daskol

#!/usr/bin/env python3
#   encoding: utf8
#   filename: gensitemap.py
"""Simple script to generate sitemap for a specified domain. It traverse all
HTML files from a given root directory and build URLs.
"""

import logging
import xml.etree.ElementTree as etree

daskol

#!/usr/bin/env python3
#   encoding: utf8
#   filename: fix-nbcounter.py
"""This simple script load Jupyter notebook and fix execution counter.
"""

from json import load, dump
from sys import argv

with open(argv[1]) as fin:

daskol

daskol

#!/usr/bin/env bash
#   download.sh

declare -a archives=(
    "https://data-static.usercontent.dev/DataClusteringSample0107.tar.gz"
    "https://data-static.usercontent.dev/DataClusteringSample0817.tar.gz"
    "https://data-static.usercontent.dev/DataClusteringSample1821.tar.gz"
)

for archive in ${archives[@]}; do

daskol

# Maintainer: Daniel Bershatsky <[email protected]>

pkgname=apache-arrow
pkgver=0.17.1
pkgrel=1
pkgdesc="Language-independent columnar memory format for flat and hierarchical data"
arch=('x86_64')
url='https://arrow.apache.org/'
license=('Apache')
depends=('boost-libs' 'jemalloc')

daskol

from typing import Tuple


def unzip_dataset(dataset) -> Tuple[tf.data.Dataset, ...]:
    """Function unzip_dataset takes a single dataset which element spec is a
    tuple and returns multiple datasets by number of tuple size of element spec.
    
    :param dataset: Input dataset.
    :return: Output tuple of datasets.
    """

daskol

#!/usr/bin/env python3
"""This script demonstrates event multiplexing on process identifiers (PIDs).
More specifically, we issue file descriptor (FD) from PID and. Then we wait
events on the descriptor. Note that polling such events is feasible because of
obtaining FD from PID with pidfd_open() system call. This feature was
introduced in 5.3 (Sep 2019). A usage example is below.

    $ ./wait4pid.py 1337 &
    $ kill -9 1337
    process with pid 1337 exited

daskol

import jax


def collect(threshold=256 * 1024 ** 2):
    backend = jax.lib.xla_bridge.get_backend()
    freed = 0
    for buf in backend.live_buffers():
        if buf.nbytes >= threshold:
            buf += buf.nbytes
            buf.delete()

daskol

import torch as T

model = T.nn.Sequential()
model.add_module('W0', T.nn.Linear(128, 10))
model.add_module('tanh', T.nn.Tanh())
model.add_module('W1', T.nn.Linear(10, 5))
model.add_module('tanh', T.nn.Tanh())
model.add_module('W2', T.nn.Linear(5, 1))

input = T.randn(16, 128)

daskol

#!/usr/bin/evn python3
# Run this script and then the command below.
#
#   dot -Tpng -ograph.png graph.dot
#

import torch as T
from torchviz import make_dot

model = T.nn.Sequential(