Kaixhin

# Collection of LSTM cells (including forget gates)
# https://en.wikipedia.org/w/index.php?title=Long_short-term_memory&oldid=784163987

import torch
from torch import nn
from torch.nn import Parameter
from torch.nn import functional as F
from torch.nn.modules.utils import _pair
from torch.autograd import Variable

Kaixhin

import torch


def cast(cuda):
  if cuda:
    return lambda x: x.cuda()
  else:
    return lambda x: x

Kaixhin

"""
The Annotated Transformer
http://nlp.seas.harvard.edu/2018/04/03/attention.html
Note: Only includes basic example, not real world example or multi-GPU training
"""


import numpy as np
import torch
import torch.nn as nn

Kaixhin

"""
Introduction to Monte Carlo Tree Search
http://jeffbradberry.com/posts/2015/09/intro-to-monte-carlo-tree-search/
"""

from copy import deepcopy
import datetime
from math import log, sqrt
from random import choice

Kaixhin

import os
import torch
from torch import nn, optim
from torch.nn import functional as F
from torch.utils.data import DataLoader
from torchvision import datasets, transforms
from torchvision.utils import save_image


class Encoder(nn.Module):

Kaixhin

from matplotlib import pyplot as plt
from mpl_toolkits import mplot3d

def scatter(X, Y, c=None, ax=None):
  ax = plt.axes() if ax is None else ax
  ax.scatter(X.numpy(), Y.numpy(), c=None if c is None else c.numpy())
  return ax

def contour(X, Y, Z, levels=None, ax=None):
  ax = plt.axes() if ax is None else ax