Model params 46 MB
Estimates for a single full pass of model at input size 224 x 224:
- Memory required for features: 43 MB
- Flops: 2 GFLOPs
Estimates are given below of the burden of computing the inception_5b_scale features in the network for different input sizes using a batch size of 128:
| input size | feature size | feature memory | flops |
|---|---|---|---|
| 224 x 224 | 7 x 7 x 1024 | 5 GB | 262 GFLOPs |
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:
