Querying the Details About a Training Job

Function

This API is used to query the details about a training job.

Debugging

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

URI

GET /v2/{project_id}/training-jobs/{training_job_id}

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

None

Response Parameters

Status code: 200

Table 2 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 3 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 4 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 5 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 6 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 7 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 8 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 9 i18n_description

Parameter	Type	Description
language	String	Internationalization language.
description	String	Description.

Table 10 policies

Parameter	Type	Description
auto_search	auto_search object	Hyperparameter search configuration.

Table 11 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 12 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 13 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 14 algo_configs

Parameter	Type	Description
name	String	Name of the search algorithm.
params	Array of AutoSearchAlgoConfigParameter objects	Search algorithm parameters.

Table 15 AutoSearchAlgoConfigParameter

Parameter	Type	Description
key	String	Parameter key.
value	String	Parameter value.
type	String	Parameter type.

Table 16 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 17 InputDataInfo

Parameter	Type	Description
dataset	dataset object	Dataset as the data input.
obs	obs object	OBS in which data input and output stored.

Table 18 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 19 obs

Parameter	Type	Description
obs_url	String	OBS URL of the dataset required by a training job. For example, /usr/data/.

Table 20 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 21 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 22 remote

Parameter	Type	Description
obs	obs object	OBS to which data is actually exported.

Table 23 obs

Parameter	Type	Description
obs_url	String	OBS URL to which data is actually exported.

Table 24 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 25 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 26 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 27 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 28 remote

Parameter	Type	Description
obs	obs object	OBS in which data input and output stored.

Table 29 obs

Parameter	Type	Description
obs_url	String	OBS URL of the dataset required by a training job. For example, /usr/data/.

Table 30 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 31 remote

Parameter	Type	Description
obs	obs object	OBS to which data is actually exported.

Table 32 obs

Parameter	Type	Description
obs_url	String	OBS URL to which data is actually exported.

Table 33 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 34 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 35 billing

Parameter	Type	Description
code	String	Billing code.
unit_num	Integer	Number of billing units.

Table 36 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 37 cpu

Parameter	Type	Description
arch	String	CPU architecture.
core_num	Integer	Number of cores.

Table 38 gpu

Parameter	Type	Description
unit_num	Integer	Number of GPUs.
product_name	String	Product name.
memory	String	Memory.

Table 39 npu

Parameter	Type	Description
unit_num	String	Number of NPUs.
product_name	String	Product name.
memory	String	Memory.

Table 40 memory

Parameter	Type	Description
size	Integer	Memory size.
unit	String	Memory size

Table 41 disk

Parameter	Type	Description
size	Integer	Disk size.
unit	String	Unit of the disk size.

Table 42 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 43 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 44 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 45 billing

Parameter	Type	Description
code	String	Billing code.
unit_num	Integer	Number of billing units.

Table 46 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 47 cpu

Parameter	Type	Description
arch	String	CPU architecture.
core_num	Integer	Number of cores.

Table 48 gpu

Parameter	Type	Description
unit_num	Integer	Number of GPUs.
product_name	String	Product name.
memory	String	Memory.

Table 49 npu

Parameter	Type	Description
unit_num	String	Number of NPUs.
product_name	String	Product name.
memory	String	Memory.

Table 50 memory

Parameter	Type	Description
size	Integer	Memory size.
unit	String	Number of memory units.

Table 51 disk

Parameter	Type	Description
size	String	Disk size.
unit	String	Unit of the disk size. Generally, the value is GB.

Table 52 volumes

Parameter	Type	Description
nfs	nfs object	Volumes attached in NFS mode.

Table 53 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 54 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 query a training job whose UUID is 3faf5c03-aaa1-4cbe-879d-24b05d997347.

GET https://endpoint/v2/{project_id}/training-jobs/3faf5c03-aaa1-4cbe-879d-24b05d997347

Example Responses

Status code: 200

ok

{
  "kind" : "job",
  "metadata" : {
    "id" : "3faf5c03-aaa1-4cbe-879d-24b05d997347",
    "name" : "trainjob--py14_mem06-108",
    "description" : "",
    "create_time" : 1636447346315,
    "workspace_id" : "0",
    "user_name" : ""
  },
  "status" : {
    "phase" : "Abnormal",
    "secondary_phase" : "CreateFailed",
    "duration" : 0,
    "start_time" : 0,
    "node_count_metrics" : [ [ 1636447746000, 0 ], [ 1636447755000, 0 ], [ 1636447756000, 0 ] ],
    "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" : {
      "flavor_id" : "modelarts.vm.p100.large.eco",
      "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,
            "memory" : "8GB"
          },
          "memory" : {
            "size" : 64,
            "unit" : "GB"
          }
        }
      }
    }
  }
}

Status Codes

Status Code	Description
200	ok

Error Codes

See Error Codes.

last updated: 2024-11-14 08:44 UTC - commit: 3b80612feba1452e3d3adbec6770d8e1b5070820