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Querying the Details About a Model

Function

This API is used to query the details about a model based on the model ID.

URI

GET /v1/{project_id}/models/{model_id}

Table 1 describes the required parameters.

**Table 1** Parameter description
Parameter	Mandatory	Type	Description
project_id	Yes	String	Project ID. For details about how to obtain the project ID, see Obtaining a Project ID.
model_id	Yes	String	Model ID

Request Body

None

Response Body

Table 2 describes the response parameters.

**Table 2** Parameter description
Parameter	Type	Description
model_id	String	Model ID
model_name	String	Model name
model_version	String	Model version
create_at	Long	Time when a model is created, in milliseconds calculated from 1970.1.1 0:0:0 UTC
tenant	String	Tenant to which a model belongs
project	String	Project to which a model belongs
owner	String	User to which a model belongs
source_location	String	OBS path where the model is located or the template address of the SWR image
source_job_id	String	ID of the source training job
source_job_version	String	Version of the source training job
source_type	String	Model source type. If the model is an ExeML model, the value is auto. If the model is deployed by a user through a training job or an 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
runtime	String	Model runtime environment
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	image path generated after model packaging
input_params	params array	Collection of input parameters of a model. For details, see Table 3.
output_params	params array	Collection of output parameters of a model. For details, see Table 3.
dependencies	dependency array	Package required for running the inference code and model. For details, see Table 4.
model_metrics	String	Model precision
apis	String	All input and output apis parameter information of a model, which is obtained from the model preview
model_source	String	Model source. Possible values are as follows: auto: ExeML algos: built-in algorithm custom: custom model
tunable	boolean	Whether a model can be tuned. Possible values are as follows: true: yes false: no
market_flag	boolean	Whether a model is subscribed from the marketplace. Possible values are as follows: true: yes false: no
publishable_flag	boolean	Whether a model can be published to the marketplace. Possible values are as follows: true: yes false: no
model_docs	GuideDoc array	List of template documents
health	Health structure	Model health check interface information
model_algorithm	String	Model algorithm type. The value can be predict_analysis, object_detection, or image_classification.
model_labels	String array	Model label array
labels_map	Map	Model label map. The key is fixed to labels, and the value is the model label array.
workspace_id	String	Workspace ID
install_type	String array	Supported service type for deployment
specification	Specification structure	Minimum model deployment specifications
config	String	Model configurations

**Table 3** **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	This parameter is optional when param_type is set to int or float. By default, this parameter is left blank.
max	Number	This parameter is optional when param_type is set to int or float. 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 4** **dependency** parameters
Parameter	Type	Description
installer	String	Installer
packages	package array	Collection of dependency packages. For details, see Table 5.

**Table 5** **package** parameters
Parameter	Type	Description
package_name	String	Name of a dependency package
package_version	String	Version of a dependency package
restraint	String	Version restriction. The value can be EXACT, ATLEAST, or ATMOST.

**Table 6** **metric** parameters
Parameter	Type	Description
f1	Double	F1 score
recall	Double	Recall
precision	Double	Precision
accuracy	Double	Accuracy

**Table 7** **GuideDoc** parameters
Parameter	Type	Description
doc_name	String	Document name
doc_url	String	HTTP(S) link of the document

**Table 8** **Health** parameters
Parameter	Type	Description
url	String	URL of the health check interface
protocol	String	Request protocol of the health check interface. Currently, only HTTP is supported.
initial_delay_seconds	String	After an instance is started, a health check starts after seconds configured in initial_delay_seconds.
timeout_seconds	String	Health check timeout

**Table 9** **Specification** parameters
Parameter	Type	Description
min_cpu	String	Minimum CPU
min_gpu	String	Minimum GPU
min_mem	String	Minimum memory capacity
min_ascend	String	Minimum Ascend

Samples

The following shows how to query the details about a model based on the model ID.

