sebastiancarlos

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

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

felixgwu

import torch
from torch import nn

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


class DenseBlock(nn.Module):

vxgmichel

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

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

from itertools import count

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.