karpathy

""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym

# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward

nailo2c

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

import os
import argparse
import gym
import numpy as np
from itertools import count

import torch
import torch.nn as nn

tokestermw

import torch, torch.nn as nn
from torch.autograd import Variable

text = ['BOS', 'How', 'are', 'you', 'EOS']
seq_len = len(text)
batch_size = 1
embedding_size = 1
hidden_size = 1
output_size = 1

ptrblck

import torch
import torch.nn as nn
import torch.optim as optim
from torch.autograd import Variable
import torch.nn.functional as F

import matplotlib.pyplot as plt

import numpy as np

IdeaKing

import cv2

from typing import Tuple

def resize_with_pad(image: np.array, 
                    new_shape: Tuple[int, int], 
                    padding_color: Tuple[int] = (255, 255, 255)) -> np.array:
    """Maintains aspect ratio and resizes with padding.
    Params:
        image: Image to be resized.