Model params 196 MB
Estimates for a single full pass of model at input size 368 x 368:
- Memory required for features: 245 MB
- Flops: 134 GFLOPS
Estimates are given below of the burden of computing the Mconv6_stage6_L2 features in the network for different input sizes using a batch size of 128:
| input size | feature size | feature memory | flops |
|---|---|---|---|
| 184 x 184 | 23 x 23 x 128 | 7 GB | 4 TFLOPS |
| 368 x 368 | 46 x 46 x 128 | 30 GB | 16 TFLOPS |
| 552 x 552 | 69 x 69 x 128 | 67 GB | 36 TFLOPS |
| 736 x 736 | 92 x 92 x 128 | 119 GB | 64 TFLOPS |
| 920 x 920 | 115 x 115 x 128 | 185 GB | 100 TFLOPS |
| 1104 x 1104 | 138 x 138 x 128 | 267 GB | 144 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:
