Obtaining the Details About a Training Job
Sample Code
In ModelArts notebook, you do not need to enter authentication parameters for session authentication. For details about session authentication of other development environments, see Session Authentication.
- Method 1: Use the specified job_id.
from modelarts.session import Session from modelarts.estimatorV2 import Estimator session = Session() estimator = Estimator(session=session, job_id="618222c4-dc2f-4cfe-bc49-72b075b7552f") job_info = estimator.get_job_info() print(job_info)
- Method 2: Use the training job created in Creating a Training Job.
job_info = job_instance.get_job_info() print(job_info)
Parameters
Parameter |
Mandatory |
Type |
Description |
---|---|---|---|
session |
Yes |
Object |
Session object. For details about the initialization method, see Session Authentication. |
job_id |
Yes |
String |
ID of a training job. You can obtain job_id using the training job created in Creating a Training Job, for example, job_instance.job_id, or from the response obtained in Obtaining Training Jobs. |
Parameter |
Type |
Description |
---|---|---|
kind |
String |
Training job type, which defaults to job. Options:
|
metadata |
JobMetadata object |
Metadata of a training job. |
status |
Status object |
Status of a training job. When creating a training job, you do not need to set this parameter. |
algorithm |
JobAlgorithmResponse object |
Algorithm used by a training job. The following formats are supported:
|
tasks |
Array of TaskResponse objects |
Tasks of a heterogeneous training job. |
spec |
spec object |
Specifications of a training job. |
Parameter |
Type |
Description |
---|---|---|
id |
String |
Training job ID, which is generated and returned by ModelArts after a 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 training job is deployed. Default value: 0 |
description |
String |
Description of a training job, which defaults to NULL. The value must contain 0 to 256 characters. |
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> |
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. |
Parameter |
Type |
Description |
---|---|---|
phase |
String |
Level-1 status of a training job. The value will remain unchanged. Options: Creating, Pending, Running, Failed, Completed, Terminating, Terminated, and Abnormal |
secondary_phase |
String |
Level-2 status of a training job. The value can be changed. Options: Creating, Queuing, Running, Failed, Completed, Terminating, Terminated, CreateFailed, TerminatedFailed, Unknown, and Lost |
duration |
Long |
Running duration of a training job, in milliseconds |
node_count_metrics |
Array<Array<Integer>> |
Node count changes during the runtime of a training job |
tasks |
Array of strings |
Task of a training job |
start_time |
String |
Start time of a training job. The value is in timestamp format. |
task_statuses |
Array of objects |
Status of a training job task |
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 |
Parameter |
Type |
Description |
---|---|---|
id |
String |
Algorithm ID Options:
|
name |
String |
Algorithm name |
subscription_id |
String |
Subscription ID of the 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 with boot_file. Leave this parameter blank if id, or subscription_id and item_version_id are specified. |
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 an auto search job. An OBS URL is required. |
autosearch_framework_path |
String |
Framework code directory of an auto search job. An OBS URL is required. |
command |
String |
Boot command for starting the container of the custom image used for creating a training job. The value of this parameter can be the same as the code_dir value. |
parameters |
Array of Parameter objects |
Running parameters of a training job. |
policies |
policies object |
Policies supported by a training job. |
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 and item_version_id of the subscribed algorithm. |
environments |
Map<String,String> |
Environment variables of a training job in the format of "key":"value". Leave this parameter blank. |
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 |
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 |
Parameter |
Type |
Description |
---|---|---|
language |
String |
Internationalization language |
description |
String |
Description |
Parameter |
Type |
Description |
---|---|---|
auto_search |
auto_search object |
Hyperparameter search configuration |
Parameter |
Type |
Description |
---|---|---|
skip_search_params |
String |
Hyperparameter parameters that need to be skipped |
reward_attrs |
Array of objects |
Search metrics |
search_params |
Array of objects |
Search parameters |
algo_configs |
Array of objects |
Search algorithm configurations |
Parameter |
Type |
Description |
---|---|---|
name |
String |
Metric name |
mode |
String |
Search mode
|
regex |
String |
Regular expression of a metric |
Parameter |
Type |
Description |
---|---|---|
name |
String |
Hyperparameter name |
param_type |
String |
Parameter type
|
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 hyperparameter with continuous values |
discrete_values |
Array of strings |
Discrete hyperparameter values |
Parameter |
Type |
Description |
---|---|---|
name |
String |
Name of the search algorithm |
params |
Array of AutoSearchAlgoConfigParameter objects |
Search algorithm parameters |
Parameter |
Type |
Description |
---|---|---|
key |
String |
Parameter key |
value |
String |
Parameter value |
type |
String |
Parameter type |
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 |
Information of the data input |
remote_constraint |
Array of objects |
Data input constraint |
Parameter |
Type |
Description |
---|---|---|
dataset |
dataset object |
Dataset as the data input |
obs |
obs object |
OBS in which data input and output are stored |
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, which is automatically parsed by ModelArts based on the dataset ID and dataset version IDs, for example, /usr/data/ |
Parameter |
Type |
Description |
---|---|---|
obs_url |
String |
OBS URL of the dataset for a training job, for example, /usr/data/ |
Parameter |
Type |
Description |
---|---|---|
data_type |
String |
