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Please make sure you already install the Anaconda.

I will create a virtual environment with anaconda and install the pygame in this virtual environment.

• First create a virtual environment called pygame and install the Python 3.6 version.

conda create --name pygame python=3.6

• Change to the pygame virtual environment.

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#!/usr/bin/env bash

if [ ! -x .git/hooks/commit-msg ] || [ ! -f .git/hooks/commit-msg ] || ! cmp ./hooks/commit-msg.sh .git/hooks/commit-msg
    then
    echo -e "\033[33m Setting Up Git commit Hook..."
    mkdir -p .git/hooks/
    cp ./hooks/commit-msg.sh .git/hooks/commit-msg
    chmod +x .git/hooks/commit-msg
    echo -e "\033[32m Done"
    echo -e "\033[33m You can make commit now."

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import os
import tarfile
import urllib.request
from datetime import datetime
import zipfile


data_dir = "./data/"
if not os.path.exists(data_dir):
    os.mkdir(data_dir)

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{"version":1,"resource":"file:///Users/smap/Project/seqal/seqal/stoppers/__init__.py","entries":[{"id":"F4pE.py","timestamp":1658194872996}]}

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from collections import OrderedDict
import numpy as np
import spacy
from spacy.lang.en.stop_words import STOP_WORDS

nlp = spacy.load('en_core_web_sm')

class TextRank4Keyword():
    """Extract keywords from text"""
    

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import requests

headers ={
      'Authorization': 'token <TOKEN>', # replace <TOKEN> with your token
    }

response = requests.get('https://api.github.com/users/<username>/received_events', headers=headers) # replace <username> with your user name
data = response.json()
event_actions = {'WatchEvent': 'starred', 'PushEvent': 'pushed to'}

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import numpy as np
from tqdm import tqdm


def load_glove(file):
    """Loads GloVe vectors in numpy array.
    Args:
        file (str): a path to a glove file.
    Return:
        dict: a dict of numpy arrays.

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import unicodedata
from typing import List
from pathlib import Path
from collections import defaultdict

from ahocorasick import Automaton


def read_dictionary(dict_path: str) -> dict:
  with open(dict_path, 'r', encoding='utf-8') as f:

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from typing import List, Dict, Sequence

class Matrics:
    def __init__(self, sents_true_labels: Sequence[Sequence[Dict]], sents_pred_labels:Sequence[Sequence[Dict]]):
        self.sents_true_labels = sents_true_labels
        self.sents_pred_labels = sents_pred_labels 
        self.types = set(entity['type'] for sent in sents_true_labels for entity in sent)
        self.confusion_matrices = {type: {'TP': 0, 'TN': 0, 'FP': 0, 'FN': 0} for type in self.types}
        self.scores = {type: {'p': 0, 'r': 0, 'f1': 0} for type in self.types}

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"""
pip install torch==1.4.0 torchvision==0.5.0 tensorboard==2.1.0

command:
  python tensorboard_epoch_demo.py
  tensorboard --logdir=runs    
"""

import torch
import torch.nn as nn