Terminating a Training Job

Function

This API is used to terminate a training job. Only jobs in the Creating, Waiting, or Running state can be terminated.

Debugging

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

URI

POST /v2/{project_id}/training-jobs/{training_job_id}/actions

Table 1 Path Parameters

Parameter

Mandatory

Type

Description

project_id

Yes

String

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

training_job_id

Yes

String

ID of a training job.

Request Parameters

Table 2 Request body parameters

Parameter

Mandatory

Type

Description

action_type

No

String

Operation performed on a training job. Select terminate to terminate a training job.

Response Parameters

Status code: 202

Table 3 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. Options:

  • 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

spec object

Specifications of a training job.

Table 4 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

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

user_name

String

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

annotations

Map<String,String>

Declaration template of a training job. For heterogeneous jobs, the default value of job_template is Template RL. For other jobs, the default value is Template DL.

Table 5 Status

Parameter

Type

Description

phase

String

Level-1 status of a training job. The value is stable. Options: Creating Pending Running Failed Completed, Terminating Terminated Abnormal

secondary_phase

String

Level-2 status of a training job. The value is unstable. Options: Creating Queuing Running Failed Completed Terminating Terminated CreateFailed TerminatedFailed Unknown Lost

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

String

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

task_statuses

Array of task_statuses objects

Status of a training job task.

Table 6 task_statuses

Parameter

Type

Description

task

String

Name of a training job task.

exit_code

Integer

Exit code of a training job task.

message

String

Error message of a training job task.

Table 7 JobAlgorithmResponse

Parameter

Type

Description

id

String

Algorithm used by a training job. Options:

  • 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 used together with boot_file. If id or subscription_id+item_version_id is set, leave it blank.

boot_file

String

Boot file of a training job, which must be stored in the code directory, for example, /usr/app/boot.py. This parameter must be used with code_dir. Leave this parameter blank if id, or subscription_id and item_version_id are specified.

autosearch_config_path

String

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

autosearch_framework_path

String

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

command

String

Boot command used to start the container of the custom image used by a training job. You can set this parameter to code_dir.

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

engine 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 to the training container to which the algorithm code directory is downloaded. Ensure that the following rules are complied with: - The directory must be in the /home directory. - 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.

Table 8 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 9 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.

valid_type

String

Valid type.

valid_range

Array of strings

Valid range.

Table 10 i18n_description

Parameter

Type

Description

language

String

Internationalization language.

description

String

Description.

Table 11 policies

Parameter

Type

Description

auto_search

auto_search object

Hyperparameter search configuration.

Table 12 auto_search

Parameter

Type

Description

skip_search_params

String

Hyperparameter parameters that need to be skipped.

reward_attrs

Array of reward_attrs objects

List of search metrics.

search_params

Array of search_params objects

Search parameters.

algo_configs

Array of algo_configs objects

Search algorithm configurations.

Table 13 reward_attrs

Parameter

Type

Description

name

String

Metric name.

mode

String

Search direction.

  • max: A larger metric value indicates better performance.

  • min: A smaller metric value indicates better performance.

regex

String

Regular expression of a metric.

Table 14 search_params

Parameter

Type

Description

name

String

Hyperparameter name.

param_type

String

Parameter type.

  • continuous: The parameter is a continuous value.

  • discreate: The parameter is a discrete value.

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 15 algo_configs

Parameter

Type

Description

name

String

Name of the search algorithm.

params

Array of AutoSearchAlgoConfigParameter objects

Search algorithm parameters.

Table 16 AutoSearchAlgoConfigParameter

Parameter

Type

Description

key

String

Parameter key.

value

String

Parameter value.

type

String

Parameter type.

Table 17 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.

remote

InputDataInfo object

Data input. Options:

  • dataset: Dataset as the data input

  • obs: OBS path as the data input

remote_constraint

Array of remote_constraint objects

Data input constraint

Table 18 InputDataInfo

Parameter

Type

Description

dataset

dataset object

Dataset as the data input.

obs

obs object

OBS in which data input and output stored.