Data input type, including the data storage location and dataset |
attributes |
String |
Attributes when a dataset functions as the data input Options:
|
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 |
Information of the data output |
Parameter |
Type |
Description |
---|---|---|
obs_url |
String |
OBS URL to which data is exported |
Parameter |
Type |
Description |
---|---|---|
engine_id |
String |
Engine ID selected for a training job, which can be engine_id, engine_name and engine_version, or image_url |
engine_name |
String |
Name of the engine selected for a training job. Leave this parameter blank if engine_id is specified. |
engine_version |
String |
Version of the engine selected for a training job. Leave this parameter blank if engine_id is specified. |
image_url |
String |
Custom image URL selected for a training job |
Parameter |
Type |
Description |
---|---|---|
role |
String |
Role of a heterogeneous training job task Options:
|
algorithm |
algorithm object |
Algorithm configurations in algorithm management |
task_resource |
FlavorResponse object |
Flavors for a training job or an 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 |
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, which can only be OBS for heterogeneous jobs |
Parameter |
Type |
Description |
---|---|---|
obs |
obs object |
OBS in which data input and output are stored |
Parameter |
Type |
Description |
---|---|---|
obs_url |
String |
OBS URL of the dataset for a training job, for example, /usr/data/ |
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 |
Information of the data output |
mode |
String |
Data transmission mode, which defaults to upload_periodically |
period |
String |
Data transmission period, which defaults to 30s |
Parameter |
Type |
Description |
---|---|---|
obs |
obs object |
OBS to which data is exported |
Parameter |
Type |
Description |
---|---|---|
obs_url |
String |
OBS URL to which data is exported |
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 v1 is compatible |
run_user |
String |
User UID for which the engine is started by default |
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 with the resource flavor |
flavor_type |
String |
Resource flavor type. Options:
|
billing |
billing object |
Billing information of a resource flavor |
flavor_info |
flavor_info object |
Resource flavor details |
attributes |
Map<String,String> |
Other flavor attributes |
Parameter |
Type |
Description |
---|---|---|
code |
String |
Billing code |
unit_num |
Integer |
Number of billing units |
Parameter |
Type |
Description |
---|---|---|
max_num |
Integer |
Maximum number of nodes that can be selected. 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 |
Parameter |
Type |
Description |
---|---|---|
arch |
String |
CPU architecture |
core_num |
Integer |
Number of cores |
Parameter |
Type |
Description |
---|---|---|
unit_num |
Integer |
Number of GPUs |
product_name |
String |
Product name |
memory |
String |
Memory |
Parameter |
Type |
Description |
---|---|---|
unit_num |
String |
Number of NPUs |
product_name |
String |
Product name |
memory |
String |
Memory |
Parameter |
Type |
Description |
---|---|---|
size |
Integer |
Memory size |
unit |
String |
Number of memory units |
Parameter |
Type |
Description |
---|---|---|
resource |
Resource object |
Resource flavors of a training job, which can either be flavor_id or pool_id and flavor_id |
volumes |
Array of objects |
Volumes attached for a training job |
log_export_path |
log_export_path object |
Export path of training job logs |
Parameter |
Type |
Description |
---|---|---|
policy |
String |
Resource flavor mode of a training job. Options: regular, economic, and turbo |
flavor_id |
String |
Resource flavor ID of a training job |
flavor_name |
String |
Read-only flavor name returned by ModelArts when flavor_id is specified |
node_count |
Integer |
Number of resource replicas selected for a training job Minimum value: 1 |
pool_id |
String |
Resource pool ID selected for a training job |
flavor_detail |
flavor_detail object |
Flavors for a training job or an algorithm |
Parameter |
Type |
Description |
---|---|---|
flavor_type |
String |
Resource flavor type. Options:
|
billing |
billing object |
Billing information of a resource flavor |
flavor_info |
flavor_info object |
Resource flavor details |
Parameter |
Type |
Description |
---|---|---|
code |
String |
Billing code |
unit_num |
Integer |
Number of billing units |
Parameter |
Type |
Description |
---|---|---|
max_num |
Integer |
Maximum number of nodes that can be selected. 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 |
Parameter |
Type |
Description |
---|---|---|
arch |
String |
CPU architecture |
core_num |
Integer |
Number of cores |
Parameter |
Type |
Description |
---|---|---|
unit_num |
Integer |
Number of GPUs |
product_name |
String |
Product name |
memory |
String |
Memory |
Parameter |
Type |
Description |
---|---|---|
unit_num |
String |
Number of NPUs |
product_name |
String |
Product name |
memory |
String |
Memory |
Parameter |
Type |
Description |
---|---|---|
size |
Integer |
Memory size |
unit |
String |
Number of memory units |
Parameter |
Type |
Description |
---|---|---|
size |
String |
Disk size |
unit |
String |
Unit of the disk size, which is GB generally |
Parameter |
Type |
Description |
---|---|---|
nfs |
nfs object |
Disks attached in NFS mode |
Parameter |
Type |
Description |
---|---|---|
nfs_server_path |
String |
NFS server path |
local_path |
String |
Path for attaching disks to the training container |
read_only |
Boolean |
Whether the disks attached to the container in NFS mode are read-only |
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 |
Parameter |
Type |
Description |
---|---|---|
error_msg |
String |
Error message when calling an API failed. This parameter is unavailable if an API is successfully called. |
error_code |
String |
Error code when calling an API failed. For details, see "Error Codes" in ModelArts API Reference. This parameter is unavailable if an API is successfully called. |
error_solution |
String |
Solution to an API calling failure. This parameter is unavailable if an API is successfully called. |
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