Numerical differences in OD evaluation (in 5.8 and 6.0) on CPU and GPU

[srikris]

For evaluation of an object detector, there are some slight variance between the

In version 5.8, we have

## MPS
Out[4]:
{'average_precision_50': {'Bagel': 0.8520384669200912,
  'Banana': 0.8575615741065546,
  'Coffee': 0.5958508158508159,
  'Croissant': 0.7764094658504597,
  'Egg': 0.6904679838895471,
  'Waffle': 0.719937989567849},
 'mean_average_precision_50': 0.7487110493642196}

## MXNET
Out[6]:
{'average_precision_50': {'Bagel': 0.852246094152459,
  'Banana': 0.8586351107478006,
  'Coffee': 0.5961538461538463,
  'Croissant': 0.7625511019920956,
  'Egg': 0.6781562921839436,
  'Waffle': 0.6855548346869123},
 'mean_average_precision_50': 0.7388828799861763}

and in version 6.0, we have

## MPS
{'average_precision_50': {'Coffee': 0.5881511569023132, 
  'Croissant': 0.7716814875602722, 
  'Waffle': 0.6675131916999817, 
  'Bagel': 0.8474096059799194, 
  'Egg': 0.6781503558158875, 
  'Banana': 0.8502914309501648}, 
'mean_average_precision_50': 0.7338662147521973}

## TF
{'average_precision_50': {'Coffee': 0.5817939043045044, 
  'Croissant': 0.7605029940605164, 
  'Waffle': 0.6415750980377197, 
  'Bagel': 0.8460806012153625, 
  'Egg': 0.6689953804016113, 
  'Banana': 0.8549931645393372}, 
'mean_average_precision_50': 0.7256568074226379}