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