#!/usr/bin/env python
#
# file: qmllab/__init__.py
#
# revision history:
#  20260810 (am): initial version for workshop lab 02
#
# qmllab -- helpers for Lab 02 of the Quantum Machine Learning Workshop.
#
# Session 3 described two ways to do quantum machine learning:
#
#   path a  a quantum kernel feeding a classical svm
#   path b  a variational circuit that trains its own parameters
#
# This package builds both, runs them on a simulator or a real qpu, and
# shows how much the encoding decides.
#
# The notebook keeps the ideas visible and imports only the plumbing:
#
#   from qmllab import data, kernels, models, plotting, experiments
#
#   X_tr, X_te, y_tr, y_te, _ = data.prepare("two_moons")
#   K = kernels.exact_kernel(X_tr)
#   res = models.qsvm(X_tr, y_tr, X_te, y_te)
#   print(res["test_acc"])
#------------------------------------------------------------------------------

# import qmllab modules
#
from . import backends, data, experiments, kernels, models, plotting

#------------------------------------------------------------------------------
#
# global variables are listed here
#
#------------------------------------------------------------------------------

# define the public api
#
__all__ = ["data", "kernels", "models", "backends", "plotting",
           "experiments"]

# the package version
#
__version__ = "1.1.0"

#
# end of file