libfun

libfun

import os
import time
from slackclient import SlackClient
import re


slack_client = SlackClient(apikey)


def proc_out(msg):

libfun

import telepot

bot = telepot.Bot('key')
response = bot.getUpdates()
botid = bot_id


def sendMessage(z):
    try:
        bot.sendMessage(botid, z)

libfun

import lasagne
from lasagne.layers import InputLayer
from lasagne.layers.dnn import Conv3DDNNLayer
from lasagne.layers.dnn import Pool3DDNNLayer
from lasagne.layers import BatchNormLayer
from lasagne.layers import NonlinearityLayer
from lasagne.layers import ElemwiseSumLayer
from lasagne.layers import DenseLayer
from lasagne.nonlinearities import identity, softmax

libfun

import theano.tensor as T
from lasagne.layers import Layer


class Unpool3DLayer(Layer):
    """
    3D Unpooling layer
    This layer performs unpooling over the last two dimensions
    of a 5D tensor.
    Parameters

libfun

categories = ['bags', 'belts', 'dresses', 'eyewear',
              'footwear', 'hats', 'leggings', 'outerwear',
              'pants', 'skirts', 'tops']

photodict = dict()

train_ids = dict()
test_ids = dict()
retr_ids = list()
train_data = dict()