Hiroshiba

# findで見つけたファイルの最新-最古unixタイムを得るコマンド
echo `find [dir] [filter] -printf '%C@\n' | sort | awk 'NR==1; END{print}'` | awk '{print ($2 - $1)}'

Hiroshiba

Hiroshiba

rsync-xargs-pull () {
    d=$2; d=${d%/*}
    rsync --dry-run -av $1:$2 $3 | xargs -n128 -P1 -I@ rsync -avR $1:$d/./@ $3
}

Hiroshiba

"""
python chainer_log_to_csv.py [input path] [output path]
"""

import argparse
import csv
import json

parser = argparse.ArgumentParser()
parser.add_argument('input')

Hiroshiba

Hiroshiba

import argparse
import glob
import multiprocessing

import numpy
import tqdm

parser = argparse.ArgumentParser()
parser.add_argument('glob')
parser.add_argument('--processes', type=int)

Hiroshiba

p=`python -c "import matplotlib; print(matplotlib.matplotlib_fname())"`
sed -i -e "s/backend\s*:\s*TkAgg/backend : Agg/g" $p

Hiroshiba

import chainer


class Convolution1D(chainer.links.ConvolutionND):
    def __init__(self, in_channels, out_channels, ksize, stride=1, pad=0,
                 nobias=False, initialW=None, initial_bias=None,
                 cover_all=False):
        super(Convolution1D, self).__init__(
            ndim=1,
            in_channels=in_channels,

Hiroshiba

Hiroshiba

import numpy


def concat_recursive(batch, newaxis=False):
    """
    >>> from pprint import pprint
    >>> onedata = numpy.arange(3).reshape(1, -1)
    >>> batch = [onedata] * 4
    >>> pprint(concat_recursive(batch))
    array([[0, 1, 2],