Obtaining 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 and version_id.
from modelarts.session import Session from modelarts.estimator import Estimator session = Session() estimator = Estimator(modelarts_session=session, job_id="182626", version_id="278813") job_info = estimator.get_job_info()
Method 2: Use the training job created in Creating a Training Job.
job_info = job_instance.get_job_info()
Method 3: Use the training job version object returned in Querying the List of Training Job Versions.
job_info = job_version_instance_list[0].get_job_info()
Parameter Description¶
Parameter | Mandatory | Type | Description |
|---|---|---|---|
modelarts_session | Yes | Object | Session object. For details about the initialization method, see Session Authentication. |
job_id | Yes | String | ID of a training job. Obtain job_id using the training job object generated in Creating a Training Job, for example, job_instance.job_id, or from the response in Obtaining Training Jobs. |
version_id | Yes | String | Version ID of a training job. Obtain version_id using the training job object generated in Creating a Training Job, for example, job_instance.version_id, or from the response in Obtaining Training Jobs. |
Parameter | Type | Description |
|---|---|---|
error_msg | String | Error message when the API call fails. This parameter is not included when the API call succeeds. |
error_code | String | Error code when the API fails to be called. For details, see Error Codes in ModelArts API Reference. This parameter is not included when the API call succeeds. |
is_success | Boolean | Whether the API call succeeds |
job_id | Long | Training job ID |
job_name | String | Training job name |
job_desc | String | Description of a training job |
version_id | Long | Version ID of a training job |
version_name | String | Version name of a training job |
pre_version_id | Long | Name of the previous version of a training job |
engine_type | Short | Engine type of a training job. The mapping between engine_type and engine_name is as follows:
|
engine_name | String | Name of the engine selected for a training job. Currently, the following engines are supported:
|
engine_id | Long | ID of the engine selected for a training job |
engine_version | String | Version of the engine selected for a training job |
status | Integer | Status of a training job. For details about job statuses, see Job Statuses. |
app_url | String | Code directory of a training job |
boot_file_url | String | Boot file of a training job |
create_time | Long | Time when a training job is created |
parameter | JSON Array | Running parameters of a training job. It is a collection of label-value pairs. This parameter is a container environment variable when a job uses a custom image. |
duration | Long | Training job running duration, in milliseconds |
spec_id | Long | ID of the resource specifications selected for a training job |
core | String | Number of cores of the resource specifications |
cpu | String | CPU memory of the resource specifications |
gpu_num | Integer | Number of GPUs of the resource specifications |
gpu_type | String | GPU type of the resource specifications |
worker_server_num | Integer | Number of workers in a training job |
data_url | String | Dataset of a training job |
train_url | String | OBS path to the training job output file |
dataset_version_id | String | Dataset version ID of a training job |
dataset_id | String | Dataset ID of a training job |
data_source | JSON Array | Datasets of a training job |
model_id | Long | Model ID of a training job |
model_metric_list | JSON Array | Model metrics of a training job |
system_metric_list | JSON Array | System monitoring metrics of a training job |
user_image_url | String | SWR URL of the custom image used by a training job |
user_command | String | Boot command used to start the container of the custom image of a training job |
Parameter | Type | Description |
|---|---|---|
dataset_id | String | Dataset ID of a training job |
dataset_version | String | Dataset version ID of a training job |
type | String | Dataset type obs: Data from OBS is used. dataset: Data from a specified dataset is used. |
data_url | String | OBS bucket path |
Parameter | Type | Description |
|---|---|---|
metric | JSON Array | Validation metrics of a class of a training job |
total_metric | JSON Array | All validation metrics of a training job |
Parameter | Type | Description |
|---|---|---|
cpuUsage | JSON Array | CPU usage of a training job |
memUsage | JSON Array | Memory usage of a training job |
gpuUtil | JSON Array | GPU usage of a training job |
Parameter | Type | Description |
|---|---|---|
metric_values | JSON Array | Validation metrics of a class of a training job |
reserved_data | JSON Array | Reserved parameter |
metric_meta | JSON Array | A class of a training job, including the class ID and name |
Parameter | Type | Description |
|---|---|---|
recall | JSON Array | Recall of a class of a training job |
precision | JSON Array | Precision of a class of a training job |
accuracy | JSON Array | Accuracy of a class of a training job |
Parameter | Type | Description |
|---|---|---|
total_metric_meta | JSON Array | Reserved parameter |
total_reserved_data | JSON Array | Reserved parameter |
total_metric_values | JSON Array | All validation metrics of a training job |
Parameter | Type | Description |
|---|---|---|
f1_score | Float | F1 score of a training job |
recall | Float | Total recall of a training job |
precision | Float | Total precision of a training job |
accuracy | Float | Total accuracy of a training job |