GaelVaroquaux

'''
Non-parametric computation of entropy and mutual-information

Adapted by G Varoquaux for code created by R Brette, itself
from several papers (see in the code).

This code is maintained at https://github.com/mutualinfo/mutual_info 
Please download the latest code there, to have improvements and 
bug fixes.

vxgmichel

"""Command line interface for monitoring asyncio tasks."""

import os
import signal
import asyncio
import argparse
import traceback
import linecache

from itertools import count

felixgwu

import torch
from torch import nn

__all__ = ['FCDenseNet', 'fcdensenet_tiny', 'fcdensenet56_nodrop',
           'fcdensenet56', 'fcdensenet67', 'fcdensenet103',
           'fcdensenet103_nodrop']


class DenseBlock(nn.Module):

naotokui

# coding: utf8

## based on this article: http://qiita.com/mokemokechicken/items/937a82cfdc31e9a6ca12

import numpy as np
from keras.models import Sequential
from keras.engine.topology import Input, Container
from keras.engine.training import Model
from keras.layers.core import Dense

kevinzakka

"""
Create train, valid, test iterators for CIFAR-10 [1].
Easily extended to MNIST, CIFAR-100 and Imagenet.

[1]: https://discuss.pytorch.org/t/feedback-on-pytorch-for-kaggle-competitions/2252/4
"""

import torch
import numpy as np

sebastiancarlos