"""
Module description:
"""
__version__ = '0.3.1'
__author__ = 'Vito Walter Anelli, Claudio Pomo'
__email__ = 'vitowalter.anelli@poliba.it, claudio.pomo@poliba.it'
import numpy as np
[docs]class Sampler:
def __init__(self, indexed_ratings, sp_i_train):
np.random.seed(42)
self._indexed_ratings = indexed_ratings
self._sp_i_train = sp_i_train
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()}
[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
lui_dict = self._lui_dict
def sample():
u = r_int(n_users)
ui = ui_dict[u]
lui = lui_dict[u]
if lui == n_items:
sample()
i = ui[r_int(lui)]
j = r_int(n_items)
while j in ui:
j = r_int(n_items)
return u, i, j, self._sp_i_train[u].toarray()[0]
for batch_start in range(0, events, batch_size):
bui, bii, bij, bpos = map(np.array, zip(*[sample() for _ in range(batch_start, min(batch_start + batch_size, events))]))
yield bui[:, None], bii[:, None], bij[:, None], bpos[:, None]