Querying the Algorithm List

Function

This API is used to obtain the list of all algorithms on ModelArts.

This API applies to the following scenarios: When you need to view all available algorithms on the platform, you can call this API to obtain the algorithm list. Before using this API, ensure that you have the permission to view the algorithm list. After the query is complete, the platform returns an algorithm list. Information such as the algorithm name and ID is displayed. If you do not have the permission to perform operations, 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.

Authorization Information

Each account has all the permissions required to call all APIs, but IAM users must be assigned the required permissions.

If you are using role/policy-based authorization, see Permissions Policies and Supported Actions for details on the required permissions.
If you are using identity policy-based authorization, the following identity policy-based permissions are required.

Action

Access Level

Resource Type (*: required)

Condition Key

Alias

Dependencies

modelarts:aiAlgorithm:list

List

-

-

-

-

Action	Access Level	Resource Type (*: required)	Condition Key	Alias	Dependencies
modelarts:aiAlgorithm:list	List	-	-	-	-

URI

GET /v2/{project_id}/algorithms

**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: N/A Range: The value can contain 1 to 64 characters. Only letters, digits, and hyphens (-) are allowed. Default Value: N/A

**Table 2** Query Parameters
Parameter	Mandatory	Type	Description
offset	No	Integer	Definition: Start page for pagination display Constraints: The minimum value is 0. For example, if this parameter is set to 0, the query starts from the first page. Range: N/A Default Value: 0
limit	No	Integer	Definition: Number of records on each page for obtaining algorithms. Constraints: The value ranges from 1 to 50. Range: N/A. Default Value: N/A
sort_by	No	String	Definition: Metric for sorting algorithms to be queried Constraints: N/A Range: N/A Default Value: create_time is used for sorting by default.
order	No	String	Definition: Order of queried algorithms Constraints: N/A Range: asc: The queried algorithms are sorted in ascending order. desc: The queried algorithms are sorted in descending order. Default Value: desc
searches	No	String	Definition: Filter criteria for querying algorithms, for example, fuzzy match by the algorithm name: searches = name:algorithm-. Constraints: Multi-condition query is supported. Format: searches=key1:value1,key2:value2. Range: N/A. Default Value: N/A
workspace_id	No	String	Definition: Workspace ID. Constraints: If no workspaces are available, the default value is 0. If a workspace is created and used, use the actual value. For details about how to obtain the ID, see Querying the Workspace List. Range: N/A Default Value: N/A

Request Parameters

None

Response Parameters

Status code: 200

**Table 3** Response body parameters
Parameter	Type	Description
total	Integer	Definition: Total number of algorithms of the current user. Range: N/A
count	Integer	Definition: Total number of algorithms that meet the search criteria of the current user. Range: N/A
limit	Integer	Definition: Maximum number of obtained algorithms of the current user. Range: 1 to 50.
offset	Integer	Definition: Offset of all algorithm obtained of the current user. Range: N/A
sort_by	String	Definition: Fields used to sort obtained algorithms of the current user. Range: N/A
order	String	Definition: Order of queried algorithms of the current user. Range: asc: ascending order desc: descending order.
group_by	String	Definition: Grouping mode of obtained algorithms of the current user. Range: N/A
items	Array of AlgorithmResponse objects	Definition: Details of the algorithms that meet the search criteria of the current user.

**Table 4** AlgorithmResponse
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, which specifies whether and how the algorithm supports three types of advanced training features: elastic training, shared GPU training, and automated hyperparameter search.

**Table 5** metadata
Parameter	Type	Description
id	String	Definition: Algorithm ID. You do not need to set this parameter when creating an algorithm. Range: N/A
name	String	Definition: Algorithm name. Range: The value must contain 1 to 64 characters consisting of only digits, letters, underscores (_), and hyphens (-).
description	String	Definition: Algorithm description. Range: The value can contain 0 to 256 characters.
workspace_id	String	Definition: Workspace where a specified algorithm is located. The value 0 indicates the default workspace. Range: N/A
ai_project	String	Definition: AI project to which a specified algorithm belongs. 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	Boolean	Definition: Algorithm availability. Range true: available false: unavailable
state	String	Definition: Algorithm status. Range: N/A
tags	Array of Map<String,String> objects	Definition: algorithm tag, in key/value format. The key is the tag name, and the value is the tag value.
attr_list	Array of strings	Definition: Algorithm attributes.
version_num	Integer	Definition: Number of algorithm versions. Range: N/A
size	Integer	Definition: algorithm size, in bytes. Range: N/A
create_time	Long	Definition: Algorithm creation timestamp, which is a Unix timestamp in milliseconds. Range: N/A
update_time	Long	Definition: Algorithm update timestamp, which is a Unix timestamp in milliseconds. Range: N/A

**Table 6** job_config
Parameter	Type	Description
code_dir	String	Definition: Algorithm code directory, Example value: /usr/app/ 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. 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	CodeTreeNode object	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 7** 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 8** constraint
Parameter	Type	Description
type	String	Definition: Parameter type. Range: Integer: Integer Float: Floating point number String: String Boolean: Boolean value
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: - Choice: Enumerated values - Range: Range values - None: None
valid_range	Array of strings	Definition: Valid range.

**Table 9** i18n_description
Parameter	Type	Description
language	String	Definition: Internationalization language. Range: zh-cn: Chinese en-us: English](tag:hc,hk)
description	String	Definition: Internationalization language description. Range: N/A

**Table 10** 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 11** remote_constraints
Parameter	Type	Description
data_type	String	Definition: Data input type, including the data storage location and dataset. For example, obs indicates the data storage location (OBS), and modelarts_dataset indicates a ModelArts dataset. The dataset function will be brought offline soon. 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 12** 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 13** engine
Parameter	Type	Description
engine_id	String	Definition: Engine ID selected for an algorithm. Range: N/A
engine_name	String	Definition: Engine name selected for an algorithm. Range: N/A
engine_version	String	Definition: Engine version name selected for an algorithm. Range: N/A
image_url	String	Definition: Custom image URL selected for an algorithm. Range: N/A

**Table 14** CodeTreeNode
Parameter	Type	Description
name	String	Definition: Name of the current directory in the algorithm directory tree. Range: N/A
children	Array of CodeTreeNode objects	Definition: Subfiles and subdirectories in the current directory of the algorithm directory tree.

**Table 15** 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: Key-value relationship. Range: in (the inclusion relationship between the key and value), for example, flavor_type in [CPU,GPU].

**Table 16** advanced_config
Parameter	Type	Description
auto_search	auto_search object	Definition: Hyperparameter search policy.

**Table 17** 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 18** 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 19** 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 20** algo_configs
Parameter	Type	Description
name	String	Definition: Search algorithm name. Range: N/A
params	Array of AutoSearchAlgoConfigParameterResp objects	Definition: Search algorithm parameters.

**Table 21** 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 Integer Float String

Example Requests

The following shows how to query all algorithms in jobs whose names contain TestModelArtsalgorithm and maximum number of algorithms is set to 1.

GET https://endpoint/v2/{project_id}/algorithms?limit=1&searches=name%3ATestModelArtsalgorithm

Example Responses

Status code: 200

{
  "total" : 1,
  "count" : 1,
  "limit" : 1,
  "offset" : 0,
  "sort_by" : "create_time",
  "order" : "desc",
  "group_by" : "",
  "items" : [ {
    "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" : { }
  } ]
}