ktnyt

import numpy as np
import theano
import theano.tensor as T

class RAE(object):
	def __init__(self, input, rng, d, W=None, b=None, U=None, c=None):
		dv = d
		dh = d * 2

		self.dv = dv

ktnyt

use strict;
use warnings;

use utf8;
use Encode;

use Scalar::Util 'blessed';
use Net::Twitter;

my $username = shift;

ktnyt

#!/usr/bin/env perl
###############################################################################
#
# Modules
#
use strict;
use warnings;
use utf8;

use POSIX;

ktnyt

use strict;
use warnings;

print p([@ARGV]), "\n";

sub p {
    my $e = shift;
    my $s = shift @{$e};
    return p($e) + p($e) if $s eq "+";
    return p($e) - p($e) if $s eq "-";

ktnyt

use strict;
use warnings;

my @list = qw(1 2 3 4);
my @p = permute([@list], []);
foreach my $s (map{join("\t", @{$_})}@p) {
    printf("%s\n", $s);
}

sub permute {

ktnyt

/******************************************************************************
**  iqstat - Interactive qstat viewer
**
**  Created by kotone on 2015/01/16.
**  Copyright (c) 2015 Kotone Itaya. All rights reserved.
**
** iqstat is free software: you can redistribute it and/or modify
** it under the terms of the GNU General Public License as published by
** the Free Software Foundation, either version 3 of the License, or
** (at your option) any later version.

ktnyt

#!/usr/bin/env python
import numpy as np
from chainer import cuda, Function, FunctionSet, gradient_check, Variable, optimizers
import chainer.functions as F

x_train = np.array([
    [[0., 0.]],
    [[0., 1.]],
    [[1., 0.]],
    [[1., 1.]]

ktnyt

import argparse
import numpy as np
from sklearn.datasets import fetch_mldata
from chainer import Variable, FunctionSet, optimizers, cuda
import chainer.functions  as F
#import utils

parser = argparse.ArgumentParser(description='Chainer example: MNIST')
parser.add_argument('--gpu', '-g', default=-1, type=int,
                    help='GPU ID (negative value indicates CPU)')

ktnyt

import argparse
import numpy as np
from sklearn.datasets import fetch_mldata
from chainer import Variable, FunctionSet, optimizers, cuda
import chainer.functions  as F
import brica1

class Perceptron():
    def __init__(self, n_in, n_out, use_cuda=False):
        self.model = FunctionSet(

ktnyt

#!/usr/bin/env perl
use strict;
use warnings;

my $base = "togows.dbcls.jp/entry/nucleotide";

my ($prefix, $from_id, $to_id) = (@ARGV);

if($from_id > $to_id) {
    ($from_id, $to_id) = ($to_id, $from_id);