lantiga

from transformers import BertForQuestionAnswering
import torch

bert_name = "bert-large-uncased-whole-word-masking-finetuned-squad"

model = BertForQuestionAnswering.from_pretrained(bert_name, torchscript=True)
model.eval()

inputs = [torch.ones(1, 2, dtype=torch.int64),
          torch.ones(1, 2, dtype=torch.int64),

tyhoff

from tqdm import tqdm
from tqdm.utils import CallbackIOWrapper

file_path = os.path.abspath(__file__)
upload_url = https://some-bucket.s3.amazonaws.com

file_size = os.stat(file_path).st_size
with open(file_path, "rb") as f:
    with tqdm(total=file_size, unit="B", unit_scale=True, unit_divisor=1024) as t:
        wrapped_file = CallbackIOWrapper(t.update, f, "read")

D2theR

##Gunicorn config file
"""
USAGE
gunicorn -b 127.0.0.1:8888 -c gunicorn.conf.py myapp.wsgi
"""
import os, pathlib

template_root = pathlib.Path('/full/path/to/myapp/templates/')
template_list = []
for path, subdirs, files in os.walk(template_root):

akashpalrecha

mblondel

# Authors: Mathieu Blondel, Vlad Niculae
# License: BSD 3 clause

import numpy as np


def _gen_pairs(gen, max_iter, max_inner, random_state, verbose):
    rng = np.random.RandomState(random_state)

    # if tuple, interpret as randn

alvations

What the BookCorpus?

So in the midst of all these Sesame Streets characters and robots transforming automobile era of "contextualize" language models, there is this "Toronto Book Corpus" that points to this kinda recently influential paper:

Yukun Zhu, Ryan Kiros, Rich Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, and Sanja Fidler. 2015. "Aligning books and movies: Towards story-like visual explanations by watching movies and reading books." In Proceedings of the IEEE international conference on computer vision, pp. 19-27.

Why do I even care, there's no translations there?

Some might know my personal pet peeve on collecting translation datasets but this BookCorpus has no translations, so why do I even care about it?

justinvanwinkle

# I was looking for a rate limiting library to call rate limited apis as closely 
#   as possible to their enforced limits.  I looked at the first few python libraries
#   that I found, and when I glanced at the source, they were all clearly broken.
# Curious how this could be, I took all the top google and pip search results for: python rate limiting
#   and tried to get them to do the wrong thing and fail to rate limit in situations that could come up 
#   in normal use (though in some cases very specific use)


# https://github.com/tomasbasham/ratelimit
# Where broken:

seanjtaylor

stepney141

Twitter Undocumented Bookmark API (DEPRECATED)

Update: 2022-03-25

Twitter has released the official API v2 endpoint for the bookmark feature. https://twittercommunity.com/t/build-with-bookmarks-on-the-twitter-api-v2/168804/

The following descriptions are or will soon be no longer useful; I suggest using the new official API.

---

naumansiddiqui4