{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "69c32066",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<NVIDIA GeForce RTX 3050 Ti Laptop GPU on Platform: NVIDIA CUDA (1 refs)>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pyclesperanto_prototype as cle\n",
    "import timeit\n",
    "\n",
    "cle.select_device(\"RTX\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0d5e8e7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "inp = cle.create((1024, 1024, 40))\n",
    "out = cle.create((1024, 1024, 40))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6f7f61c0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The slowest run took 10.12 times longer than the fastest. This could mean that an intermediate result is being cached.\n",
      "2.31 ms ± 1.79 ms per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit cle.add_image_and_scalar(inp, out, scalar = 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "58651618",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'cupy backend (experimental)'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cle.select_device(\"cupy\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "690dde8e",
   "metadata": {},
   "outputs": [],
   "source": [
    "inp = cle.create((1024, 1024, 40))\n",
    "out = cle.create((1024, 1024, 40))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "bb399ac9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\structure\\code\\pyclesperanto_prototype\\pyclesperanto_prototype\\_tier0\\_cuda_backend.py:31: UserWarning: clesperanto's cupy / CUDA backend is experimental. Please use it with care. The following functions are known to cause issues in the CUDA backend:\n",
      "affine_transform, apply_vector_field, create(uint64), create(int32), create(int64), label_spots, labelled_spots_to_pointlist, resample, scale, spots_to_pointlist\n",
      "  warnings.warn(\"clesperanto's cupy / CUDA backend is experimental. Please use it with care. The following functions are known to cause issues in the CUDA backend:\\n\" +\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The slowest run took 7.37 times longer than the fastest. This could mean that an intermediate result is being cached.\n",
      "1.23 ms ± 1.02 ms per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit cle.add_image_and_scalar(inp, out, scalar = 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b50fddfc",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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