Deleting
Machine Learning object deletion.
Once an entity is saved to the ML Registry following the instructions outlined
here, it is available for use by other users. However,
the storage of these models may result in errors or may not need to be persisted
for all time. As such, the kxi.ml.registry.delete
class provides a user with the
ability to remove models, parameters, metrics etc from an ML Registry. All functionality
within this class is described below.
kxi.ml.registry.delete.registry
Delete a registry.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
folder_path |
Union[str, dict] |
Either a string containing the folder path denoting location of the registry,
or a dictionary specifying the vendor (as key) and the path (as value),
e.g. |
None |
config |
dict |
Either a registry configuration as dictionary, or |
None |
Examples:
Delete the registry:
>>> from kxi import ml
>>> ml.init()
>>> ml.registry.delete.registry(folder_path="/tmp")
kxi.ml.registry.delete.experiment
Delete an experiment within the specified registry.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
folder_path |
Union[str, dict] |
Either a string containing the folder path denoting where to delete the
experiment, or a dictionary specifying the vendor (as key) and the path
(as value), e.g. |
None |
experiment_name |
str |
The name of the experiment. |
None |
Examples:
Delete an experiment from the registry:
>>> from kxi import ml
>>> ml.init()
>>> ml.registry.delete.experiment(folder_path="/tmp", experiment_name="day0")
kxi.ml.registry.delete.model
Delete a model within the specified registry.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
folder_path |
Union[str, dict] |
Either a string containing the folder path denoting where to delete the
model, or a dictionary specifying the vendor (as key) and the path
(as value), e.g. |
None |
experiment_name |
str |
Either the name of the experiment under which the model resides as a
string, or |
None |
model_name |
str |
Either the name of model to be deleted as a string, or |
None |
version |
List[int] |
A list of the major and minor versions of the model - [major, minor]. If
|
None |
Returns:
Type | Description |
---|---|
Optional[uuid.UUID] |
Unique ID of given model or |
Examples:
Delete a model from the registry:
>>> from kxi import ml
>>> ml.init()
>>> ml.registry.delete.model(folder_path="/tmp",
experiment_name="day0",
model_name="linear_regression")
kxi.ml.registry.delete.code
Delete a code file associated with a specific model.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
code_file |
str |
The name of the code file to be deleted. |
required |
folder_path |
Union[str, dict] |
Either a string containing the folder path denoting where to delete the
code, or a dictionary specifying the vendor (as key) and the path
(as value), e.g. |
None |
experiment_name |
str |
The name of the experiment under which the code resides. |
None |
model_name |
str |
The name of model whose code is to be deleted. If |
None |
version |
List[int] |
The version of model whose code is to be deleted as a length two list
of integers indicating the major and minor versions. If |
None |
Examples:
Delete a code file from a model in the registry:
>>> from kxi import ml
>>> ml.init()
>>> ml.registry.delete.code(code_file="prerequisites.py",
folder_path="/tmp",
experiment_name="day0",
model_name="complex_model")
kxi.ml.registry.delete.parameters
Delete a parameter file associated with a specific model.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
param_file |
str |
A string giving the name of the parameter file to be deleted. |
required |
folder_path |
Union[str, dict] |
Either a string containing the folder path denoting where to delete the
parameters, or a dictionary specifying the vendor (as key) and the path
(as value), e.g. |
None |
experiment_name |
str |
The name of the experiment under which the parameter file resides. |
None |
model_name |
str |
The name of model whose parameters are to be deleted. If |
None |
version |
List[int] |
The version of model whose parameters are to be deleted as a length two
list of integers indicating the major and minor versions. If |
None |
Examples:
Delete a parameter file from a model in the registry:
>>> from kxi import ml
>>> ml.init()
>>> ml.registry.delete.parameters(param_file="alpha.json",
folder_path="/tmp",
experiment_name="day0",
model_name="logistic_regression")
kxi.ml.registry.delete.metrics
Delete metrics table associated with a specific model.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
folder_path |
Union[str, dict] |
Either a string containing the folder path denoting the registry from
which to delete the metrics, or a dictionary specifying the vendor
(as key) and the path (as value), e.g.
|
None |
experiment_name |
str |
The name of the experiment under which the metrics table resides. |
None |
model_name |
str |
The name of model whose metrics are to be deleted. If |
None |
version |
List[int] |
The version of model whose metrics are to be deleted as a length two
list of integers indicating the major and minor versions. If |
None |
Examples:
Delete all metrics from a model in the registry:
>>> from kxi import ml
>>> ml.init()
>>> ml.registry.delete.metrics(folder_path="/tmp",
experiment_name="day0",
model_name="linear_regression")
kxi.ml.registry.delete.metric
Delete metric associated with a specific model.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
metric_name |
str |
The name of the metric to be deleted. |
required |
folder_path |
Union[str, dict] |
Either a string containing the folder path denoting the registry from
which to delete the metric, or a dictionary specifying the vendor
(as key) and the path (as value), e.g.
|
None |
experiment_name |
str |
The name of the experiment under which the metric resides. |
None |
model_name |
str |
The name of model whose metric is to be deleted. If |
None |
version |
List[int] |
The version of model whose metric is to be deleted as a length two
list of integers indicating the major and minor versions. If |
None |
Examples:
Delete a metric from a model in the registry:
>>> from kxi import ml
>>> ml.init()
>>> ml.registry.delete.metric(metric_name="mse",
folder_path="/tmp",
experiment_name="day0",
model_name="linear_regression")