Sample request

GET    https://endpoint/v1/{project_id}/models/{model_id}

Sample response

{
"model_id": "10eb0091-887f-4839-9929-cbc884f1e20e",
"model_name": "mnist",
"model_version": "1.0.0",
"runtime": "python2.7",
"tenant": "6d28e85aa78b4e1a9b4bd83501bcd4a1",
"project": "d04c10db1f264cfeb1966deff1a3527c",
"owner": "6d28e85aa78b4e1a9b4bd83501bcd4a1",
"source_location": "https://models.obs.cn-north-4.myhuaweicloud.com/mnist",
"model_type": "TensorFlow",
"model_size": 5633481,
"model_status": "published",
"execution_code": "https://testmodel.obs.cn-north-4.myhuaweicloud.com/customize_service.py",
"image_address": "100.125.5.235:20202/models/10eb0091-887f-4839-9929-cbc884f1e20e:1.0.0",
"input_params": [{           
     "url": "/",           
     "method": "post",           
     "protocol": "http",           
     "param_name": "data",           
     "param_type": "object",           
     "param_desc": "{\"type\":\"object\",\"properties\":{\"req_data\":{\"items\":[{\"type\":\"object\",\"properties\":{}}],\"type\":\"array\"}}}"       }],
"output_params": [{           
     "url": "/",           
     "method": "post",           
     "protocol": "http",           
     "param_name": "data",           
     "param_type": "object",           
     "param_desc": "{\"type\":\"object\",\"properties\":{\"resp_data\":{\"type\":\"array\",\"items\":[{\"type\":\"object\",\"properties\":{}}]}}}"       }],
"dependencies": [{
    "installer": "pip",
    "packages": [{
        "package_name": "pkg1",
        "package_version": "1.0.1",
        "restraint": "ATLEAST"
    }]
}],
"model_metrics":"{\"f1\":0.52381,\"recall\":0.666667,\"precision\":0.466667,\"accuracy\":0.625}",
"apis": "[{\"protocol\":\"http\",\"method\":\"post\",\"url\":\"/\",\"input_params\":{\"type\":\"object\",\"properties\":{\"data\":{\"type\":\"object\",\"properties\":{\"req_data\":{\"items\":[{\"type\":\"object\",\"properties\":{}}],\"type\":\"array\"}}}}},\"output_params\":{\"type\":\"object\",\"properties\":{\"data\":{\"type\":\"object\",\"properties\":{\"resp_data\":{\"type\":\"array\",\"items\":[{\"type\":\"object\",\"properties\":{}}]}}}}}}]",
"model_labels":[],
"labels_map":{"labels":[]},
"workspace_id": "0",
"install_type": ["realtime", "batch", "edge"],
"specification":{},
"config":"{\"model_algorithm\": \"image_classification\", \"model_source\": \"auto\", \"tunable\": false, \"downloadable_flag\": true, \"algorithm\": \"resnet_v2_50,mobilenet_v1\", \"metrics\": {\"f1\": 0.912078373015873, \"recall\": 0.9125, \"precision\": 0.9340277777777778, \"accuracy\": 0.263250724969475}, \"model_type\": \"TensorFlow\", \"runtime\": \"tf1.13-python3.6-cpu\", \"apis\": [{\"protocol\": \"https\", \"url\": \"/\", \"method\": \"post\", \"request\": {\"data\": {\"type\": \"object\", \"properties\": {\"images\": {\"type\": \"file\"}}}, \"Content-type\": \"multipart/form-data\"}, \"response\": {\"data\": {\"type\": \"object\", \"required\": [\"predicted_label\", \"scores\"], \"properties\": {\"predicted_label\": {\"type\": \"string\"}, \"scores\": {\"type\": \"array\", \"items\": {\"type\": \"array\", \"minItems\": 2, \"maxItems\": 2, \"items\": [{\"type\": \"string\"}, {\"type\": \"number\"}]}}}}, \"Content-type\": \"multipart/form-data\"}}], \"dependencies\": [{\"installer\": \"pip\", \"packages\": [{\"package_name\": \"numpy\", \"package_version\": \"1.17.0\", \"restraint\": \"EXACT\"}, {\"package_name\": \"h5py\", \"package_version\": \"2.8.0\", \"restraint\": \"EXACT\"}, {\"package_name\": \"Pillow\", \"package_version\": \"5.2.0\", \"restraint\": \"EXACT\"}, {\"package_name\": \"scipy\", \"package_version\": \"1.2.1\", \"restraint\": \"EXACT\"}, {\"package_name\": \"resampy\", \"package_version\": \"0.2.1\", \"restraint\": \"EXACT\"}, {\"package_name\": \"scikit-learn\", \"package_version\": \"0.19.1\", \"restraint\": \"EXACT\"}]}]}"
}

Status Code

For details about the status code, see Table 1.

Parent topic: Models

Last Article: Querying the List of Models

Next Article: Deleting a Model

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