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alfabeto = "ABCDEFGHIJKLMNÑOPQRSTUVWXYZ"
message = "GUVQA EQORN GVCOG PVGUG IWTQF GSWGG NRTKO GTCNW OPQSWGFGUE KHTGG UVGOG PUCLG ANQRW DNKSW GGPGN HQTQF GNCCUKIPCV WTCVG PFTCO CURWP VQUGP UWPQV C"
message = message.replace(" ", "")

def count_occurrences(message, letter):
    res = 0
    for i in message:
        if i == letter:
            res += 1
    return (res)

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#include <stdio.h>
#include <stdlib.h>
#include <unistd.h>

int ft_strlen(char *str)
{
	int i;

	i = 0;
	while (*str != '\0')

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print(model.evaluate(X_test, y_test, verbose = 2))

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for i in range(0, 10):
  X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size = 0.2)
  model.fit(X_train, y_train, batch_size = 5, epochs = 5)

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"""
Created on Wed Mar 18 17:55:11 2020
@author: alexr
"""


import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Activation, Dense, Flatten, MaxPool2D, Conv2D, Dropout
from sklearn.model_selection import train_test_split

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"""
Created on Tue Mar 17 21:28:15 2020
@author: alexr
"""


import matplotlib.pyplot as plt
import os
import cv2
import random

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#Creditos: parulnith https://gist.github.com/parulnith

#Importamos todas las librerias necesarias
import librosa
import librosa.display
import matplotlib.pyplot as plt
import os
import pathlib

cmap = plt.get_cmap('inferno')