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Aleksei Petrenko alex-petrenko

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Last active May 11, 2021
Batch grading script
This script clones students' github repos with HW solutions, checks out a commit specified by the student,
and runs corresponding tests, generating a directory with reports.
Just place the script into the root of cloned "tests" repo and change global variables below appropriately.
Then run as "python"
from typing import Tuple
import torch
import torch.nn as nn
from torch.nn.utils.rnn import PackedSequence, invert_permutation
def _build_pack_info_from_dones(
dones, T: int
) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]:
View wireframe.cpp
#include <Corrade/Containers/GrowableArray.h>
#include <Corrade/Containers/Optional.h>
#include <Magnum/GL/Buffer.h>
#include <Magnum/GL/DefaultFramebuffer.h>
#include <Magnum/GL/Mesh.h>
#include <Magnum/GL/Renderer.h>
#include <Magnum/Math/Color.h>
#include <Magnum/Math/Matrix4.h>
#include <Magnum/MeshTools/Interleave.h>
class VizdoomEnvMultiplayer(VizdoomEnv):
def __init__(self, level, player_id, num_players, skip_frames, level_map='map01'):
super().__init__(level, skip_frames=skip_frames, level_map=level_map)
self.player_id = player_id
self.num_players = num_players
self.timestep = 0
self.update_state = True
def _is_server(self):
import os
import shutil
import time
from os.path import join
import cv2
import deepmind_lab
import gym
import numpy as np
from gym.utils import seeding
View gist:937da36b18bf58a830cf49710de81804
import sys
import math
import random
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
def encoder(observation):
with tf.variable_scope('encoder', reuse=tf.AUTO_REUSE):