nikhilweee

import random
import torch

num_examples = 128
message_length = 32


def dataset(num_examples):
    """Returns a list of 'num_examples' pairs of the form (encrypted, original).

impshum

from pymongo import MongoClient


try:
    client = MongoClient('localhost')
    db = client.searchfollow
except:
    print("Could not connect to MongoDB")

call = db.command("dbstats")

stungeye

[
  {
    "url": "http://money.cnn.com",
    "rss": "http://rss.cnn.com/rss/money_topstories.rss"
  },
  {
    "url": "http://thehill.com",
    "rss": "http://thehill.com/rss/syndicator/19110"
  },
  {

oseiskar

lirnli

lirnli

fchollet

import keras
import numpy as np

timesteps = 60
input_dim = 64
samples = 10000
batch_size = 128
output_dim = 64

# Test data.

pieceofsummer

#!/usr/bin/python
import os, sys, gzip
from StringIO import StringIO
from datetime import datetime

def readByte(f):
	return ord(f.read(1))

def readInt(f):
	l = 0

tkm2261

cimport cython
import numpy as np
cimport numpy as np
from sklearn.metrics import f1_score


@cython.boundscheck(False)
@cython.wraparound(False)
def f1_opt(np.ndarray[long, ndim=1] label, np.ndarray[double, ndim=1] preds):

timehaven

"""akmtdfgen:  A Keras multithreaded dataframe generator.

Works with Python 2.7 and Keras 2.x.

For Python 3.x, need to fiddle with the threadsafe generator code.


Test the generator_from_df() functions by running this file:

    python akmtdfgen.py