modules.applications.qml.data_handler.DataHandler

class DataHandler

Bases: ABC

Abstract base class for DataHandler. This class defines the necessary methods that both supervised and unsupervised QML applciations must implement.

__init__()

Methods

__init__()

data_load(gen_mod, config)

Helps to ensure that the model can effectively learn the underlying patterns and structure of the data, and produce high-quality outputs.

evaluate(solution)

Computes the best loss values.

tb_to_pd(logdir, rep)

Converts TensorBoard event files in the specified log directory into a pandas DataFrame and saves it as a pickle file.
abstract data_load(gen_mod: dict, config: dict) → tuple[any, float]

Helps to ensure that the model can effectively learn the underlying patterns and structure of the data, and produce high-quality outputs.

Parameters:

  • gen_mod -- Dictionary with collected information of the previous modules

  • config -- Config specifying the parameters of the data handler

Returns:

Mapped problem and the time it took to create the mapping

abstract evaluate(solution: any) → tuple[any, float]

Computes the best loss values.

Parameters:

solution -- Solution data

Returns:

Evaluation data and the time it took to create it

static tb_to_pd(logdir: str, rep: str) → None

Converts TensorBoard event files in the specified log directory into a pandas DataFrame and saves it as a pickle file.

Parameters:

  • logdir -- Path to the log directory containing TensorBoard event files

  • rep -- Repetition counter