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Report for ssd-pascal-mobilenet-ft

Model params 22 MB

Estimates for a single full pass of model at input size 300 x 300:

  • Memory required for features: 37 MB
  • Flops: 1 GFLOPs

Estimates are given below of the burden of computing the conv17_2_relu features in the network for different input sizes using a batch size of 128:

input size feature size feature memory flops
150 x 150 1 x 1 x 128 1 GB 39 GFLOPs
300 x 300 1 x 1 x 128 4 GB 146 GFLOPs
450 x 450 1 x 1 x 128 10 GB 336 GFLOPs
600 x 600 2 x 2 x 128 17 GB 574 GFLOPs
750 x 750 2 x 2 x 128 27 GB 890 GFLOPs
900 x 900 2 x 2 x 128 39 GB 1 TFLOPs

A rough outline of where in the network memory is allocated to parameters and features and where the greatest computational cost lies is shown below. The x-axis does not show labels (it becomes hard to read for networks containing hundreds of layers) - it should be interpreted as depicting increasing depth from left to right. The goal is simply to give some idea of the overall profile of the model:

ssd-pascal-mobilenet-ft profile

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