legendre_decomp.module_mba
==========================

.. py:module:: legendre_decomp.module_mba

.. autoapi-nested-parse::

   CUDA-enabled LegendreDecomposition calculations



Functions
---------

.. autoapisummary::

   legendre_decomp.module_mba.xp_get
   legendre_decomp.module_mba.kl
   legendre_decomp.module_mba.get_eta
   legendre_decomp.module_mba.get_h
   legendre_decomp.module_mba.get_q
   legendre_decomp.module_mba.get_slice
   legendre_decomp.module_mba.initialize_theta
   legendre_decomp.module_mba.compute_G
   legendre_decomp.module_mba.LD_MBA
   legendre_decomp.module_mba.get_weight
   legendre_decomp.module_mba.compute_nbody
   legendre_decomp.module_mba.recons_nbody


Module Contents
---------------

.. py:function:: xp_get(val)

.. py:function:: kl(P, Q, xp = cp)

   Kullback-Leibler divergence.

   :param P: P tensor
   :param Q: Q tensor
   :param xp: Array module, either numpy (CPU) or cupy
   :type xp: ModuleType

   :returns: KL divergence.


.. py:function:: get_eta(Q, D, xp = cp)

   Eta tensor.

   :param Q: Q tensor
   :param D: Dimensionality
   :param xp: Array module, either numpy (CPU) or cupy
   :type xp: ModuleType

   :returns: Eta tensor.


.. py:function:: get_h(theta, D, xp = cp)

   H tensor.

   :param theta: Theta tensor
   :param D: Dimensionality
   :param xp: Array module, either numpy (CPU) or cupy
   :type xp: ModuleType

   :returns: Updated theta.


.. py:function:: get_q(h, gpu=True, xp = cp)

   Q tensor.

   :param H: H tensor

   :returns: Updated Q.


.. py:function:: get_slice(key, D)

.. py:function:: initialize_theta(keys, shape, theta0_flag=False, xp = cp)

.. py:function:: compute_G(eta, mask, xp = cp)

.. py:function:: LD_MBA(X, I = None, order = 2, n_iter = 100, lr = 1.0, eps = 1e-05, error_tol = 1e-05, init_theta = None, init_theta_mask = None, ngd = True, ngd_lstsq=True, verbose = True, gpu = True, dtype = None)

   Compute many-body tensor approximation.

   :param X: Input tensor.
   :param I: A list of pairs of indices that represent slices with nonzero elements in the parameter tensor.
             e.g. [(0,1),(2,),(1,3)]
   :param n_iter: Maximum number of iteration.
   :param lr: Learning rate.
   :param eps: (see paper).
   :param error_tol: KL divergence tolerance for the iteration.
   :param ngd: Use natural gradient.
   :param verbose: Print debug messages.

   :returns: KL divergence history.
             scaleX: Scaled X tensor.
             Q: Q tensor.
             theta: Theta.
   :rtype: all_history_kl


.. py:function:: get_weight(shape, I_x=None, order=2, xp = cp)

.. py:function:: compute_nbody(theta, shape, I_x=None, order=2, dtype=None, gpu=True, verbose=False)

.. py:function:: recons_nbody(X_out, D, rescale=True, dtype=None, gpu=True)