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#from my repo
#https://github.com/AdityaSoni19031997/Machine-Learning/blob/master/AV/AV_Enigma_NLP_functional_api.ipynb
def preprocess_word(word):
# Remove punctuation
word = word.strip('\'"?!,.():;')
# Convert more than 2 letter repetitions to 2 letter
# funnnnny --> funny
word = re.sub(r'(.)\1+', r'\1\1', word)
# Remove - & '
#!/usr/bin/env python
# encoding: utf-8
import sys
def trace_calls_and_returns(frame, event, arg):
co = frame.f_code
func_name = co.co_name
if func_name == 'write':
# Ignore write() calls from print statements

1.251.423.0 1.279.441.0 1.257.387.0 1.275.1078.0 1.249.88.0 1.275.1080.0 1.257.401.0 1.275.1744.0 1.275.1346.0 1.249.715.0

# Installs PyTorch, PyTorch/XLA, and Torchvision
# Copy this cell into your own notebooks to use PyTorch on Cloud TPUs
# Warning: this may take a couple minutes to run
import collections
from datetime import datetime, timedelta
import os
import requests
import threading
import random
from itertools import chain, cycle, islice
import torch.utils.data as data
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
import time
import torch
import numpy as np
@AdityaSoni19031997
AdityaSoni19031997 / redis.py
Created April 18, 2021 09:39 — forked from hanneshapke/redis.py
Load word vectors into a redis db
import bz2
import pickle
from django.conf import settings
from djang_redis import get_redis_connection
from tqdm import tqdm
from .constants import GOOGLE_WORD2VEC_MODEL_NAME
@AdityaSoni19031997
AdityaSoni19031997 / NOTES.md
Created July 14, 2021 07:03 — forked from wvengen/NOTES.md
Semantic web of food notes
@AdityaSoni19031997
AdityaSoni19031997 / gist:0916ddf3d0918d4980eac13d3411fbfa
Created July 23, 2021 18:03 — forked from Nicksil/gist:5646003
Python - Knuth-Morris-Pratt (KMP) string-matching algorithm
# File: KnuthMorrisPratt.py
# Author: Keith Schwarz (htiek@cs.stanford.edu)
#
# An implementation of the Knuth-Morris-Pratt (KMP) string-matching algorithm.
# This algorithm takes as input a pattern string P and target string T, then
# finds the first occurrence of the string T in the pattern P, doing so in time
# O(|P| + |T|). The logic behind the algorithm is not particularly complex,
# though getting it to run in linear time requires a few non-obvious tricks.
#
# To motivate KMP, consider the naive algorithm for trying to match a pattern