f0k

#!/usr/bin/env python
# -*- coding: utf-8 -*-

"""
Example employing Lasagne for digit generation using the MNIST dataset and
Least Squares Generative Adversarial Networks
(LSGANs, see https://arxiv.org/abs/1611.04076 for the paper).

It is based on a WGAN example:
https://gist.github.com/f0k/f3190ebba6c53887d598d03119ca2066

kashif

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, Dropout
from keras.layers.normalization import BatchNormalization
from keras.models import Model
from keras.preprocessing.image import ImageDataGenerator
from keras.utils import np_utils

matthias-k

lebedov

#!/usr/bin/env python

"""
Self-launching MPI4PY script that uses spawning and sets an environmental 
variable to different values for each of the launched script instances..

Notes
-----
Requires an MPI implementation that supports dynamic process management.
"""

benanne

import lasagne as nn
Conv2DLayer = nn.layers.Conv2DDNNLayer

def inception_module(l_in, num_1x1, reduce_3x3, num_3x3, reduce_5x5, num_5x5, gain=1.0, bias=0.1):
    """
    inception module (without the 3x3s1 pooling and projection because that's difficult in Theano right now)
    """
    shape = l_in.get_output_shape()
    out_layers = []

henrik

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