implement of @timeit_all

[kongdd]

Any idea how to implement the macro reported by @ffevotte https://discourse.julialang.org/t/tooling-for-line-by-line-memory-allocation-analysis/74552/6

[KristofferC]

Interesting. If you look at what a macro gets to work with:

julia> macro dumpit(ex)
           dump(ex)
           return esc(ex)
       end
@dumpit (macro with 1 method)

julia> @dumpit function f(x)
           x = 3; sin(x)
           y = 2; sin(2)
       end
Expr
  head: Symbol function
  args: Array{Any}((2,))
    1: Expr
      head: Symbol call
      args: Array{Any}((2,))
        1: Symbol f
        2: Symbol x
    2: Expr
      head: Symbol block
      args: Array{Any}((9,))
        1: LineNumberNode
          line: Int64 1
          file: Symbol REPL[14]
        2: LineNumberNode
          line: Int64 2
          file: Symbol REPL[14]
        3: Expr
          head: Symbol =
          args: Array{Any}((2,))
            1: Symbol x
            2: Int64 3
        4: LineNumberNode
          line: Int64 2
          file: Symbol REPL[14]
        5: Expr
          head: Symbol call
          args: Array{Any}((2,))
            1: Symbol sin
            2: Symbol x
        6: LineNumberNode
          line: Int64 3
          file: Symbol REPL[14]
        7: Expr
          head: Symbol =
          args: Array{Any}((2,))
            1: Symbol y
            2: Int64 2
        8: LineNumberNode
          line: Int64 3
          file: Symbol REPL[14]
        9: Expr
          head: Symbol call
          args: Array{Any}((2,))
            1: Symbol sin
            2: Int64 2
f (generic function with 1 method)

you can see there are LineNumberNodes in there. You would probably loop through each statement and for each new LineNumberNode you would insert a @timeit call.

[kongdd]

Thanks for your quick response and useful information

[kongdd]

Sorry. I still has no idea how to implement this function.

[kongdd]

This is my solution: https://github.com/jl-spatial/Ipaper.jl/blob/master/src/timeit_all.jl

julia> @timeit_all function foo(n)
         for i = 1:n
           begin
             A = randn(100, 100, 20)
             m = maximum(A)
           end
           if i < 10
             Am = mapslices(sum, A; dims=2)
             B = A[:, :, 5]
             Bsort = mapslices(B; dims=1) do col
               sort(col)
             end
           elseif i < 15
             sleep(0.01)
           else
             sleep(0.02)
           end
           let j
             j = i
             while j < 5
               b = rand(100)
               C = B .* b
               j += 1
             end
           end
         end
         sleep(0.5)
       end
foo (generic function with 1 method)

julia> foo(20)

julia> show(to, sortby = :firstexec)
 ───────────────────────────────────────────────────────────────────────────────────────────────────
                                                           Time                    Allocations      
                                                  ───────────────────────   ────────────────────────
                 Tot / % measured:                     11.8s /  13.8%            272MiB /  43.4%

 Section                                  ncalls     time    %tot     avg     alloc    %tot      avg
 ───────────────────────────────────────────────────────────────────────────────────────────────────
 L5: for                                       1    1.12s   69.0%   1.12s    118MiB  100.0%   118MiB
   L6: block                                  20    149ms    9.1%  7.43ms   30.5MiB   25.8%  1.53MiB
     L7: A = randn(100, 100, 20)              20    140ms    8.6%  6.99ms   30.5MiB   25.8%  1.53MiB
     L8: m = maximum(A)                       20   2.22ms    0.1%   111μs      640B    0.0%    32.0B
   L10: if                                    20    974ms   59.8%  48.7ms   86.9MiB   73.5%  4.34MiB
     L11: Am = mapslices(sum, A; di ...        9    435ms   26.7%  48.3ms   61.8MiB   52.3%  6.87MiB
     L12: B = A[:, :, 5]                       9    431μs    0.0%  47.8μs    704KiB    0.6%  78.2KiB
     L13: Bsort = mapslices(B; dims ...        9    278ms   17.1%  30.9ms   24.3MiB   20.6%  2.70MiB
   L21: let                                   20    506μs    0.0%  25.3μs    797KiB    0.7%  39.8KiB
     L22: j = i                               20   18.8μs    0.0%   940ns      640B    0.0%    32.0B
     L23: while                               20    411μs    0.0%  20.5μs    794KiB    0.7%  39.7KiB
       L24: b = rand(100)                     10   10.9μs    0.0%  1.09μs   9.06KiB    0.0%     928B
       L25: C = B .* b                        10    335μs    0.0%  33.5μs    782KiB    0.6%  78.2KiB
       L26: j += 1                            10   6.70μs    0.0%   670ns      320B    0.0%    32.0B
 L30: sleep(0.5)                               1    505ms   31.0%   505ms      176B    0.0%     176B
 ───────────────────────────────────────────────────────────────────────────────────────────────────