bicepjai

bicepjai

import sys
import os
import re
import gc
import traceback
import tqdm
import mmap
import datetime as dt

bicepjai

def train_dcgan(generator_func, discriminator_func, data_in, model_weights_name_prefix, load_model=False, 
              epochs=10, batch_size=32, lr_opt=1e-3, lr_d_opt=1e-4, plot_epoch=None):
    
    # get image shape
    image_shape = data_in[0,:,:,:].shape
    print("image shape:",image_shape)
    
    K.clear_session()
    # use generator and discriminator functions and make gan model

bicepjai

sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt update

sudo apt-get install gdebi-core

sudo add-apt-repository ppa:openrazer/stable
sudo add-apt-repository ppa:lah7/polychromatic
sudo apt update

bicepjai

import tensorflow.contrib.keras as keras
import tensorflow as tf

from keras.engine import Layer, InputSpec
from keras import regularizers, initializers, constraints
from keras import backend as K

class AttentionWithContext(Layer):

bicepjai

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bicepjai

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bicepjai

import java.util.*;

public class simplesa {
    private final String[] suffixes;
    private final int N;
		private int[] sa,lcp,nofsubs,nofusubs,nofusubs_acc;
		
    public simplesa(String s) {
        N = s.length();
        suffixes = new String[N];

bicepjai

import java.lang.String;
import java.util.Scanner;

public class Main{
	public static String str;
	public static int len;
	public static int[] SA,lcp,subsAcc;
	
  // length of longest common prefix of s and t
   private static int lcp(int s, int t) {

bicepjai

import java.util.*;

public class ss {
  public static int stacktrack;
	public char TERMINATORS_RANGE = '\ud800';
	public static int count=0;
	public static void dfsd(Node c){
		if (c.isLeaf()){
			//System.out.println("\nbasecase");
			//count++;