TeraBytesMemory

# -*- mode: ruby -*-
# vi: set ft=ruby :

Vagrant.configure("2") do |config|
  config.vm.box = "Microsoft/EdgeOnWindows10"
  config.vm.box_version = "1.0"

  config.vm.provider "virtualbox" do |vb|
    # guiの設定
    vb.gui = true

TeraBytesMemory

from notebook.base.handlers import APIHandler as IPyAPIHandler
import json


class APIHandler(IPyAPIHandler):
    def set_default_headers(self):
        self.set_header('Content-Type', 'application/json')

    def finish(self, chunk=None):
        if type(chunk) == dict:

TeraBytesMemory

# encode: utf-8

from flask.views import MethodView
from flask import request, Response, json
import os
import re


OAUTH_BEAR_TOKEN = os.environ.get('OAUTH_BEAR_TOKEN')

TeraBytesMemory

# coding: utf-8

from logging import getLogger, Formatter, StreamHandler
import logging


def logger(
    logger_name='',
    level=logging.DEBUG,
    Handler=StreamHandler,

TeraBytesMemory

import chainer
import chainer.functions as F
from chainer import LinkHook
from typing import List, Optional
import cv2


class IntermidateCache(LinkHook):
    def __init__(self, layer: chainer.Chain):
        layer.add_hook(self)

TeraBytesMemory

import chainer
import chainer.functions as F

class Dropout1d(chainer.Chain):
    '''
    spatial dropout module (1d)
    '''

    def __init__(self, raito=.5):
        super().__init__()

TeraBytesMemory

# coding: utf-8

import chainer
import chainer.functions as F
import chainer.links as L

try:
    from chainer.backend import get_array_module
except:
    import numpy as np

TeraBytesMemory

# coding: utf-8

from io import BytesIO
import cv2
from fnmatch import fnmatch
from google.cloud.storage import Client, Blob
import numpy as np
import pandas as pd
import os.path
from pathlib import Path

TeraBytesMemory

import MeCab

class MeCabGenerator(object):
    def __init__(self, dict_path='/usr/local/lib/mecab/dic/mecab-ipadic-neologd'):
        self.mecab = MeCab.Tagger ('-d {}'.format(dict_path))
        
    def parse(self, text):
        return self._generator_wrapper(text)
    
    def get_morphemes(self, text, surface_filter=lambda x: x):

TeraBytesMemory

import CaboCha
class CaboChaGenerator(object):
    def __init__(self):
        self.c = CaboCha.Parser()
        
    def parse_to_chunk(self, text):
        tree =  self.c.parse(text)
        for i in range(tree.chunk_size()):
            chunk = tree.chunk(i)
            chunk_tokens = [