Table 19 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 required by a training job. ModelArts automatically parses and generates the URL based on the dataset and dataset version IDs. For example, /usr/data/.

Table 20 obs

Parameter

Type

Description

obs_url

String

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

Table 21 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 22 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 23 remote

Parameter

Type

Description

obs

obs object

OBS to which data is actually exported.

Table 24 obs

Parameter

Type

Description

obs_url

String

OBS URL to which data is actually exported.

Table 25 engine

Parameter

Type

Description

engine_id

String

Engine ID selected for a training job. You can set this parameter to engine_id, engine_name + engine_version, or image_url.

engine_name

String

Name of the engine selected for a training job. If engine_id is set, leave this parameter blank.

engine_version

String

Name of the engine version selected for a training job. If engine_id is set, leave this parameter blank.

image_url

String

Custom image URL selected for a training job.

Table 26 TaskResponse

Parameter

Type

Description

role

String

Role of a heterogeneous training job. Options:

  • learner: supports GPUs or CPUs.

  • worker: supports CPUs.

algorithm

algorithm object

Algorithm management and configuration.

task_resource

FlavorResponse object

Flavors of a training job or an algorithm.

Table 27 algorithm

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

inputs object

Algorithm input channel.

outputs

outputs object

Algorithm output channel.

engine

engine object

Engine on which a heterogeneous job depends.

local_code_dir

String

Local directory to the training container to which the algorithm code directory is downloaded. Ensure that the following rules are complied with: - The directory must be in the /home directory. - 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 28 inputs

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

remote object

Actual data input. Heterogeneous jobs support only OBS.

Table 29 remote

Parameter

Type

Description

obs

obs object

OBS in which data input and output stored.

Table 30 obs

Parameter

Type

Description

obs_url

String

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

Table 31 outputs

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 32 remote

Parameter

Type

Description

obs

obs object

OBS to which data is actually exported.

Table 33 obs

Parameter

Type

Description

obs_url

String

OBS URL to which data is actually exported.

Table 34 engine

Parameter

Type

Description

engine_id

String

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

engine_name

String

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

engine_version

String

Engine version of a heterogeneous job.

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 by an algorithm.

Table 35 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

billing

billing object

Billing information of a resource flavor.

flavor_info

flavor_info object

Resource flavor details.

attributes

Map<String,String>

Other specification attributes.

Table 36 billing

Parameter

Type

Description

code

String

Billing code.

unit_num

Integer

Number of billing units.

Table 37 flavor_info

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 38 cpu

Parameter

Type

Description

arch

String

CPU architecture.

core_num

Integer

Number of cores.

Table 39 gpu

Parameter

Type

Description

unit_num

Integer

Number of GPUs.

product_name

String

Product name.

memory

String

Memory.

Table 40 npu

Parameter

Type

Description

unit_num

String

Number of NPUs.

product_name

String

Product name.

memory

String

Memory.

Table 41 memory

Parameter

Type

Description

size

Integer

Memory size.

unit

String

Memory size

Table 42 disk

Parameter

Type

Description

size

Integer

Disk size.

unit

String

Unit of the disk size.

Table 43 spec

Parameter

Type

Description

resource

Resource object

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

volumes

Array of volumes objects

Volumes attached to a training job.

log_export_path

log_export_path object

Export path of training job logs.

Table 44 Resource

Parameter

Type

Description

policy

String

Resource flavor of a training job. Options: regular

flavor_id

String

Resource flavor ID of a training job. This parameter is not supported by CPU-powered dedicated resource pools.

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

flavor_detail object

Flavors of a training job or an algorithm.

Table 45 flavor_detail

Parameter

Type

Description

flavor_type

String

Resource flavor type. Options:

  • CPU

  • GPU

billing

billing object

Billing information of a resource flavor.

flavor_info

flavor_info object

Resource flavor details.

