Help Center/ ModelArts/ SDK Reference/ Model Management/ Obtaining Details About a Model

Updated on 2024-03-21 GMT+08:00

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Obtaining Details About a Model

You can use the API to obtain the information about a model object.

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: Obtain details about a model based on the model object created in Importing a Model.

      
           from modelarts.session import Session
from modelarts.model import Model

session = Session()
model_instance = Model(session, model_id="your_model_id")
model_info = model_instance.get_model_info()
print(model_info)

Method 2: Obtain details about a model based on the model object returned in Obtaining Model Objects.

      
           from modelarts.session import Session
from modelarts.model import Model

session = Session()
model_object_list = Model.get_model_object_list(session)
model_instance = model_object_list[0]                
model_info = model_instance.get_model_info()
print(model_info)

Parameters

**Table 1** **get_model_info** response parameters
Parameter	Type	Description
model_id	String	Model ID
model_name	String	Model name
model_version	String	Model version
tenant	String	Tenant
project	String	Project
owner	String	User
create_at	Long	Time when a model is created, in milliseconds calculated from 1970.1.1 0:0:0 UTC
source_location	String	OBS path where a model resides
source_job_id	String	ID of the source training job
source_job_version	String	Version of the source training job
source_type	String	Type of a model source If a model is deployed by an ExeML project, the value is auto. If a model is deployed by a training job or OBS model file, this parameter is left blank.
model_type	String	Model type. The value can be TensorFlow, MXNet, Spark_MLlib, Scikit_Learn, XGBoost, MindSpore, Image, or PyTorch.
model_size	Long	Model size, in bytes
model_status	String	Model status. The value can be publishing, published, or failed.
description	String	Model description
execution_code	String	OBS path for storing the execution code. The name of the execution code file is fixed to customize_service.py.
schema_doc	String	Download address of the model schema file
image_address	String	Execution image path of a model. Before the image is built, that is, before a model has been published as a service, this parameter is left blank.
input_params	params array	Collection of input parameters of a model. By default, this parameter is left blank.
output_params	params array	Collection of output parameters of a model. By default, this parameter is left blank.
dependencies	dependency array	Package required for running the code and model
model_metrics	String	Model evaluation parameter. This parameter is returned only when source_job_id and source_job_version are assigned values and the corresponding training job has evaluation results.
apis	String	All apis input and output parameters of the model

**Table 2** **params** parameters
Parameter	Type	Description
url	String	API URL
param_name	String	Parameter name, which contains a maximum of 64 characters
param_type	String	Parameter type. The value can be int, string, float, timestamp, date, or file.
min	Number	When param_type is set to int or float and min is set during model creation, the value will be returned. By default, this parameter is left blank.
max	Number	When param_type is set to int or float and max is set during model creation, the value will be returned. By default, this parameter is left blank.
param_desc	String	Parameter description, which contains a maximum of 100 characters. By default, this parameter is left blank.

**Table 3** **dependency** parameters
Parameter	Type	Description
installer	String	Installer
packages	package array	Collection of dependency packages

**Table 4** **package** parameters
Parameter	Type	Description
package_name	String	Name of a dependency package
package_version	String	Version of a dependency package
restraint	String	Version filtering criterion. The options are as follows: EXACT: the specified version ATLEAST: not earlier than the specified version ATMOST: not later than the specified version