Creating an Algorithm

Function

This API is used to create an algorithm.

URI

POST /v2/{project_id}/algorithms

**Table 1** Path Parameters
Parameter	Mandatory	Type	Description
project_id	Yes	String	Project ID. For details, see Obtaining a Project ID and Name.

Request Parameters

**Table 2** Request body parameters
Parameter	Mandatory	Type	Description
metadata	No	metadata object	Algorithm metadata, which describes basic algorithm information.
job_config	No	job_config object	Algorithm configuration, such as the boot file.
resource_requirements	No	Array of resource_requirements objects	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	No	advanced_config object	Advanced algorithm policy: auto_search

**Table 3** metadata
Parameter	Mandatory	Type	Description
id	No	Integer	Algorithm UUID. You do not need to set this parameter when creating an algorithm.
name	Yes	String	Algorithm name. The value must contain 1 to 64 characters consisting of only digits, letters, underscores (_), and hyphens (-).
description	No	String	Description of the algorithm. The value is a string of [0, 256] characters. The default value is NULL.
workspace_id	No	String	Workspace where a specified algorithm is located. The default value is 0. The value 0 indicates the default workspace.
ai_project	No	String	AI project to which a specified algorithm belongs. The default value is default-ai-project. The AI project has been brought offline. Ignore it.

**Table 4** job_config
Parameter	Mandatory	Type	Description
code_dir	No	String	Algorithm code directory, for example, /usr/app/. This parameter must be used together with boot_file.
boot_file	No	String	Code boot file of the algorithm, which needs to be stored in the code directory, for example, /usr/app/boot.py. This parameter must be used together with code_dir.
command	No	String	Container startup command of a custom image algorithm.
parameters	No	Array of Parameter objects	Running parameter of an algorithm.
inputs	No	Array of inputs objects	Data input of an algorithm.
outputs	No	Array of outputs objects	Data output of an algorithm.
engine	No	engine object	Algorithm engine.
parameters_customization	No	Boolean	Whether the algorithm allows hyperparameter customization during training job creation.

**Table 5** Parameter
Parameter	Mandatory	Type	Description
name	No	String	Parameter name.
value	No	String	Parameter value.
description	No	String	Parameter description.
constraint	No	constraint object	Parameter constraint.
i18n_description	No	i18n_description object	Internationalization description.

**Table 6** constraint
Parameter	Mandatory	Type	Description
type	No	String	Parameter type.
editable	No	Boolean	Whether the parameter is editable.
required	No	Boolean	Whether the parameter is mandatory.
sensitive	No	Boolean	Whether the parameter is sensitive This function is not implemented currently.
valid_type	No	String	Valid type.
valid_range	No	Array of strings	Valid range.

**Table 7** i18n_description
Parameter	Mandatory	Type	Description
language	No	String	Language.
description	No	String	Description.

**Table 8** inputs
Parameter	Mandatory	Type	Description
name	Yes	String	Name of the data input channel.
description	No	String	Description of the data input channel.
remote_constraints	No	Array of remote_constraints objects	Data input constraint.

**Table 9** remote_constraints
Parameter	Mandatory	Type	Description
data_type	No	String	Data input type. The data storage location (OBS) and ModelArts dataset are supported.
attributes	No	Array of Map<String,String> objects	Attributes if a dataset is used as the data input. Options: data_format: Data format data_segmentation: Data segmentation dataset_type: Labeling type

**Table 10** outputs
Parameter	Mandatory	Type	Description
name	Yes	String	Name of the data output channel.
description	No	String	Description of the data output channel.

**Table 11** engine
Parameter	Mandatory	Type	Description
engine_id	No	String	Engine ID selected for an algorithm.
engine_name	No	String	Engine version name selected for an algorithm. If engine_id is specified, leave this parameter blank.
engine_version	No	String	Engine version name selected for an algorithm. If engine_id is specified, leave this parameter blank.
image_url	No	String	Custom image URL selected by an algorithm.

**Table 12** resource_requirements
Parameter	Mandatory	Type	Description
key	No	String	Resource constraint. The options are as follows: flavor_type indicates the resource type. The value can be CPU, GPU, or Ascend (tag: hc, hk,fcs_super). device_distributed_mode: indicates whether to support multi-card training. The value can be multiple (supported) or singular (not supported). host_distributed_mode: indicates whether distributed training is supported. The value can be multiple (supported) or singular (not supported).
values	No	Array of strings	Value of the resource constraint key.
operator	No	String	Relationship between keys and values. Currently, only in is supported. For example: flavor_type in [CPU,GPU].

