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# install mkl
RUN apt update && apt install -y --force-yes apt-transport-https && \
  wget https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS-2019.PUB && \
  apt-key add GPG-PUB-KEY-INTEL-SW-PRODUCTS-2019.PUB && \
  sh -c 'echo deb https://apt.repos.intel.com/mkl all main > /etc/apt/sources.list.d/intel-mkl.list' && \
  apt-get update && DEBIAN_FRONTEND=noninteractive apt-get -y install cpio intel-mkl-64bit-2018.3-051 && \
  (find /opt/intel -name "ia32*" -exec rm -rf {} \; || echo "removing ia32 binaries") ; \
  (find /opt/intel -name "examples" -type d -exec rm -rf {} \; || echo "removing examples") ; \
  (find /opt/intel -name "benchmarks" -exec rm -rf {} \; || echo "removing benchmarks") ; \
  (find /opt/intel -name "documentation*" -exec rm -rf {} \; || echo "removing documentation") ; \

alapini

extern mod sync;

// str op trait
use std::str::StrSlice;
// for tcp listen
use std::io::{TcpListener, TcpStream};
use std::io::net::ip::SocketAddr;
// for trait
use std::io::{Listener, Writer, Acceptor, Buffer};
// for spawn

alapini

"""
Hierarchial Clustering.
The goal of gist is to show to use scikit-learn to perform agglomerative clustering when:
1. There is a need for a custom distance metric (like levenshtein distance)
2. Use the distance in sklearn's API.

Adapted from: sklearn's FAQ.
http://scikit-learn.org/stable/faq.html
"""

alapini

import time
import numba
from numba import jit
import numpy as np

#input matrices
matrix1 = np.random.rand(30,30)
matrix2 = np.random.rand(30,30)
rmatrix = np.zeros(shape=(30,30))

alapini

from numba import cuda

gpus = cuda.gpus.lst

for gpu in gpus:
    with gpu:
        meminfo = cuda.current_context().get_memory_info()
        print("%s, free: %s bytes, total, %s bytes" % (gpu, meminfo[0], meminfo[1]))

alapini

:: Launch PyCharm from within conda environment

:: This will ensure that all necessary environment variables are set.
:: Modify the paths and environment name for your installation, if necessary.
:: This configuration is for PyCharm x64 installed with JetBrains Toolbox and 
:: will launch the latest installed version.

@set condaroot="%userprofile%\Anaconda3"
@set pycharmroot="%localappdata%\JetBrains\Toolbox\apps\PyCharm-P\ch-0"
@set env=base

alapini

alapini

// Source : https://gist.github.com/Azerothian/dc84f009a94579b5bb43#gistcomment-2002977
function isObject(avar) {
    // cosntructor.name tested for `function Animal(){}; var a = new Animal(); isObject(a);` will return true otherwise as it is [Object object]
    return Object.prototype.toString.call(avar) === '[object Object]' && avar.constructor.name === 'Object';
}
function createGqlQuery(obj) {
    let shape = [];
  
    for (let [key, val] of Object.entries(obj))
      shape.push(isObject(val) ? `${key} { ${createGqlQuery(val)} }` : key);

alapini

https://github.com/Microsoft/vscode/blob/c2d56115afa1647f204ec9afec3a078fc1dac67a/src/vs/workbench/api/electron-browser/mainThreadSaveParticipant.ts#L333

alapini

package com.stackoverflow.q3732109;

import java.io.IOException;
import java.io.OutputStream;
import java.net.InetSocketAddress;

import com.sun.net.httpserver.HttpExchange;
import com.sun.net.httpserver.HttpHandler;
import com.sun.net.httpserver.HttpServer;