ShigekiKarita

"use strict";

// カリー化関数
const func = x => y => z => x + y + z;
func(1)(2)(3); // きもい


// 不動点コンビネータ
// 参考： http://mew.org/~kazu/material/2012-id-const.pdf
const y_con = f => (x => y => f(x(x))(y))

ShigekiKarita

[==========] Running 3 tests from 1 test case.
[----------] Global test environment set-up.
[----------] 3 tests from CNN
[ RUN      ] CNN.PropConv
[       OK ] CNN.PropConv (59 ms)
[ RUN      ] CNN.PropPool
[       OK ] CNN.PropPool (0 ms)
[ RUN      ] CNN.PropPoolRandom
[       OK ] CNN.PropPoolRandom (4 ms)
[----------] 3 tests from CNN (63 ms total)

ShigekiKarita

// just FAIL
TEST(CNN, TotalPooling)
{
    const std::size_t pool = 2;
    const std::size_t stride = 2;
    const std::size_t input = 6; // NOTE: this means W_conv.rows(), output from convolution ply
    const std::size_t output = (input / stride - pool + 1) * stride; // no overlap
    const std::size_t batch = 2;
    ASSERT_EQ(4, output);
    

ShigekiKarita

;; =======
;; Haskell
;; =======

(require 'auto-complete)
(require 'haskell-mode)
(require 'haskell-cabal)

(autoload 'ghc-init "ghc" nil t)

ShigekiKarita

import std.algorithm

auto deeper(T, U)(U[T][] records, U[][] maxElems)
{
    // こういうのはこうかけるが
    auto maxRec = records.map!values.reduce!max;
    
    // こういうのはこうかくしか
    auto nextRecords = maxElems
        .map!(

ShigekiKarita

from math import log2
from csv import reader
from collections import Counter
from sys import argv


def transpose(xx):
    return map(list, zip(*xx))

ShigekiKarita

#ifndef matrix_utils_hpp
#define matrix_utils_hpp

#include <vector>
#include <array>
#include <type_traits>
#include <fstream>

#include <boost/archive/xml_iarchive.hpp>
#include <boost/archive/xml_oarchive.hpp>

ShigekiKarita

cmake_minimum_required(VERSION 2.8.4)
project(MyCMakeTemplate)


## Configure compiler and libraries : Boost
add_compile_options(-std=c++1y -Wall -Wextra)
include_directories(${PROJECT_SOURCE_DIR}/include)

if(CMAKE_CXX_COMPILER_ID STREQUAL "GNU")

ShigekiKarita

# built in
import random

# previous code
from sdr import to_sdr, to_real_number

# third library : https://github.com/pybrain/pybrain
from pybrain.structure import LinearLayer, SigmoidLayer, BiasUnit, FullConnection, RecurrentNetwork
from pybrain.datasets import SupervisedDataSet
from pybrain.supervised.trainers import BackpropTrainer

ShigekiKarita

#!/usr/bin/env bash

# Functions
function usage {
this=$(basename ${0})
    cat <<EOF
${this} is a tool for CMake and CTest

Usage:
    ${this} [command] [<options>]