**Table 13** advanced_config
Parameter	Mandatory	Type	Description
auto_search	No	auto_search object	Hyperparameter search policy.

**Table 14** auto_search
Parameter	Mandatory	Type	Description
skip_search_params	No	String	Hyperparameter parameters that need to be skipped.
reward_attrs	No	Array of reward_attrs objects	List of search metrics.
search_params	No	Array of search_params objects	Search parameters.
algo_configs	No	Array of algo_configs objects	Search algorithm configurations.

**Table 15** reward_attrs
Parameter	Mandatory	Type	Description
name	No	String	Metric name.
mode	No	String	Search direction. max: A larger metric value indicates better performance. min: A smaller metric value indicates better performance.
regex	No	String	Regular expression of a metric.

**Table 16** search_params
Parameter	Mandatory	Type	Description
name	No	String	Hyperparameter name.
param_type	No	String	Parameter type If continuous is specified, 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 for training jobs, discrete hyperparameters are displayed as a drop-down list box on the console.
lower_bound	No	String	Lower bound of the hyperparameter.
upper_bound	No	String	Upper bound of the hyperparameter.
discrete_points_num	No	String	Number of discrete points of a continuous hyperparameter.
discrete_values	No	String	List of discrete hyperparameter values.

**Table 17** algo_configs
Parameter	Mandatory	Type	Description
name	No	String	Name of the search algorithm.
params	No	Array of AutoSearchAlgoConfigParameter objects	Search algorithm parameters.

**Table 18** AutoSearchAlgoConfigParameter
Parameter	Mandatory	Type	Description
key	No	String	Parameter key.
value	No	String	Parameter value.
type	No	String	Parameter type.

Response Parameters

Status code: 201

**Table 19** Response body parameters
Parameter	Type	Description
metadata	metadata object	Algorithm metadata, which describes basic algorithm information.
job_config	job_config object	Algorithm configuration, such as the boot file.
resource_requirements	Array of resource_requirements objects	Algorithm resource constraint. 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	Advanced algorithm policy: auto_search

**Table 20** metadata
Parameter	Type	Description
id	Integer	Algorithm UUID. You do not need to set this parameter when creating an algorithm.
name	String	Algorithm name. The value must contain 1 to 64 characters consisting of only digits, letters, underscores (_), and hyphens (-).
description	String	Description of the algorithm. The value is a string of [0, 256] characters. The default value is NULL.
workspace_id	String	Workspace where a specified algorithm is located. The default value is 0. The value 0 indicates the default workspace.
ai_project	String	AI project to which a specified algorithm belongs. The default value is default-ai-project. The AI project has been brought offline. Ignore it.
user_name	String	Username.
domain_id	String	Domain ID of a user.
source	String	Algorithm source.
api_version	String	Algorithm API version, which identifies the old and new ones.
is_valid	String	Algorithm availability.
state	String	Algorithm state.
tags	Array of Map<String,String> objects	Algorithm tags.
attr_list	Array of strings	Algorithm attribute list.
version_num	Integer	Number of algorithm versions. The default value is 0.
size	Integer	Algorithm size.
create_time	Long	Timestamp when the algorithm is created.
update_time	Long	Timestamp when the algorithm is updated.

**Table 21** job_config
Parameter	Type	Description
code_dir	String	Algorithm code directory, for example, /usr/app/. This parameter must be used together with boot_file.
boot_file	String	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.
command	String	Container startup command of a custom image algorithm.
parameters	Array of Parameter objects	Running parameter of an algorithm.
inputs	Array of inputs objects	Data input of an algorithm.
outputs	Array of outputs objects	Data output of an algorithm.
engine	engine object	Algorithm engine.
code_tree	Array of code_tree objects	Algorithm directory tree
parameters_customization	Boolean	Whether the algorithm allows hyperparameter customization during training job creation.

**Table 22** Parameter
Parameter	Type	Description
name	String	Parameter name.
value	String	Parameter value.
description	String	Parameter description.
constraint	constraint object	Parameter constraint.
i18n_description	i18n_description object	Internationalization description.

**Table 23** constraint
Parameter	Type	Description
type	String	Parameter type.
editable	Boolean	Whether the parameter is editable.
required	Boolean	Whether the parameter is mandatory.
sensitive	Boolean	Whether the parameter is sensitive This function is not implemented currently.
valid_type	String	Valid type.
valid_range	Array of strings	Valid range.

