Source code for elliot.dataset.samplers.pointwise_cfgan_sampler

"""
Module description:

"""

__version__ = '0.3.1'
__author__ = 'Felice Antonio Merra, Vito Walter Anelli, Claudio Pomo'
__email__ = 'felice.merra@poliba.it, vitowalter.anelli@poliba.it, claudio.pomo@poliba.it'

import numpy as np


[docs]class Sampler: def __init__(self, indexed_ratings, sp_i_train, s_zr, s_pm): np.random.seed(42) self._indexed_ratings = indexed_ratings self._users = list(self._indexed_ratings.keys()) self._nusers = len(self._users) self._items = list({k for a in self._indexed_ratings.values() for k in a.keys()}) self._nitems = len(self._items) self._ui_dict = {u: list(set(indexed_ratings[u])) for u in indexed_ratings} self._lui_dict = {u: len(v) for u, v in self._ui_dict.items()} self._s_zr = s_zr self._s_pm = s_pm self._sp_i_train = sp_i_train
[docs] def step(self, events: int, batch_size: int): r_int = np.random.randint n_users = self._nusers n_items = self._nitems ui_dict = self._ui_dict s_zr = self._s_zr s_pm = self._s_pm sp_i_train = self._sp_i_train def sample(C_u, N_zr, mask, n): u = r_int(n_users) ui = ui_dict[u] for i in ui: mask[n][i] = 1 for i in range(int(s_zr * n_items)): ng = r_int(n_items) while ng in ui_dict[u]: ng = r_int(n_items) N_zr[n][ng] = 1 for i in range(int(s_pm * n_items)): ng = r_int(n_items) while ng in ui_dict[u]: ng = r_int(n_items) mask[n][ng] = 1 C_u[n] = sp_i_train.getrow(u).toarray() for batch_start in range(0, events, batch_size): C_u, mask, N_zr = np.zeros((batch_size, n_items)), np.zeros((batch_size, n_items)), np.zeros( (batch_size, n_items)) for n, _ in enumerate(range(batch_start, min(batch_start + batch_size, events))): sample(C_u, N_zr, mask, n) # zip(*[sample(C_u, N_zr, mask, n) for n, _ in enumerate(range(batch_start, min(batch_start + batch_size, events)))]) yield C_u, mask, N_zr