def __init__(self, epsilon, datapath):
self.util = utils.Util(datapath)
self.epsilon = epsilon
self.recommended_song_ids = []
self.cumulative_regret = 0
#self.recommend_song()
self.recommended_song_candidate = 0
def __init__(self, alpha, datapath):
self.util = utils.Util(datapath)
self.song_features = self.util.get_features_and_times()
self.d = self.song_features.shape[0]
self.K = self.song_features.shape[1] # length of feature vector
self.alpha = alpha
self.A = np.zeros((self.d, self.K, self.K))
for i in range(self.d):
self.A[i] = np.identity(self.K)
self.b = np.zeros((self.d, self.K))
self.theta_hat = np.zeros(self.K)
self.choosen_song_index = 0 # random initial value
self.p = np.zeros(self.d)
self.norms = []
self.ratings = []
self.choices = []
self.rewards = []
self.epsilon = 0.2
import tensorflow as tf
import numpy as np
import os
import RNN_AE_model_decoder_feedback as rnn_AE
import utils
import csv
import time
with open("nowtime.txt", 'r') as f: # nowtime.txt가 파일의 경로
savepath = f.read()
sv_datetime = savepath
util = utils.Util()
MIN_SONG_LENGTH = 35
ms = time.strftime('_%H%M%S', time.localtime(time.time()))
filename = sv_datetime
filename = filename + ms
def test(trained_data, len_data, mode): # trained_data = song_pitches or song_durations, len_data = MIN_SONG_LENGTH, # mode = pitch or duration
# Test the RNN model
char2idx = util.getchar2idx(mode=mode)
enc_model = rnn_AE.LSTMAutoEnc(sequence_length=len_data,
batch_size=len(trained_data),
mode='test')
dec_model = rnn_AE.LSTMAutoEnc(sequence_length=160,
batch_size=1,
mode='test')
enc_out_state = enc_model.encoder(scopename=mode)
dec_model.decoder(scopename=mode)
from random import choice
from string import ascii_uppercase
import telebot
import db
import utils
from flask import Flask, request, session, redirect, url_for, render_template
bot = telebot.TeleBot(os.environ['API_TIKEN'], threaded=False)
server = Flask(__name__)
server.secret_key = os.urandom(24)
menu = {"shop": "Магазин", "basket": "Корзина"}
ut = utils.Util(bot, db)
def get_menu():
keyboard = telebot.types.InlineKeyboardMarkup()
for key in menu.keys():
keyboard.add(
telebot.types.InlineKeyboardButton(text=menu[key],
callback_data=key))
return keyboard
def cat_list(tag, prod=None):
keyboard = telebot.types.InlineKeyboardMarkup()
for cat in db.Category.select():
if prod is not None:
def __init__(self, datapath):
self.epsilon = epsilon
self.recommended_song_ids = []
self.util = utils.Util(datapath)
self.recommended_song_candidate = 0