API Reference

afs.models module

class afs.models.models(target_endpoint=None, instance_id=None, auth_code=None, token=None)

Bases: afs.get_env.AfsEnv

create_model_repo(model_repository_name)

Create a new model repository. (Support v2 API)

Parameters:model_repository_name (str) – (optional)The name of model repository. Returns:the new uuid of the repository

decrypt_model(model, decrypt_key)

Decrypt model.

Parameters:

• model (object) – the object of model
• decrypt_key (str) – use decrypt_key to decrypt the model

Returns:

object

delete_model(model_name, model_repository_name=None)

Delete model.

Parameters:

• model_name – model name.
• model_repository_name – model repository name.

Returns:

bool

delete_model_repository(model_repository_name)

Delete model repository.

Parameters:model_repository_name – model repository name. Returns:bool

download_model(save_path, model_repository_name=None, model_name=None, last_one=False)

Download model from model repository to a file.

Parameters:

• model_repository_name (str) – The model name exists in the model repository
• save_path (str) – The path exist in the file system
• model_name (str) – Get the specific model file from the model reposiotry, if getting last one value for None.
• last_one (str) – Get the last uploading model from the model repository.

get_latest_model_info(model_repository_name=None)

Get the latest model info, including created_at, tags, evaluation_result. (Support v2 API)

Parameters:model_repository_name – (optional)The name of model repository. Returns:dict. the latest of model info in model repository.

get_model_id(model_name=None, model_repository_name=None, last_one=True)

Get model id by model name.

Parameters:

• model_name (str) – model name. No need if last_one is true.
• model_repository_name (str) – model respository name where the model is.
• last_one (bool) – auto get the model_repository last one model

Returns:

str model id

get_model_info(model_name, model_repository_name=None)

Get model info, including created_at, tags, evaluation_result. (V2 API)

Parameters:

• model_name – model name
• model_repository_name – The name of model repository.

Returns:

dict model info

get_model_repo_id(model_repository_name=None)

Get model repository by name.

Parameters:model_repository_name (str) – Returns:str model repository id

set_blob_credential(blob_endpoint, encode_blob_accessKey, encode_blob_secretKey, blob_record_id, bucket_name)

Set blob credential when upload the big model.

Parameters:

• blob_endpoint (str) – blob endpoint
• encode_blob_accessKey (str) – blob accessKey encode with base64
• encode_blob_secretKey (str) – blob secretKey encode with base64
• blob_record_id (str) – MD5 with instance_id + ‘_’ + accessKey
• bucket_name (str) – blob bucket name

upload_model(model_path, accuracy=None, loss=None, tags={}, extra_evaluation={}, feature_importance=None, coefficient=None, model_repository_name=None, model_name=None, encrypt_key='')

Upload model to model repository. (Support v2 API)

Parameters:

• model_path (str) – (required) model filepath
• accuracy (float) – (optional) model accuracy value, between 0-1
• loss (float) – (optional) model loss value
• tags (dict) – (optional) tag from model
• extra_evaluation (dict) – (optional) other evaluation from model
• model_name (str) – (optional) Give model a name or a default name
• model_repository_name (str) – (optional) model_repository_name
• feature_importance (list) – (optional) feature_importance is the record how the features important in the model
• coefficient (list) – (optional) coefficient indicates the direction of the relationship between a predictor variable and the response
• encrypt_key (str) – (optional) If there is a encrypt_key, use the encrypt_key to encrypt the model

Returns:

dict. the information of the upload model.