kastnerkyle

import torch
import torch.nn as nn
import torch.nn.parallel

class DCGAN_D(nn.Container):
    def __init__(self, isize, nz, nc, ndf, ngpu, n_extra_layers=0):
        super(DCGAN_D, self).__init__()
        self.ngpu = ngpu
        assert isize % 16 == 0, "isize has to be a multiple of 16"

kastnerkyle

SetOutputFilter DEFLATE

kastnerkyle

import torch
import math
import torch.optim
from torch.optim.optimizer import Optimizer, required
class AdamHD(Optimizer):
    """Implements Adam algorithm.
    It has been proposed in `Adam: A Method for Stochastic Optimization`_.
    Arguments:
        params (iterable): iterable of parameters to optimize or dicts defining
            parameter groups

kastnerkyle

"""
TreeLSTM[1] implementation in Pytorch

Based on dynet benchmarks : 
  https://github.com/neulab/dynet-benchmark/blob/master/dynet-py/treenn.py
  https://github.com/neulab/dynet-benchmark/blob/master/chainer/treenn.py
Other References:
  https://github.com/pytorch/examples/tree/master/word_language_model
  https://github.com/pfnet/chainer/blob/29c67fe1f2140fa8637201505b4c5e8556fad809/chainer/functions/activation/slstm.py
  https://github.com/stanfordnlp/treelstm

kastnerkyle

"""
A bare bones examples of optimizing a black-box function (f) using
Natural Evolution Strategies (NES), where the parameter distribution is a 
gaussian of fixed standard deviation.
"""

import numpy as np
np.random.seed(0)

# the function we want to optimize

kastnerkyle

def solve_tsp_dynamic(points):
    #calc all lengths
    all_distances = [[length(x,y) for y in points] for x in points]
    #initial value - just distance from 0 to every other point + keep the track of edges
    A = {(frozenset([0, idx+1]), idx+1): (dist, [0,idx+1]) for idx,dist in enumerate(all_distances[0][1:])}
    cnt = len(points)
    for m in range(2, cnt):
        B = {}
        for S in [frozenset(C) | {0} for C in itertools.combinations(range(1, cnt), m)]:
            for j in S - {0}:

kastnerkyle

kastnerkyle

# -*- coding: utf-8 -*-

# Copyright (C) 2017 by Akira TAMAMORI

# This program is free software; you can redistribute it and/or modify it under
# the terms of the GNU General Public License as published by the Free Software
# Foundation, either version 3 of the License, or (at your option) any later
# version.
#
# This program is distributed in the hope that it will be useful, but WITHOUT

kastnerkyle

# Copyright (C) 2017 by Akira TAMAMORI
#
# This program is free software; you can redistribute it and/or modify it under
# the terms of the GNU General Public License as published by the Free Software
# Foundation, either version 3 of the License, or (at your option) any later
# version.
#
# This program is distributed in the hope that it will be useful, but WITHOUT
# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
# FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more

kastnerkyle