prevision_quantum_nn

prevision_quantum_nn module

Subpackages

Package Contents

Functions

get_model(params)

Get a model according to parameters.

get_application(application_type, prefix='qnn', preprocessing_params=None, model_params=None, postprocessing_params=None, rl_learner_type='quantum')

Get application.

load_application(application_params, model_weights, preprocessor_file)

loads application from files

get_dataset_from_numpy(train_features, train_labels, val_features=None, val_labels=None)

get dataset from numpy

get_dataset_from_pandas(train_data_frame, targets, val_data_frame=None)

get dataset from pandas

parse_results(results_file)

Parse a result file in order to extract parameters.

plot_losses(results, prefix='qnn')

Plot the losses of an application.

plot_metric(results, prefix='qnn')

Plot the relevant metric of an application.

plot_reward(results, prefix='qnn')

Plot the reward of a RL application.
prevision_quantum_nn.__version__ = 1.0.2
prevision_quantum_nn.get_model(params)

Get a model according to parameters.

Parameters

params (dictionnary) – parameters of the model

Returns

QuantumNeuralNetwork

model to be constructed with these parameters

Return type

model

prevision_quantum_nn.get_application(application_type, prefix='qnn', preprocessing_params=None, model_params=None, postprocessing_params=None, rl_learner_type='quantum')

Get application.

Parameters

application_type (str) – application type can be 1. classification 2. multiclassification 3. regression 4. reinforcement_learning

Returns

Application

application according to application type

Return type

application

prevision_quantum_nn.load_application(application_params, model_weights, preprocessor_file)

loads application from files

prevision_quantum_nn.get_dataset_from_numpy(train_features, train_labels, val_features=None, val_labels=None)

get dataset from numpy

prevision_quantum_nn.get_dataset_from_pandas(train_data_frame, targets, val_data_frame=None)

get dataset from pandas

prevision_quantum_nn.parse_results(results_file)

Parse a result file in order to extract parameters.

Parameters

results_file (string) – path to a log file of an application

Returns

Pandas dataframe

dataframe containing parameters to be plotted.

Return type

results

prevision_quantum_nn.plot_losses(results, prefix='qnn')

Plot the losses of an application.

Parameters

  • results (Pandas dataframe) – dataframe containing the losses

  • prefix (string) – part of the name given to the generated plot

prevision_quantum_nn.plot_metric(results, prefix='qnn')

Plot the relevant metric of an application.

Parameters

  • results (Pandas dataframe) – dataframe containing the metrics

  • prefix (string) – part of the name given to the generated plot

prevision_quantum_nn.plot_reward(results, prefix='qnn')

Plot the reward of a RL application.

Parameters

  • results (Pandas dataframe) – dataframe containing the rewards

  • prefix (string) – part of the name given to the generated plot