Aoinu

{
    "name": "pm.booth.aoinu607.udon.Something",
	"references": [
        "GUID:3c1bc1267eab5884ebe7f232c09ee0d9",
        "GUID:99835874ee819da44948776e0df4ff1d",
        "GUID:6490804aa441dfe4b88eb56cccbdf081"
    ],
    "includePlatforms": [],
    "excludePlatforms": [],
    "allowUnsafeCode": false,

Aoinu

# ~/.bashrc: executed by bash(1) for non-login shells.
# see /usr/share/doc/bash/examples/startup-files (in the package bash-doc)
# for examples

# If not running interactively, don't do anything
case $- in
    *i*) ;;
      *) return;;
esac

Aoinu

#include <stdio.h>
#include <omp.h>

#define W 100
#define H 100
double diff(double backward, double material, double forward);
double one_side_diff(double wall, double material);

int main() {
    double Temperature = 10.0; // [℃]

Aoinu

#! /usr/bin/env python
# coding : utf-8

import argparse
import numpy as np
from scipy.misc import imsave
import chainer
import chainer.functions as F
import chainer.links as L
from chainer.training import extensions

Aoinu

#! /usr/bin/env python
# coding: utf-8

import argparse
import chainer
import chainer.functions as F
import chainer.links as L
import numpy as np
from scipy.misc import imsave
from chainer.training import extensions

Aoinu

#! /usr/bin/env python
# coding: utf-8

import argparse
import chainer
import chainer.functions as F
import chainer.links as L
import numpy as np
from scipy.misc import imsave
from chainer.training import extensions

Aoinu

train, test = chainer.datasets.get_cifar100(withlabel=False)

Aoinu

#! /usr/bin/env python
# coding: utf-8

import argparse
import chainer
import chainer.functions as F
import chainer.links as L
import numpy as np
from chainer.training import extensions
from scipy.misc import imsave

Aoinu

#! /usr/bin/env python
# coding: utf-8

import argparse
import chainer
import chainer.functions as F
import chainer.links as L
import numpy as np
from scipy.misc import imsave
from chainer.training import extensions

Aoinu

#!/usr/bin/env python
# coding: utf-8

import numpy as np
import chainer
import chainer.links as L
import chainer.functions as F
from chainer.training import extensions
import argparse
from scipy.misc import imsave