modules.core.Core

class Core(name: str = None)

Bases: ABC

Core Module for QUARK, used by all other Modules that are part of a benchmark process.

__init__(name: str = None)

Constructor method.

Parameters:: name -- Name used to identify this QUARK module. If not specified class name will be used as default.

Methods

`__init__`([name])	Constructor method.
`get_available_submodule_options`()	Gets the list of available options.
`get_available_submodules`(option)	If the module has submodules depending on certain options, this method should adjust the submodule_options accordingly.
`get_default_submodule`(option)	Given an option string by the user, this returns a submodule.
`get_depending_parameters`(option, config)	If the module has parameters depending on certain options, this method should return the parameters for the given option.
`get_parameter_options`()	Returns the parameters for a given module.
`get_requirements`()	Returns the required pip packages for this module.
`get_submodule`(option)	Submodule is instantiated according to the information given in self.sub_options.
`postprocess`(input_data, config, **kwargs)	Essential Method for the benchmarking process.
`preprocess`(input_data, config, **kwargs)	Essential method for the benchmarking process.

final get_available_submodule_options() → list

Gets the list of available options.

Returns:: List of module options

get_available_submodules(option: list) → list

If the module has submodules depending on certain options, this method should adjust the submodule_options accordingly.

Parameters:: option -- List of chosen options
Returns:: List of available submodules

abstract get_default_submodule(option: str) → Core

Given an option string by the user, this returns a submodule.

Parameters:: option -- String with the chosen submodule
Returns:: Module of type Core

get_depending_parameters(option: str, config: dict) → dict

If the module has parameters depending on certain options, this method should return the parameters for the given option.

Parameters:

option -- The chosen option
config -- Current config dictionary

Returns:

The parameters for the given option

abstract get_parameter_options() → dict

Returns the parameters for a given module.

Should always be in this format:

{
   "parameter_name":{
      "values":[1, 2, 3],
      "description":"How many nodes do you need?"
   },
    "parameter_name_2":{
      "values":["x", "y"],
      "description":"Which type of problem do you want?"
   }
}

Returns:: Available settings for this application

static get_requirements() → list

Returns the required pip packages for this module. Optionally, version requirements can be added.

Returns:: List of dictionaries

final get_submodule(option: str) → Core

Submodule is instantiated according to the information given in self.sub_options. If self.sub_options is None, get_default_submodule is called as a fallback.

Parameters:: option -- String with the options
Returns:: Instance of a module

postprocess(input_data: any, config: dict, **kwargs) → tuple[any, float]

Essential Method for the benchmarking process. Is always executed after the submodule is finished. The data by this method is passed up to the parent module.

Parameters:

input_data -- Input data comes from the submodule if that exists
config -- Config for the module
kwargs -- Optional keyword arguments

Returns:

The output of the postprocessing and the time it took to postprocess

preprocess(input_data: any, config: dict, **kwargs) → tuple[any, float]

Essential method for the benchmarking process. This is always executed before traversing down to the next module, passing the data returned by this function.

Parameters:

input_data -- Data for the module, comes from the parent module if that exists
config -- Config for the module
kwargs -- Optional keyword arguments

Returns:

The output of the preprocessing and the time it took to preprocess