Parameters

Placeholder docstring

class sagemaker.parameter.ParameterRange(min_value, max_value, scaling_type='Auto')

Bases: object

Base class for representing parameter ranges. This is used to define what hyperparameters to tune for an Amazon SageMaker hyperparameter tuning job and to verify hyperparameters for Marketplace Algorithms.

Initialize a parameter range.

Parameters

• min_value (float or int) – The minimum value for the range.

• max_value (float or int) – The maximum value for the range.

• scaling_type (str) – The scale used for searching the range during tuning (default: ‘Auto’). Valid values: ‘Auto’, ‘Linear’, ‘Logarithmic’ and ‘ReverseLogarithmic’.

is_valid(value)

Determine if a value is valid within this ParameterRange.

Parameters

value (float or int) – The value to be verified.

Returns

True if valid, False otherwise.

Return type

bool

classmethod cast_to_type(value)

Parameters

value –

as_tuning_range(name)

Represent the parameter range as a dicionary suitable for a request to create an Amazon SageMaker hyperparameter tuning job.

Parameters

name (str) – The name of the hyperparameter.

Returns

A dictionary that contains the name and values of the hyperparameter.

Return type

dict[str, str]

class sagemaker.parameter.ContinuousParameter(min_value, max_value, scaling_type='Auto')

Bases: sagemaker.parameter.ParameterRange

A class for representing hyperparameters that have a continuous range of possible values.

Parameters

• min_value (float) – The minimum value for the range.

• max_value (float) – The maximum value for the range.

Initialize a parameter range.

Parameters

• min_value (float or int) – The minimum value for the range.

• max_value (float or int) – The maximum value for the range.

• scaling_type (str) – The scale used for searching the range during tuning (default: ‘Auto’). Valid values: ‘Auto’, ‘Linear’, ‘Logarithmic’ and ‘ReverseLogarithmic’.

classmethod cast_to_type(value)

Parameters

value –

class sagemaker.parameter.CategoricalParameter(values)

Bases: sagemaker.parameter.ParameterRange

A class for representing hyperparameters that have a discrete list of possible values.

Initialize a CategoricalParameter.

Parameters

values (list or object) – The possible values for the hyperparameter. This input will be converted into a list of strings.

as_tuning_range(name)

Represent the parameter range as a dicionary suitable for a request to create an Amazon SageMaker hyperparameter tuning job.

Parameters

name (str) – The name of the hyperparameter.

Returns

A dictionary that contains the name and values of the hyperparameter.

Return type

dict[str, list[str]]

as_json_range(name)

Represent the parameter range as a dictionary suitable for a request to create an Amazon SageMaker hyperparameter tuning job using one of the deep learning frameworks.

The deep learning framework images require that hyperparameters be serialized as JSON.

Parameters

name (str) – The name of the hyperparameter.

Returns

A dictionary that contains the name and values of the hyperparameter, where the values are serialized as JSON.

Return type

dict[str, list[str]]

is_valid(value)

Parameters

value –

classmethod cast_to_type(value)

Parameters

value –

class sagemaker.parameter.IntegerParameter(min_value, max_value, scaling_type='Auto')

Bases: sagemaker.parameter.ParameterRange

A class for representing hyperparameters that have an integer range of possible values. :param min_value: The minimum value for the range. :type min_value: int :param max_value: The maximum value for the range. :type max_value: int

Initialize a parameter range.

Parameters

• min_value (float or int) – The minimum value for the range.

• max_value (float or int) – The maximum value for the range.

• scaling_type (str) – The scale used for searching the range during tuning (default: ‘Auto’). Valid values: ‘Auto’, ‘Linear’, ‘Logarithmic’ and ‘ReverseLogarithmic’.

classmethod cast_to_type(value)

Parameters

value –