**Table 24** i18n_description
Parameter	Type	Description
language	String	Language.
description	String	Description.

**Table 25** inputs
Parameter	Type	Description
name	String	Name of the data input channel.
description	String	Description of the data input channel.
remote_constraints	Array of remote_constraints objects	Data input constraint.

**Table 26** remote_constraints
Parameter	Type	Description
data_type	String	Data input type, including the data storage location and dataset.
attributes	Array of Map<String,String> objects	Attributes if a dataset is used as the data input. Options: data_format: Data format data_segmentation: Data segmentation dataset_type: Labeling type

**Table 27** outputs
Parameter	Type	Description
name	String	Name of the data output channel.
description	String	Description of the data output channel.

**Table 28** engine
Parameter	Type	Description
engine_id	String	Engine ID selected for an algorithm.
engine_name	String	Engine version name selected for an algorithm. If engine_id is specified, leave this parameter blank.
engine_version	String	Engine version name selected for an algorithm. If engine_id is specified, leave this parameter blank.
image_url	String	Custom image URL selected by an algorithm.

**Table 29** code_tree
Parameter	Type	Description
name	String	Name of the current directory in the algorithm directory tree.
children	Object	Subfiles and subdirectories in the current directory of the algorithm directory tree.

**Table 30** resource_requirements
Parameter	Type	Description
key	String	Resource constraint. The options are as follows: Resource type (flavor_type). The value can be CPU, GPU, or Ascend (tag: hc, hk,fcs_super). Whether to support multi-card training (device_distributed_mode). The value can be multiple or singular. Indicates whether distributed training is supported (host_distributed_mode). The value can be multiple or singular.
value	Array of strings	Value of the resource constraint key.
operator	String	Relationship between keys and values. Currently, only in is supported. For example: flavor_type in [CPU,GPU].

**Table 31** advanced_config
Parameter	Type	Description
auto_search	auto_search object	Hyperparameter search policy.

**Table 32** auto_search
Parameter	Type	Description
skip_search_params	String	Hyperparameter parameters that need to be skipped.
reward_attrs	Array of reward_attrs objects	List of search metrics.
search_params	Array of search_params objects	Search parameters.
algo_configs	Array of algo_configs objects	Search algorithm configurations.

**Table 33** reward_attrs
Parameter	Type	Description
name	String	Metric name.
mode	String	Search direction. max: A larger metric value indicates better performance. min: A smaller metric value indicates better performance.
regex	String	Regular expression of a metric.

**Table 34** search_params
Parameter	Type	Description
name	String	Hyperparameter name.
param_type	String	Parameter type If continuous is specified, 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 for training jobs, discrete hyperparameters are displayed as a drop-down list box on the console.
lower_bound	String	Lower bound of the hyperparameter.
upper_bound	String	Upper bound of the hyperparameter.
discrete_points_num	String	Number of discrete points of a continuous hyperparameter.
discrete_values	String	List of discrete hyperparameter values.

**Table 35** algo_configs
Parameter	Type	Description
name	String	Name of the search algorithm.
params	Array of AutoSearchAlgoConfigParameter objects	Search algorithm parameters.

**Table 36** AutoSearchAlgoConfigParameter
Parameter	Type	Description
key	String	Parameter key.
value	String	Parameter value.
type	String	Parameter type.

Example Requests

The following is an example of how to create an algorithm whose name is TestModelArtsalgorithm and description is This is a ModelArts algorithm.

POST https://endpoint/v2/{project_id}/algorithms

{
  "metadata" : {
    "name" : "TestModelArtsalgorithm",
    "description" : "This is a ModelArts algorithm"
  },
  "job_config" : {
    "code_dir" : "/algo-test/pytorch/work1/code/",
    "boot_file" : "/algo-test/pytorch/work1/code/test-pytorch.py",
    "parameters" : [ {
      "name" : "test-parameter",
      "value" : "10",
      "constraint" : {
        "type" : "String",
        "editable" : true,
        "required" : false,
        "sensitive" : false,
        "valid_type" : "None",
        "valid_range" : [ ]
      }
    } ],
    "parameters_customization" : true,
    "inputs" : [ {
      "name" : "data_url",
      "description" : "data source."
    } ],
    "outputs" : [ {
      "name" : "train_url",
      "description" : "model output."
    } ],
    "engine" : {
      "engine_name" : "PyTorch",
      "engine_version" : "PyTorch-1.3.0-python3.6"
    }
  }
}

Example Responses

Status code: 201

{
  "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" : { }
}