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.
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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.
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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
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
|
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 |
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. |
Parameter |
Type |
Description |
---|---|---|
installer |
String |
Installer |
packages |
package array |
Collection of dependency packages |
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:
|
Parameter |
Mandatory |
Type |
Description |
---|---|---|---|
f1 |
Yes |
Double |
Mean |
recall |
Yes |
Double |
Recall |
precision |
Yes |
Double |
Precision |
accuracy |
Yes |
Double |
Accuracy |
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