jihobak

from sqlalchemy.ext.declarative import declarative_base
#from sqlalchemy import *
#from sqlalchemy.orm import *

# Pro entity v podadresari. Podaresar *musi* obsahovat prazdny soubor __init__.py !
#from entity.User import User

'''
Zavislosti:
    # apt-get install python-sqlalchemy

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module_param_named, 커널 모듈 매개 변수 매크로

모듈 매개 변수 지정 방법:

#include:

#include <linux/moduleparam.h>

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"""adapted from https://github.com/OlavHN/bnlstm to store separate population statistics per state"""
import tensorflow as tf, numpy as np
RNNCell = tf.nn.rnn_cell.RNNCell

class BNLSTMCell(RNNCell):
    '''Batch normalized LSTM as described in arxiv.org/abs/1603.09025'''
    def __init__(self, num_units, is_training_tensor, max_bn_steps, initial_scale=0.1, activation=tf.tanh, decay=0.95):
        """
        * max bn steps is the maximum number of steps for which to store separate population stats
        """

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import numpy as np
from scipy.ndimage.interpolation import map_coordinates
from scipy.ndimage.filters import gaussian_filter

def elastic_transform(image, alpha, sigma, random_state=None):
    """Elastic deformation of images as described in [Simard2003]_.
    .. [Simard2003] Simard, Steinkraus and Platt, "Best Practices for
       Convolutional Neural Networks applied to Visual Document Analysis", in
       Proc. of the International Conference on Document Analysis and
       Recognition, 2003.

jihobak

7
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jihobak

jihobak

#!/usr/bin/env python
#coding=utf8
##########################################################################################
import os
import logging
import logging.handlers
import traceback
from flask import Flask
from flask.ext.restful import reqparse, abort, Api, Resource
from flask import request

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##########################################################################################
import os
import sys
import json
import unittest
import pprint
import httplib
import urllib
import datetime
import random

jihobak

Automation for the People

Long ago, the first time I read "The Pragmatic Programmer", I read some advice that really stuck with me.

"Don't Use Manual Procedures".

This in the chapter on Ubiquitous Automation. To summarize, they want you to automate all the things.

The trouble was that I hadn't much of an idea how to actually go

jihobak

from __future__ import print_function

from keras.datasets import cifar10
from keras.layers import merge, Input
from keras.layers.convolutional import Convolution2D, ZeroPadding2D, AveragePooling2D
from keras.layers.core import Dense, Activation, Flatten
from keras.layers.normalization import BatchNormalization
from keras.models import Model
from keras.preprocessing.image import ImageDataGenerator
from keras.utils import np_utils