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#!/usr/bin/env python
# coding: utf-8

# <h1>Table of Contents<span class="tocSkip"></span></h1>
# <div class="toc"><ul class="toc-item"></ul></div>

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import os

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#!/usr/bin/env python
# coding: utf-8

## =============== REQUIREMENTS =============== ##
## rmrl: https://github.com/naturale0/rmrl
## rsync (for rM): 
##   - https://github.com/JBBgameich/rsync-static/releases/download/continuous/rsync-arm
##   - https://www.reddit.com/r/RemarkableTablet/comments/hetyfa/comment/fvu1fy3/?utm_source=share&utm_medium=web2x&context=3

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pkg update
pkg install python build-essential freetype libpng libzmq libcrypt libjpeg-turbo libxml2 libxslt
pip install bs4 requests lxml

curl -LO https://its-pointless.github.io/setup-pointless-repo.sh
bash setup-pointless-repo.sh
pkg install numpy scipy

pip install matplotlib jupyter

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import itertools
from torchtext.experimental.datasets import TextClassificationDataset
from torchtext.vocab import build_vocab_from_iterator
from torchtext.experimental.functional import sequential_transforms

from torchtext.experimental.datasets import IMDB
from torchtext.data.utils import get_tokenizer
from torch.nn.utils.rnn import pack_padded_sequence

def build_char_vocab(data, index, bow="<w>", eow="</w>"):

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# In []:
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import scipy as sp

A = np.random.normal(5, 1, 100)
B = np.random.normal(3, 1.5, 100)
C = np.random.normal(4, 2, 100)

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