Scott Wolchok swolchok

## untrusted-lvl13-lazy-solution.js
/*
 * robotMaze.js
 *
 * The blue key is inside a labyrinth, and extracting
 * it will not be easy.
 *
 * It's a good thing that you're a AI expert, or
 * we would have to leave empty-handed.
 */

## prof100k.txt
Flat profile:

Each sample counts as 0.01 seconds.
  %   cumulative   self              self     total
 time   seconds   seconds    calls   s/call   s/call  name
 72.28     21.82    21.82 47800000     0.00     0.00  camlDefault_Tar__Layout__layoutNodeImpl_1039
 10.67     25.04     3.22 13800000     0.00     0.00  camlDefault_Tar__Layout__layoutNode_1161
  6.64     27.05     2.01 40900001     0.00     0.00  caml_obj_dup
  4.27     28.34     1.29 61600000     0.00     0.00  camlDefault_Tar__Layout__layoutNodeInternal_1038
  2.48     29.09     0.75   100000     0.00     0.00  camlDefault_Tar__LayoutTestFixedEncoding__fun_3905

## baseline.txt
Nesting level: 1
output: Dict[str, Tuple[str, str]]
<torch.utils.benchmark.utils.common.Measurement object at 0x7f7bcb854f40>
x.annotation_str
  Median: 19.34 us
  IQR:    0.81 us (19.02 to 19.83)
  101 measurements, 100 runs per measurement, 1 thread
Nesting level: 3
output: Dict[str, Tuple[Dict[str, Tuple[Dict[str, Tuple[str, str]], Dict[str,
<torch.utils.benchmark.utils.common.Measurement object at 0x7f7bcb854e80>

## tupleopt.txt
Nesting level: 1
output: Dict[str, Tuple[str, str]]
<torch.utils.benchmark.utils.common.Measurement object at 0x7f6969bb1f40>
x.annotation_str
  Median: 18.42 us
  IQR:    1.04 us (17.86 to 18.90)
  108 measurements, 100 runs per measurement, 1 thread
Nesting level: 3
output: Dict[str, Tuple[Dict[str, Tuple[Dict[str, Tuple[str, str]], Dict[str,
<torch.utils.benchmark.utils.common.Measurement object at 0x7f6969bb1e80>

## gist:8bd4ca61e156827f23bb54ca3b48d54f
Nesting level: 1
output: Dict[str, Tuple[str, str]]
<torch.utils.benchmark.utils.common.Measurement object at 0x7f8a3a31ff40>
x.annotation_str
  Median: 20.85 us
  IQR:    0.67 us (20.55 to 21.22)
  95 measurements, 100 runs per measurement, 1 thread
Nesting level: 3
output: Dict[str, Tuple[Dict[str, Tuple[Dict[str, Tuple[str, str]], Dict[str,
<torch.utils.benchmark.utils.common.Measurement object at 0x7f8a3a31fe80>
	/*
	* robotMaze.js
	*
	* The blue key is inside a labyrinth, and extracting
	* it will not be easy.
	*
	* It's a good thing that you're a AI expert, or
	* we would have to leave empty-handed.
	*/
	Flat profile:

	Each sample counts as 0.01 seconds.
	% cumulative self self total
	time seconds seconds calls s/call s/call name
	72.28 21.82 21.82 47800000 0.00 0.00 camlDefault_Tar__Layout__layoutNodeImpl_1039
	10.67 25.04 3.22 13800000 0.00 0.00 camlDefault_Tar__Layout__layoutNode_1161
	6.64 27.05 2.01 40900001 0.00 0.00 caml_obj_dup
	4.27 28.34 1.29 61600000 0.00 0.00 camlDefault_Tar__Layout__layoutNodeInternal_1038
	2.48 29.09 0.75 100000 0.00 0.00 camlDefault_Tar__LayoutTestFixedEncoding__fun_3905
	Nesting level: 1
	output: Dict[str, Tuple[str, str]]
	<torch.utils.benchmark.utils.common.Measurement object at 0x7f7bcb854f40>
	x.annotation_str
	Median: 19.34 us
	IQR: 0.81 us (19.02 to 19.83)
	101 measurements, 100 runs per measurement, 1 thread
	Nesting level: 3
	output: Dict[str, Tuple[Dict[str, Tuple[Dict[str, Tuple[str, str]], Dict[str,
	<torch.utils.benchmark.utils.common.Measurement object at 0x7f7bcb854e80>