integration-tests/examples/test_templates/deeplearning/template_torch.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "itorch.image({image.lena(), image.lena(), image.lena()})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "itorch.html('<p><b>Hi there!</b> this is arbitrary HTML</p>')\n",
    "window_id = itorch.html('<p>This text will be replaced in 2 seconds</p>')\n",
    "os.execute('sleep 2')\n",
    "itorch.html('<p>magic!</p>', window_id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Plot = require 'itorch.Plot'\n",
    "x1 = torch.randn(40):mul(100)\n",
    "y1 = torch.randn(40):mul(100)\n",
    "x2 = torch.randn(40):mul(100)\n",
    "y2 = torch.randn(40):mul(100)\n",
    "x3 = torch.randn(40):mul(200)\n",
    "y3 = torch.randn(40):mul(200)\n",
    "\n",
    "\n",
    "-- scatter plots\n",
    "plot = Plot():circle(x1, y1, 'red', 'hi'):circle(x2, y2, 'blue', 'bye'):draw()\n",
    "plot:circle(x3,y3,'green', 'yolo'):redraw()\n",
    "plot:title('Scatter Plot Demo'):redraw()\n",
    "plot:xaxis('length'):yaxis('width'):redraw()\n",
    "plot:legend(true)\n",
    "plot:redraw()\n",
    "-- print(plot:toHTML())\n",
    "plot:save('out.html')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot = Plot():line(x1, y1,'red','example'):legend(true):title('Line Plot Demo'):draw()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "iTorch",
   "language": "lua",
   "name": "KERNEL_NAME"
  },
  "language_info": {
   "name": "lua",
   "version": "5.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}