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vgg-m-1024.md

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Report for vgg-m-1024

Model params 333 MB

Estimates for a single full pass of model at input size 224 x 224:

  • Memory required for features: 12 MB
  • Flops: 2 GFLOPs

Estimates are given below of the burden of computing the pool5 features in the network for different input sizes using a batch size of 128:

input size feature size feature memory flops
112 x 112 3 x 3 x 512 365 MB 44 GFLOPs
224 x 224 6 x 6 x 512 2 GB 204 GFLOPs
336 x 336 10 x 10 x 512 4 GB 480 GFLOPs
448 x 448 13 x 13 x 512 6 GB 874 GFLOPs
560 x 560 17 x 17 x 512 10 GB 1 TFLOPs
672 x 672 20 x 20 x 512 15 GB 2 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:

vgg-m-1024 profile