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

# 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

#!/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

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

#!/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

#   encoding: utf8
#   filename: optimizer.py

import torch as T


def clip_momentum(value: float) -> float:
    if value > 1.0:
        return 1.0
    elif value < 0.0:

daskol

#   encoding: utf8
#   filename: maxout.py

import torch as T
import torch.nn.init as I

class TTMaxout(T.nn.Module):

    def __init__(self, in_features, out_features, n_channels, tt_rank,
                 bias=True, irange=0.005):

daskol

import torch as T

class Maxout(T.nn.Module):
    """Class Maxout implements maxout unit introduced in paper by Goodfellow et al, 2013.
    
    :param in_feature: Size of each input sample.
    :param out_feature: Size of each output sample.
    :param n_channels: The number of linear pieces used to make each maxout unit.
    :param bias: If set to False, the layer will not learn an additive bias.
    """

daskol

/**
 * \file tty-size.c
 * \brief Get size of console attached to stderr.
 */
#include <stdio.h>
#include <string.h>

#include <errno.h>
#include <sys/ioctl.h>
#include <unistd.h>