zckkte

using System;
using System.Collections.Generic;
using System.Linq;

namespace FunctionalExtensions
{
    [Serializable]
    public abstract class ValueObject : IComparable, IComparable<ValueObject>
    {
        private int? _cachedHashCode;

zckkte

# export mysql database
mysqldump -u username -p database_name > data-dump.sql

# Check if a sql script is a legit sql dump file
 head -n 5 prodbck_anon_reduced.sql | grep dump ; echo $?

# import 

mysql -u root -p

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object Console {
  def putStrLn(str: => String) = TIO.effect(println(str))
}

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<?php


class BusinessResult
{
    public const SUCCESS = "success";

    public const FAIL = "fail";

    private string $result;

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function curry(fn) {
    return function curriedFn(...args) {
        if (fn.length !== args.length) {
            return curriedFn.bind(null, ...args);
        }
        return fn.apply(null, args);
    };
}

zckkte

-- \/\/\/ DO NOT MODIFY THE FOLLOWING LINES \/\/\/
  
module ReversiAI (State,author,nickname,initial,think) where

import Reversi
import Data.List
import Data.Map (fromList, (!))
import Data.Maybe

-- /\/\/\ DO NOT MODIFY THE PRECEDING LINES /\/\/\

zckkte

import os
import math
import random
import shutil 
import numpy as np
import matplotlib.pyplot as plt
from time import time
from functional import seq
from collections import namedtuple
import keras

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from keras.models import Model

layer_outputs = [layer.output for layer in model.layers] 
activation_model = Model(inputs=model.input, outputs=layer_outputs) 
activations = activation_model.predict(X_train[10].reshape(1,28,28,1))

def display_activation(activations, col_size, row_size, act_index):
  activation = activations[act_index]
  activation_index=0
  fig, ax = plt.subplots(row_size, col_size, figsize=(row_size*2.5,col_size*1.5)) 

zckkte

import keras
from keras import layers
from keras import optimizers
import matplotlib.pyplot as plt
import numpy as np
from keras.models import load_model
from keras.regularizers import l2
from keras.callbacks import EarlyStopping
from keras.layers import Dropout

zckkte

#!/usr/bin/env ruby

# bam - a simple directory search utility
# author: Zack A. Kite

require 'optparse'
require 'ostruct'
require 'pp'

HIDDEN_DIRS = ['.', '..']