Querying Algorithm Details

Function

This API is used to obtain the details of a specified algorithm on ModelArts.

This API applies to the following scenario: When you need to view the detailed configuration and attributes of a specific algorithm, you can use this API to obtain the algorithm details. Before using this API, ensure that you have obtained the algorithm ID and have the permission to view algorithm details. After the query is complete, the platform returns the details, including the algorithm name, description, and version. If the algorithm ID does not exist or you do not have the operation permission, the API will return an error message.

Debugging

You can debug this API through automatic authentication in API Explorer or use the SDK sample code generated by API Explorer.

URI

GET /v2/{project_id}/algorithms/{algorithm_id}

**Table 1** Path Parameters
Parameter	Mandatory	Type	Description
project_id	Yes	String	Definition: Project ID. For details, see Obtaining a Project ID and Name. Constraints: The value can contain 1 to 64 characters. Letters, digits, and hyphens (-) are allowed. Range: N/A Default Value: N/A
algorithm_id	Yes	String	Definition: Algorithm ID Constraints: N/A Range: N/A Default Value: N/A

Request Parameters

None

Response Parameters

Status code: 200

**Table 2** Response body parameters
Parameter	Type	Description
metadata	metadata object	Definition: Algorithm metadata, which describes basic algorithm information.
job_config	job_config object	Definition: Algorithm configuration, such as the boot file.
resource_requirements	Array of resource_requirements objects	Definition: Algorithm resource constraints. This parameter is optional. After this parameter is set, the console filters available public resource pools when the algorithm is used in training jobs.
advanced_config	advanced_config object	Definition: Advanced algorithm policy. auto_search

**Table 3** metadata
Parameter	Type	Description
id	Integer	Definition: Algorithm UUID. You do not need to set this parameter when creating an algorithm. Range: N/A
name	String	Definition: Algorithm name. The value must contain 1 to 64 characters consisting of only digits, letters, underscores (_), and hyphens (-). Range: N/A
description	String	Definition: Algorithm description, which consists of 0 to 256 characters. The default value is NULL. Range: N/A
workspace_id	String	Definition: Workspace where a specified algorithm is located. The default value is 0. 0 is the default workspace. Range: N/A
ai_project	String	Definition: AI project to which a specified algorithm belongs. The default value is default-ai-project. The AI project has been brought offline. Ignore it. Range: N/A
user_name	String	Definition: Username. Range: N/A
domain_id	String	Definition: Domain ID of a user. Range: N/A
source	String	Definition: Algorithm source type. Range: N/A
api_version	String	Definition: Algorithm API version, which shows whether it is new or old. Range: N/A
is_valid	String	Definition: Algorithm availability. Range: N/A
state	String	Definition: Algorithm status. Range: N/A
tags	Array of Map<String,String> objects	Definition: Algorithm tag.
attr_list	Array of strings	Definition: Algorithm attributes.
version_num	Integer	Definition: Number of algorithm versions. The default value is 0. Range: N/A
size	Integer	Definition: Algorithm size. Range: N/A
create_time	Long	Definition: Algorithm creation timestamp. Range: N/A
update_time	Long	Definition: Algorithm update timestamp. Range: N/A

**Table 4** job_config
Parameter	Type	Description
code_dir	String	Definition: Algorithm code directory, for example, /usr/app/. This parameter must be used together with boot_file. Range: N/A
boot_file	String	Definition: Code boot file of the algorithm, which must be stored in the code directory, for example, /usr/app/boot.py. This parameter must be used with code_dir. Range: N/A
command	String	Definition: Container boot command of a custom image algorithm. Range: N/A
parameters	Array of ParameterResp objects	Definition: Running parameters of an algorithm.
inputs	Array of inputs objects	Definition: Data input of an algorithm.
outputs	Array of outputs objects	Definition: Data output of an algorithm.
engine	engine object	Definition: Algorithm engine.
code_tree	Array of code_tree objects	Definition: Algorithm directory tree.
parameters_customization	Boolean	Definition: Specifies whether the algorithm allows hyperparameter customization during training job creation. Range: true: allowed false: not allowed

**Table 5** ParameterResp
Parameter	Type	Description
name	String	Definition: Parameter name. Range: N/A
value	String	Definition: Parameter value. Range: N/A
description	String	Definition: Parameter description. Range: N/A
constraint	constraint object	Definition: Parameter attribute.
i18n_description	i18n_description object	Definition: Internationalization description.

**Table 6** constraint
Parameter	Type	Description
type	String	Definition: Parameter type. Range: N/A
editable	Boolean	Definition: Whether the parameter can be edited. Range: true: editable false: Not uneditable
required	Boolean	Definition: Whether the parameter is mandatory. Range: true: mandatory false: optional
sensitive	Boolean	Definition: Whether the parameter is sensitive. This function is unavailable currently. Range: true: sensitive false: insensitive
valid_type	String	Definition: Valid type. Range: N/A
valid_range	Array of strings	Definition: Valid range.

**Table 7** i18n_description
Parameter	Type	Description
language	String	Definition: Internationalization language. The options are as follows: zh-cn: Chinese en-us: English Range: N/A
description	String	Definition: Internationalization language description. Range: N/A

**Table 8** inputs
Parameter	Type	Description
name	String	Definition: Name of the data input channel. Range: N/A
description	String	Definition: Description of the data input channel. Range: N/A
remote_constraints	Array of remote_constraints objects	Definition: Data input constraint.

