Update a custom algorithm for the given algorithm name. If source code is provided, all function names for the source code must also be provided.
Arguments:
REQUIRED
KEY
TYPE
DESCRIPTION
Yes
algorithm
str
The name to identify the algorithm. Only uppercase letters, numbers, and underscores are allowed.
No
sourceCode
str
Contents of a valid Python source code file. The source code should contain the train/predict/predict_many/initialize functions. A list of allowed imports and system libraries for each language is specified in the user functions documentation section.
No
trainingDataParameterNamesMapping
dict
The mapping from feature group types to training data parameter names in the train function.
No
trainingConfigParameterName
str
The train config parameter name in the train function.
No
trainFunctionName
str
Name of the function found in the source code that will be executed to train the model. It is not executed when this function is run.
No
predictFunctionName
str
Name of the function found in the source code that will be executed to run predictions through the model. It is not executed when this function is run.
No
predictManyFunctionName
str
Name of the function found in the source code that will be executed for batch prediction of the model. It is not executed when this function is run.
No
initializeFunctionName
str
Name of the function found in the source code to initialize the trained model before using it to make predictions using the model.
No
configOptions
dict
Map dataset types and configs to train function parameter names.
No
isDefaultEnabled
bool
Whether to train with the algorithm by default.
No
useGpu
bool
Whether this algorithm needs to run on GPU.
No
packageRequirements
list
List of package requirement strings. For example: ['numpy==1.2.3', 'pandas>=1.4.0'].
Note: The arguments for the API methods follow camelCase but for Python SDK underscore_case is followed.
Response:
KEY
TYPE
DESCRIPTION
success
Boolean
true if the call succeeded, false if there was an error
result
Algorithm
KEY
TYPE
Description
name
str
The name of the algorithm
problemType
str
The type of the problem this algorithm will work on
createdAt
str
When the algorithm was created
updatedAt
str
When the algorithm was last updated
isDefaultEnabled
bool
Whether train with the algorithm by default
trainingInputMappings
dict
The mappings for train function parameters' names, e.g. names for training data, name for training config
trainFunctionName
str
Name of the function found in the source code that will be executed to train the model. It is not executed when this function is run.
predictFunctionName
str
Name of the function found in the source code that will be executed run predictions through model. It is not executed when this function is run.
predictManyFunctionName
str
Name of the function found in the source code that will be executed for batch prediction of the model. It is not executed when this function is run.
initializeFunctionName
str
Name of the function found in the source code to initialize the trained model before using it to make predictions using the model
configOptions
dict
Map dataset types and configs to train function parameter names
algorithmId
str
The unique identifier of the algorithm
useGpu
bool
Whether to use gpu for model training
algorithmTrainingConfig
dict
The algorithm specific training config
onlyOfflineDeployable
bool
Whether or not the algorithm is only allowed to be deployed offline
codeSource
CodeSource
Info about the source code of the algorithm
KEY
TYPE
Description
sourceType
str
The type of the source, one of TEXT, PYTHON, FILE_UPLOAD, or APPLICATION_CONNECTOR
sourceCode
str
If the type of the source is TEXT, the raw text of the function
applicationConnectorId
str
The Application Connector to fetch the code from
applicationConnectorInfo
str
Args passed to the application connector to fetch the code
packageRequirements
list
The pip package dependencies required to run the code
status
str
The status of the code and validations
error
str
If the status is failed, an error message describing what went wrong
publishingMsg
dict
Warnings in the source code
moduleDependencies
list
The list of internal modules dependencies required to run the code