andcarnivorous

import torch
import cv2
import numpy as np
import json
from torchvision import transforms
from PIL import Image

model = torch.hub.load('pytorch/vision', 'mobilenet_v2', pretrained=True).cuda()
model.eval()

andcarnivorous

sudo apt-get update && sudo apt-get upgrade
sudo echo "Well, well, well... Look who fucked the system up again, reinstalling..."
echo "Installing cuda and cudnn"
sudo apt-get install -y system76-cuda-latest system76-cudnn-10.1 cmake
echo "installing python stuff"
sudo apt-get install -y python3-pip python3-pip
sudo pip3 install torch torchvision
sudo apt-get install -y python3-pandas python3-seaborn python3-matplotlib

echo "Installing Emacs and more..."

andcarnivorous

from matplotlib import cm as cm
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
from nltk.tokenize import word_tokenize
import re
from scipy import sparse

def repetitionMatrix(_input, title = "", kind = False, cmap = "Reds"):
  

andcarnivorous

from nltk import pos_tag, word_tokenize
    
def yodinator(text):

    text = word_tokenize(text)

    tagged = pos_tag(text)

    verbs = ("MD", "VB", "VBD", "VBG", "VBN", "VBP", "VBZ", "RB", "RBR", "RBS")

andcarnivorous

from math import cos,sin,radians
import matplotlib.pyplot as plt
import numpy as np

vec = np.array([-5,-8]) #YOUR VECTOR

k = 1 #decide K for shear

# Transformations
def custom_transf (vector, m1,m2,m3,m4):

andcarnivorous

import numpy as np
import random

def table_printer(matrix):
    print("")
    print("     1   2   3   4")
    print("1 ", matrix[0][:])
    print("1 ", matrix[1][:])
    print("1 ", matrix[2][:])
    print("1 ", matrix[3][:])