blank.

Table 111 JobEndpointsResp

Parameter

Type

Description

ssh

SSHResp object

SSH connection information.

jupyter_lab

JupyterLab object

JupyterLab connection information.

tensorboard

Tensorboard object

TensorBoard connection information.

mindstudio_insight

MindStudioInsight object

MindStudio Insight connection information.

Table 112 SSHResp

Parameter

Type

Description

key_pair_names

Array of strings

Specifies the SSH key pair name, which can be created and viewed on the Key Pair page of the ECS console.

task_urls

Array of TaskUrls objects

SSH connection address information.

Table 113 TaskUrls

Parameter

Type

Description

task

String

ID of a training job.

url

String

SSH connection address of a training job.

Table 114 JupyterLab

Parameter

Type

Description

url

String

JupyterLab address of a training job.

token

String

JupyterLab token of a training job.

Table 115 Tensorboard

Parameter

Type

Description

url

String

TensorBoard URL of a training job.

token

String

TensorBoard token of a training job

Table 116 MindStudioInsight

Parameter

Type

Description

url

String

MindStudio Insight URL of a training job.

token

String

MindStudio Insight token of a training job.

Status code: 400

Table 117 Response body parameters

Parameter

Type

Description

error_msg

String

Error message

error_code

String

Error code

error_solution

String

Solution

Example Requests

  • The following is an example of how to create a training job with free specifications. The job name has been set to TestModelArtsJob and the description has been set to This is a ModelArts job. The required algorithm's ID is 3f5d6706-7b67-408d-8ba0-ec08048c45ed. The inputs and outputs have not been defined for the algorithm.

    POST https://endpoint/v2/{project_id}/training-jobs
    
    {
      "kind" : "job",
      "metadata" : {
        "name" : "TestModelArtsJob",
        "description" : "This is a ModelArts job"
      },
      "algorithm" : {
        "id" : "3f5d6706-7b67-408d-8ba0-ec08048c45ed",
        "parameters" : [ {
          "name" : "input_dir",
          "value" : "obs://cn-north-4-rse/test/moxingtest-dir/"
        }, {
          "name" : "input_file",
          "value" : "obs://cn-north-4-rse/test/moxingtest/"
        }, {
          "name" : "large_file_method",
          "value" : "1"
        } ],
        "policies" : {
          "auto_search" : null
        },
        "environments" : { }
      },
      "spec" : {
        "resource" : {
          "flavor_id" : "modelarts.p3.large.public.free",
          "node_count" : 1
        },
        "log_export_path" : {
          "obs_url" : ""
        }
      }
    }
  • The following is an example of how to use a custom image to create a training job whose name is TestModelArtsJob2 and description is This is a ModelArts job2. A dedicated resource pool and NFS mounting are used.

    POST https://endpoint/v2/{project_id}/training-jobs
    
    {
      "kind" : "job",
      "metadata" : {
        "name" : "TestModelArtsJob2",
        "description" : "This is a ModelArts job2"
      },
      "algorithm" : {
        "engine" : {
          "image_url" : "xxxxxxxx/fastseq:1.2"
        },
        "command" : "cd /home/ma-user/ddp_demo && sh run_ddp.sh",
        "parameters" : [ ],
        "policies" : {
          "auto_search" : null
        },
        "environments" : {
          "NCCL_DEBUG" : "INFO",
          "NCCL_IB_DISABLE" : "0"
        }
      },
      "spec" : {
        "resource" : {
          "flavor_id" : "modelarts.pool.visual.xlarge",
          "node_count" : 1,
          "pool_id" : "poolfaf38d76"
        },
        "log_export_path" : {
          "obs_url" : "/cn-north-4-training-test/limou/ddp-demo-log/"
        },
        "volumes" : [ {
          "nfs" : {
            "nfs_server_path" : "192.168.0.82:/",
            "local_path" : "/home/ma-user/nfs/",
            "read_only" : false
          }
        } ]
      }
    }

Example Responses

Status code: 201

ok

{
  "kind" : "job",
  "metadata" : {
    "id" : "425b7087-83de-49ed-9e40-5bb642be956f",
    "name" : "TestModelArtsJob",
    "description" : "This is a ModelArts job",
    "create_time" : 1637045545982,
    "workspace_id" : "0",
    "user_name" : ""
  },
  "status" : {
    "phase" : "Creating",
    "secondary_phase" : "Creating",
    "duration" : 0,
    "start_time" : 0,
    "node_count_metrics" : null,
    "tasks" : [ "worker-0", "server-0" ]
  },
  "algorithm" : {
    "id" : "3f5d6706-7b67-408d-8ba0-ec08048c45ed",
    "name" : "ttt-obs-gpu",
    "code_dir" : "/cn-north-4-rse/test/moxingtest-code/",
    "boot_file" : "/cn-north-4-rse/test/moxingtest-code/test_obs_gpu.py",
    "parameters" : [ {
      "name" : "input_dir",
      "description" : "",
      "i18n_description" : null,
      "value" : "s://cn-north-4-rse/test/moxingtest-dir/",
      "constraint" : {
        "type" : "String",
        "editable" : true,
        "required" : true,
        "sensitive" : false,
        "valid_type" : "None",
        "valid_range" : [ ]
      }
    }, {
      "name" : "input_file",
      "description" : "",
      "i18n_description" : null,
      "value" : "obs://cn-north-4-rse/test/moxingtest/",
      "constraint" : {
        "type" : "String",
        "editable" : true,
        "required" : true,
        "sensitive" : false,
        "valid_type" : "None",
        "valid_range" : [ ]
      }
    }, {
      "name" : "large_file_method",
      "description" : "",
      "i18n_description" : null,
      "value" : "1",
      "constraint" : {
        "type" : "Integer",
        "editable" : true,
        "required" : true,
        "sensitive" : false,
        "valid_type" : "None",
        "valid_range" : [ ]
      }
    } ],
    "engine" : {
      "engine_id" : "horovod-cp36-tf-1.16.2",
      "engine_name" : "Horovod",
      "engine_version" : "0.16.2-TF-1.13.1-python3.6"
    },
    "policies" : { }
  },
  "spec" : {
    "resource" : {
      "policy" : "regular",
      "flavor_id" : "modelarts.p3.large.public.free",
      "flavor_name" : "Computing GPU(Vnt1) instance",
      "node_count" : 1,
      "flavor_detail" : {
        "flavor_type" : "GPU",
        "billing" : {
          "code" : "modelarts.vm.gpu.free",
          "unit_num" : 1
        },
        "flavor_info" : {
          "cpu" : {
            "arch" : "x86",
            "core_num" : 8
          },
          "gpu" : {
            "unit_num" : 1,
            "product_name" : "GP-Vnt1",
            "memory" : "32GB"
          },
          "memory" : {
            "size" : 64,
            "unit" : "GB"
          }
        }
      }
    },
    "log_export_path" : { },
    "custom_metrics" : [ {
      "metrics_url" : "/raw_text",
      "metrics_port" : 5006
    } ]
  }
}

Status code: 400

Format of the body for a common error response. The following shows the returned information when an algorithm with ID 3f5d6706-7b67-408d-8ba0-ec08048c45ee is not found.

{
  "error_msg" : "algorithm not found.",
  "error_code" : "ModelArts.2755",
  "error_solution" : "Check whether the training project information in the request is valid."
}

Status Codes

Status Code

Description

201

ok

400

Format of the body for a common error response. The following shows the returned information when an algorithm with ID 3f5d6706-7b67-408d-8ba0-ec08048c45ee is not found.

Error Codes

See Error Codes.

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