Thread_limit_test.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Thread limit test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from contextlib import ContextDecorator                                                                      \n",
    "from threadpoolctl import threadpool_limits \n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class threadpool_limits_decorator(threadpool_limits, ContextDecorator):\n",
    "    def __enter__(self):\n",
    "        return self\n",
    "    def __exit__(self, *exc):\n",
    "        return False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def thread_test_1():\n",
    "    for i in range(100):\n",
    "        _ = np.dot(np.random.rand(10**3, 10**3),np.random.rand(10**3, 10**3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "thread_test_1() #  this will run with all threads"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def thread_test_2():\n",
    "    with threadpool_limits(1):\n",
    "        for i in range(100):\n",
    "            _ = np.dot(np.random.rand(10**3, 10**3),np.random.rand(10**3, 10**3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "thread_test_2() #  this will run with one threads"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "thread_test_1() #  this will run with all threads"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "def thread_test_3():\n",
    "    for i in range(100):\n",
    "        _ = np.dot(np.random.rand(10**3, 10**3),np.random.rand(10**3, 10**3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "thread_test_3 = threadpool_limits_decorator(1)(thread_test_3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "thread_test_3()  # this will run with one thread"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "thread_test_1()  # this will run with one thread"
   ]
  }
 ],
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