Table 46 billing

Parameter

Type

Description

code

String

Billing code.

unit_num

Integer

Number of billing units.

Table 47 flavor_info

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 48 cpu

Parameter

Type

Description

arch

String

CPU architecture.

core_num

Integer

Number of cores.

Table 49 gpu

Parameter

Type

Description

unit_num

Integer

Number of GPUs.

product_name

String

Product name.

memory

String

Memory.

Table 50 npu

Parameter

Type

Description

unit_num

String

Number of NPUs.

product_name

String

Product name.

memory

String

Memory.

Table 51 memory

Parameter

Type

Description

size

Integer

Memory size.

unit

String

Number of memory units.

Table 52 disk

Parameter

Type

Description

size

String

Disk size.

unit

String

Unit of the disk size. Generally, the value is GB.

Table 53 volumes

Parameter

Type

Description

nfs

nfs object

Volumes attached in NFS mode.

Table 54 nfs

Parameter

Type

Description

nfs_server_path

String

NFS server path.

local_path

String

Path for attaching volumes to the training container.

read_only

Boolean

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

Table 55 log_export_path

Parameter

Type

Description

obs_url

String

OBS URL for storing training job logs.

host_path

String

Path of the host where training job logs are stored.

Example Requests

The following shows how to stop the training job whose UUID is 3faf5c03-aaa1-4cbe-879d-24b05d997347.

POST https://endpoint/v2/{project_id}/training-jobs/cf63aba9-63b1-4219-b717-708a2665100b/actions

{
  "action_type" : "terminate"
}

Example Responses

Status code: 202

ok

{
  "kind" : "job",
  "metadata" : {
    "id" : "cf63aba9-63b1-4219-b717-708a2665100b",
    "name" : "trainjob--py14_mem06-110",
    "description" : "",
    "create_time" : 1636515222282,
    "workspace_id" : "0",
    "user_name" : "ei_modelarts_z00424192_01"
  },
  "status" : {
    "phase" : "Terminating",
    "secondary_phase" : "Terminating",
    "duration" : 0,
    "start_time" : 0,
    "node_count_metrics" : null,
    "tasks" : [ "worker-0" ]
  },
  "algorithm" : {
    "code_dir" : "obs://test/economic_test/py_minist/",
    "boot_file" : "obs://test/economic_test/py_minist/minist_common.py",
    "inputs" : [ {
      "name" : "data_url",
      "local_dir" : "/home/ma-user/modelarts/inputs/data_url_0",
      "remote" : {
        "obs" : {
          "obs_url" : "/test/data/py_minist/"
        }
      }
    } ],
    "outputs" : [ {
      "name" : "train_url",
      "local_dir" : "/home/ma-user/modelarts/outputs/train_url_0",
      "remote" : {
        "obs" : {
          "obs_url" : "/test/train_output/"
        }
      }
    } ],
    "engine" : {
      "engine_id" : "pytorch-cp36-1.4.0-v2",
      "engine_name" : "PyTorch",
      "engine_version" : "PyTorch-1.4.0-python3.6-v2"
    }
  },
  "spec" : {
    "resource" : {
      "policy" : "economic",
      "flavor_id" : "modelarts.vm.p100.large.eco",
      "flavor_name" : "Computing GPU(P100) instance",
      "node_count" : 1,
      "flavor_detail" : {
        "flavor_type" : "GPU",
        "billing" : {
          "code" : "modelarts.vm.gpu.p100.eco",
          "unit_num" : 1
        },
        "flavor_info" : {
          "cpu" : {
            "arch" : "x86",
            "core_num" : 8
          },
          "gpu" : {
            "unit_num" : 1,
            "product_name" : "NVIDIA-P100",
            "memory" : "8GB"
          },
          "memory" : {
            "size" : 64,
            "unit" : "GB"
          }
        }
      }
    }
  }
}

Status Codes

Status Code

Description

202

ok

Error Codes

See Error Codes.