**Table 9** remote_constraints
Parameter	Type	Description
data_type	String	Definition: Data input type, including the data storage location and dataset. Range: N/A
attributes	Array of Map<String,String> objects	Definition: Attributes when the data input type is a dataset. The value can be: data_format: data format data_segmentation: data segmentation method dataset_type: data labeling type

**Table 10** outputs
Parameter	Type	Description
name	String	Definition: Name of the data output channel. Range: N/A
description	String	Definition: Description of the data output channel. Range: N/A

**Table 11** engine
Parameter	Type	Description
engine_id	String	Definition: Engine ID selected for an algorithm. Range: N/A
engine_name	String	Definition: Engine version name selected for an algorithm. If engine_id is specified, leave this parameter blank. Range: N/A
engine_version	String	Definition: Engine version name selected for an algorithm. If engine_id is specified, leave this parameter blank. Range: N/A
image_url	String	Definition: Custom image URL selected for an algorithm. Range: N/A

**Table 12** code_tree
Parameter	Type	Description
name	String	Definition: Name of the current directory in the algorithm directory tree. Range: N/A
children	Object	Definition: Subfiles and subdirectories in the current directory of the algorithm directory tree.

**Table 13** resource_requirements
Parameter	Type	Description
key	String	Definition: Resource constraints. Range: flavor_type: Flavor type, which can be CPU, Ascend, or GPU. device_distributed_mode: Specifies whether to support multi-card training. The value can be multiple (supported) or singular (not supported). host_distributed_mode: Specifies whether to support distributed training. The value can be multiple (supported) or singular (not supported).
value	Array of strings	Definition: Value of the resource constraint key.
operator	String	Definition: Relationship between keys and values. Currently, only in is supported. For example, flavor_type in [CPU,GPU]. Range: N/A

**Table 14** advanced_config
Parameter	Type	Description
auto_search	auto_search object	Definition: Hyperparameter search policy.

**Table 15** auto_search
Parameter	Type	Description
skip_search_params	String	Definition: Hyperparameter parameters that need to be skipped. Range: N/A
reward_attrs	Array of reward_attrs objects	Definition: Search metrics.
search_params	Array of search_params objects	Definition: Search parameters.
algo_configs	Array of algo_configs objects	Definition: Search algorithm configurations.

**Table 16** reward_attrs
Parameter	Type	Description
name	String	Definition: Metric name. Range: N/A
mode	String	Definition: Search mode. Range: max: A larger metric value is preferred. min: A smaller metric value is preferred.
regex	String	Definition: Regular expression of a metric. Range: N/A

**Table 17** search_params
Parameter	Type	Description
name	String	Definition: Hyperparameter name. Range: N/A
param_type	String	Definition: Parameter type. Range: continuous: The hyperparameter is of the continuous type. When an algorithm is used in a training job, continuous hyperparameters are displayed as text boxes on the console. discrete: The hyperparameter is of the discrete type. When an algorithm is used in a training job, discrete hyperparameters are displayed as drop-down lists on the console.
lower_bound	String	Definition: Lower bound of the hyperparameter. Range: N/A
upper_bound	String	Definition: Upper bound of the hyperparameter. Range: N/A
discrete_points_num	String	Definition: Number of discrete points of a hyperparameter with continuous values. Range: N/A
discrete_values	String	Definition: Discrete hyperparameter values. Range: N/A

**Table 18** algo_configs
Parameter	Type	Description
name	String	Definition: Search algorithm name. Range: N/A
params	Array of AutoSearchAlgoConfigParameterResp objects	Definition: Search algorithm parameters.

**Table 19** AutoSearchAlgoConfigParameterResp
Parameter	Type	Description
key	String	Definition: Parameter key. Range: N/A
value	String	Definition: Parameter value. Range: N/A
type	String	Definition: Parameter type. Range: N/A

Example Requests

The following shows how to query the algorithm whose UUID is 2e5451fe-913f-4492-821a-2981031382f7.

GET https://endpoint/v2/{project_id}/algorithms/2e5451fe-913f-4492-821a-2981031382f7

Example Responses

Status code: 200

{
  "metadata" : {
    "id" : "2e5451fe-913f-4492-821a-2981031382f7",
    "name" : "TestModelArtsalgorithm",
    "description" : "This is a ModelArts algorithm",
    "create_time" : 1636600721742,
    "workspace_id" : "0",
    "ai_project" : "default-ai-project",
    "user_name" : "",
    "domain_id" : "xxxxxxxxxxxxxxxxxxxxxxxxxx",
    "source" : "custom",
    "api_version" : "",
    "is_valid" : true,
    "state" : "",
    "size" : 4791,
    "tags" : null,
    "attr_list" : null,
    "version_num" : 0,
    "update_time" : 0
  },
  "job_config" : {
    "code_dir" : "/algo-test/pytorch/work1/code/",
    "boot_file" : "/algo-test/pytorch/work1/code/test-pytorch.py",
    "command" : "",
    "parameters" : [ {
      "name" : "test-parameter",
      "description" : "",
      "i18n_description" : null,
      "value" : "10",
      "constraint" : {
        "type" : "String",
        "editable" : true,
        "required" : false,
        "sensitive" : false,
        "valid_type" : "None",
        "valid_range" : [ ]
      }
    } ],
    "parameters_customization" : true,
    "inputs" : [ {
      "name" : "data_url",
      "description" : "name to translate"
    } ],
    "outputs" : [ {
      "name" : "train_url",
      "description" : "name to translate"
    } ],
    "engine" : {
      "engine_id" : "pytorch-cp36-1.3.0",
      "engine_name" : "PyTorch",
      "engine_version" : "PyTorch-1.3.0-python3.6"
    },
    "code_tree" : {
      "name" : "code/",
      "children" : [ {
        "name" : "test-pytorch.py"
      } ]
    }
  },
  "resource_requirements" : null,
  "advanced_config" : { }
}