abacusai.custom_loss_function
Classes
Code source for python-based custom feature groups and models |
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Custom Loss Function |
Module Contents
- class abacusai.custom_loss_function.CodeSource(client, sourceType=None, sourceCode=None, applicationConnectorId=None, applicationConnectorInfo=None, packageRequirements=None, status=None, error=None, publishingMsg=None, moduleDependencies=None)
Bases:
abacusai.return_class.AbstractApiClassCode source for python-based custom feature groups and models
- Parameters:
client (ApiClient) – An authenticated API Client instance
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
- __repr__()
Return repr(self).
- to_dict()
Get a dict representation of the parameters in this class
- Returns:
The dict value representation of the class parameters
- Return type:
- import_as_cell()
Adds the source code as an unexecuted cell in the notebook.
- class abacusai.custom_loss_function.AbstractApiClass(client, id)
- __eq__(other)
Return self==value.
- _get_attribute_as_dict(attribute)
- class abacusai.custom_loss_function.CustomLossFunction(client, notebookId=None, name=None, createdAt=None, lossFunctionName=None, lossFunctionType=None, codeSource={})
Bases:
abacusai.return_class.AbstractApiClassCustom Loss Function
- Parameters:
client (ApiClient) – An authenticated API Client instance
notebookId (str) – The unique identifier of the notebook used to create/edit the loss function.
name (str) – Name assigned to the custom loss function.
createdAt (str) – When the loss function was created.
lossFunctionName (str) – The name of the function defined in the source code.
lossFunctionType (str) – The category of problems that this loss would be applicable to, e.g. regression, multi-label classification, etc.
codeSource (CodeSource) – Information about the source code of the loss function.
- __repr__()
Return repr(self).