Help Center/ ModelArts/ Workflows/ How to Develop a Workflow?/ Phase Type/ Model Registration Phase/ Parameter Overview

Updated on 2024-08-14 GMT+08:00

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Parameter Overview

You can use ModelStep to create a model registration phase. The following is an example of defining a ModelStep.

**Table 1** **ModelStep**
Parameter	Description	Mandatory	Data Type
name	Name of a model registration phase. The name contains a maximum of 64 characters, including only letters, digits, underscores (_), and hyphens (-). It must start with a letter and must be unique in a workflow.	Yes	str
inputs	Inputs of the model registration phase	No	ModelInput or ModelInput list
outputs	Outputs of the model registration phase	Yes	ModelOutput or ModelOutput list
title	Title for frontend display	No	str
description	Description of the model registration phase	No	str
policy	Phase execution policy	No	StepPolicy
depend_steps	Dependency phases	No	Step or step list

**Table 2** **ModelInput**
Parameter	Description	Mandatory	Data Type
name	Input name of the model registration phase. The name can contain a maximum of 64 characters, including only letters, digits, underscores (_), and hyphens (-), and must start with a letter. The input name of a step must be unique.	Yes	str
data	Input data object of the model registration phase	Yes	OBS, SWR, or subscribed model object. Currently, only OBSPath, SWRImage, OBSConsumption, OBSPlaceholder, SWRImagePlaceholder, DataConsumptionSelector, and GalleryModel are supported.

**Table 3** **ModelOutput**
Parameter	Description	Mandatory	Data Type
name	Output name of the model registration phase. The name can contain a maximum of 64 characters, including only letters, digits, underscores (_), and hyphens (-), and must start with a letter. The output name of a step must be unique.	Yes	str
model_config	Configurations for model registration	Yes	ModelConfig

**Table 4** **ModelConfig**
Parameter	Description	Mandatory	Data Type
model_type	Model type. Supported types: TensorFlow, MXNet, Caffe, Spark_MLlib, Scikit_Learn, XGBoost, Image, PyTorch, Template, and Custom. The default value is TensorFlow.	Yes	str
model_name	Model name. Enter 1 to 64 characters. Only letters, digits, hyphens (-), and underscores (_) are allowed.	No	str, Placeholder
model_version	Model version in the format of Digit.Digit.Digit. The value range of the digits is [1, 99]. If this parameter is left blank, the version number automatically increases. CAUTION: No part of the version number can start with 0. For example, 01.01.01 is not allowed.	No	str, Placeholder
runtime	Model runtime environment. The options of runtime are the same as those of model_type.	No	str, Placeholder
description	Model description that consists of 1 to 100 characters. The following special characters cannot be contained: &!'"<>=	No	str
execution_code	OBS path for storing the execution code. By default, this parameter is left blank. The name of the execution code file is fixed to customize_service.py. The inference code file must be stored in the model directory. This parameter is left blank. The system can automatically identify the inference code in the model directory.	No	str
dependencies	Package required for the inference code and model. By default, this parameter is left blank. It is read from the configuration file.	No	str
model_metrics	Model precision, which is read from the configuration file	No	str
apis	All apis input and output parameters of a model (optional), which are parsed from the configuration file	No	str
initial_config	Model configuration information	No	dict
template	Template configuration items. This parameter is mandatory when model_type is set to Template.	No	Template
dynamic_load_mode	Dynamic loading mode. Currently, only Single is supported.	No	str, Placeholder
prebuild	Whether the model is prebuilt. The default value is False.	No	bool, Placeholder
install_type	Model installation type. The value can be real_time, edge, batch. If this parameter is left blank, all types are supported by default.	No	list[str]

**Table 5** **Template**
Parameter	Description	Mandatory	Data Type
template_id	ID of the used template. The template has a built-in input and output mode.	Yes	str, Placeholder
infer_format	Input and output mode ID. When this parameter is used, the input and output mode built in the template does not take effect.	No	str, Placeholder
template_inputs	Template input configuration, specifying the source path for configuring a model	Yes	list of TemplateInputs object

**Table 6** **TemplateInputs**
Parameter	Description	Mandatory	Data Type
input_id	Input item ID, which is obtained from the template details	Yes	str, Placeholder
input	Template input path, which can be an OBS file path or OBS directory path. When you use a template with multiple input items to create a model, if the target paths input_properties specified in the template are the same, the OBS directory or OBS file name entered here must be unique to prevent files from being overwritten.	Yes	str, Placeholder, Storage

Parent topic: Model Registration Phase

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