{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import Foundation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import Glibc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dlopen(\"/home/ubuntu/swift/usr/lib/swift/linux/libPath.so\", RTLD_NOW)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import Path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(Path.home)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dlopen(\"/home/ubuntu/swift/usr/lib/swift/linux/libJust.so\", RTLD_NOW)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import Just"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "func shell(_ launchPath: String, _ arguments: [String]) -> String?\n",
    "{\n",
    "    let task = Process()\n",
    "    task.launchPath = launchPath\n",
    "    task.arguments = arguments\n",
    "\n",
    "    let pipe = Pipe()\n",
    "    task.standardOutput = pipe\n",
    "    task.launch()\n",
    "\n",
    "    let data = pipe.fileHandleForReading.readDataToEndOfFile()\n",
    "    let output = String(data: data, encoding: String.Encoding.utf8)\n",
    "\n",
    "    return output\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "var from = \"http://yann.lecun.com/exdb/mnist\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "func get_file(_ from:String, _ fn:String) {\n",
    "    let cts = Just.get(\"\\(from)/\\(fn).gz\").content!\n",
    "    try! cts.write(to: URL.init(fileURLWithPath: \"\\(fn).gz\"))\n",
    "    shell(\"/bin/gunzip\", [\"-fq\", (Path.cwd/\"\\(fn).gz\").string])\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "protocol ConvertableFromByte {\n",
    "    init(_ d:UInt8)\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "extension Float : ConvertableFromByte{}\n",
    "extension Int32 : ConvertableFromByte{}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import TensorFlow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "func get_data<T:ConvertableFromByte & TensorFlowScalar>(_ fn:String, _ skip:Int) -> Tensor<T> {\n",
    "    let data = try! Data.init(contentsOf: URL.init(fileURLWithPath: fn)).dropFirst(skip)\n",
    "    return Tensor(data.map(T.init))\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "var trn_fn = \"train-images-idx3-ubyte\"\n",
    "var trn_lab_fn = \"train-labels-idx1-ubyte\"\n",
    "var val_fn = \"t10k-images-idx3-ubyte\"\n",
    "var val_lab_fn = \"t10k-labels-idx1-ubyte\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "get_file(from, trn_fn)\n",
    "get_file(from, trn_lab_fn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "get_file(from, val_fn)\n",
    "get_file(from, val_lab_fn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "var trn_arr:Tensor<Float> = get_data(trn_fn, 16)/255.0\n",
    "var trn_lab:Tensor<Int32> = get_data(trn_lab_fn, 8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "var val_arr:Tensor<Float> = get_data(val_fn, 16)/255.0\n",
    "var val_lab:Tensor<Int32> = get_data(val_lab_fn, 8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(val_lab[100..<300])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "val_lab.scalarCount"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Swift",
   "language": "swift",
   "name": "swift"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}