Using Cassette to pull out information about creation of Vectors.

demo.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "using Pkg\n",
    "pkg\"add Cassette\"\n",
    "pkg\"add DataVoyager\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "using Dates\n",
    "using Random\n",
    "using LinearAlgebra\n",
    "using Cassette"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Cassette.Context{nametype(VecTrack6),M,P,T,B} where B<:Union{Nothing, IdDict{Module,Dict{Symbol,BindingMeta}}} where P<:Cassette.AbstractPass where T<:Union{Nothing, Tag} where M"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Cassette.@context VecTrack6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "function track!(tracker::AbstractDict{UInt64, Any}, item, action, f)\n",
    "    id = objectid(item)\n",
    "    \n",
    "    notes = get!(tracker, id) do\n",
    "        []\n",
    "    end\n",
    "    \n",
    "    push!(notes, \n",
    "        ( # Can't put too much in here, as need to make sure not to leak memory\n",
    "            timestamp=now(),\n",
    "            action = action,\n",
    "            func = f,\n",
    "            length = length(item),\n",
    "            kind = typeof(item)\n",
    "        )\n",
    "    )\n",
    "end\n",
    "\n",
    "function Cassette.posthook(ctx::VecTrack6, output::AbstractArray, f, args...)\n",
    "    tracker = ctx.metadata\n",
    "\n",
    "    if output isa AbstractArray\n",
    "        track!(tracker, output, :output, f)\n",
    "    end\n",
    "end\n",
    "#= add this to track usage too, but very slow\n",
    "function Cassette.execute(ctx::VecTrack6, f, args...)\n",
    "    output = Cassette.@overdub(ctx, f(args...))\n",
    "\n",
    "    tracker = ctx.metadata\n",
    "    vec_inputs = Iterators.filter(x -> x isa AbstractArray, args)\n",
    "\n",
    "    for input in vec_inputs\n",
    "        track!(tracker, input, :input, f)\n",
    "    end\n",
    "\n",
    "    if output isa AbstractArray\n",
    "        track!(tracker, output, :output, f)\n",
    "    end\n",
    "    \n",
    "    return output\n",
    "end\n",
    "=#"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Results of Optimization Algorithm\n",
       " * Algorithm: BFGS\n",
       " * Starting Point: [0.0,0.0]\n",
       " * Minimizer: [0.9999999926033423,0.9999999852005353]\n",
       " * Minimum: 5.471433e-17\n",
       " * Iterations: 16\n",
       " * Convergence: true\n",
       "   * |x - x'| ≤ 0.0e+00: false \n",
       "     |x - x'| = 3.47e-07 \n",
       "   * |f(x) - f(x')| ≤ 0.0e+00 |f(x)|: false\n",
       "     |f(x) - f(x')| = 1.20e+03 |f(x)|\n",
       "   * |g(x)| ≤ 1.0e-08: true \n",
       "     |g(x)| = 2.33e-09 \n",
       "   * Stopped by an increasing objective: false\n",
       "   * Reached Maximum Number of Iterations: false\n",
       " * Objective Calls: 53\n",
       " * Gradient Calls: 53"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "using Optim\n",
    "rosenbrock(x) =  (1.0 - x[1])^2 + 100.0 * (x[2] - x[1]^2)^2\n",
    "\n",
    "\n",
    "ctx = VecTrack6(metadata=Dict{UInt64, Any}())\n",
    "Cassette.@overdub ctx optimize(rosenbrock, zeros(2), BFGS())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "using DataVoyager\n",
    "using DataFrames\n",
    "using Query\n",
    "using QueryOperators"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Voyager(Electron.Window(Application(Base.PipeEndpoint(RawFD(0x00000035) paused, 0 bytes waiting), Process(`\u001b[4m/Users/oxinabox/.julia/packages/Electron/IV1np/src/../deps/electron/Julia.app/Contents/MacOS/Julia\u001b[24m \u001b[4m/Users/oxinabox/.julia/packages/Electron/IV1np/src/main.js\u001b[24m \u001b[4m/var/folders/1r/4cjj1xk90qbb6njj7dn_cmt40000gn/T/juliaelectron-65678-1\u001b[24m \u001b[4m/var/folders/1r/4cjj1xk90qbb6njj7dn_cmt40000gn/T/juliaelectron-sysnotify-65678-1\u001b[24m \u001b[4mxHk4nMv/Mmz1Nar4h/Iub9t+6DGlp0DtfrIufx+cSCdxoEpjqjoFn4wRvu4ZCos+2IyCF+qoqisyr+0zGBAspGpYWdELE6JpCFvYkOs9CzIIvrAyk0zV9qdd4kzhlV3iyWo0ZILgLQvhmXfsEqr/90vsAat8yEqxiBp1rWtnW1g=\u001b[24m`, ProcessRunning), [1 window]), 1, true, Channel{Any}(sz_max:128,sz_curr:0)))"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "safe_data = @from log in ctx.metadata begin\n",
    "    @from ii in log.second\n",
    "    @select {\n",
    "        id = log.first,\n",
    "        ii.timestamp,\n",
    "        ii.action,\n",
    "        func=string(ii.func),\n",
    "        kind=string(ii.kind),\n",
    "        ii.length}\n",
    "    @collect \n",
    "end\n",
    "\n",
    "dt = NamedTuple{\n",
    "    (:id, :timestamp, :action, :func, :kind, :length),\n",
    "    Tuple{UInt64, DateTime,Symbol,String, String,Int64}\n",
    "}\n",
    "convert(Vector{dt}, safe_data) |> Voyager\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NamedTuple{(:timestamp, :action, :func, :length),Tuple{DateTime,Symbol,Any,Int64}}"
      ]
     },
     "execution_count": 212,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Julia 1.0.2",
   "language": "julia",
   "name": "julia-1.0"
  },
  "language_info": {
   "file_extension": ".jl",
   "mimetype": "application/julia",
   "name": "julia",
   "version": "1.0.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}