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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 / file_streaming_pytorch.py
Created April 21, 2020 02:19
In this gist i have tried to explain a very smart way of loading datasets by streaming them from bytes into PyTorch; It can be achieved in multiple ways, but here my focus was confined to David's idea of streaming records from a bytes file;
import torch
import io
import pandas as pd
import gc
import numpy as np
import transformers
'''
Original Code Author [@dlibenzi](https://github.com/dlibenzi)
@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