mmpretrain/docs/en/useful_tools/complexity_analysis.md

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# Model Complexity Analysis
## Get the FLOPs and params (experimental)
We provide a script adapted from [fvcore](https://github.com/facebookresearch/fvcore/blob/main/fvcore/nn/flop_count.py) to compute the FLOPs and params of a given model.
```shell
python tools/analysis_tools/get_flops.py ${CONFIG_FILE} [--shape ${INPUT_SHAPE}]
```
Description of all arguments:
- `config` : The path of the model config file.
- `--shape`: Input size, support single value or double value parameter, such as `--shape 256` or `--shape 224 256`. If not set, default to be `224 224`.
You will get the final result like this.
```text
==============================
Input shape: (3, 224, 224)
Flops: 17.582G
Params: 91.234M
Activation: 23.895M
==============================
```
Also, you will get the detailed complexity information of each layer like this:
```text
| module | #parameters or shape | #flops | #activations |
|:------------------------------------------|:-----------------------|:----------|:---------------|
| model | 91.234M | 17.582G | 23.895M |
| backbone | 85.799M | 17.582G | 23.895M |
| backbone.cls_token | (1, 1, 768) | | |
| backbone.pos_embed | (1, 197, 768) | | |
| backbone.patch_embed.projection | 0.591M | 0.116G | 0.151M |
| backbone.patch_embed.projection.weight | (768, 3, 16, 16) | | |
| backbone.patch_embed.projection.bias | (768,) | | |
| backbone.layers | 85.054M | 17.466G | 23.744M |
| backbone.layers.0 | 7.088M | 1.455G | 1.979M |
| backbone.layers.1 | 7.088M | 1.455G | 1.979M |
| backbone.layers.2 | 7.088M | 1.455G | 1.979M |
| backbone.layers.3 | 7.088M | 1.455G | 1.979M |
| backbone.layers.4 | 7.088M | 1.455G | 1.979M |
| backbone.layers.5 | 7.088M | 1.455G | 1.979M |
| backbone.layers.6 | 7.088M | 1.455G | 1.979M |
| backbone.layers.7 | 7.088M | 1.455G | 1.979M |
| backbone.layers.8 | 7.088M | 1.455G | 1.979M |
| backbone.layers.9 | 7.088M | 1.455G | 1.979M |
| backbone.layers.10 | 7.088M | 1.455G | 1.979M |
| backbone.layers.11 | 7.088M | 1.455G | 1.979M |
| backbone.ln1 | 1.536K | 0.756M | 0 |
| backbone.ln1.weight | (768,) | | |
| backbone.ln1.bias | (768,) | | |
| head.layers | 5.435M | | |
| head.layers.pre_logits | 2.362M | | |
| head.layers.pre_logits.weight | (3072, 768) | | |
| head.layers.pre_logits.bias | (3072,) | | |
| head.layers.head | 3.073M | | |
| head.layers.head.weight | (1000, 3072) | | |
| head.layers.head.bias | (1000,) | | |
```
```{warning}
This tool is still experimental and we do not guarantee that the number is correct. You may well use the result for simple comparisons, but double-check it before you adopt it in technical reports or papers.
- FLOPs are related to the input shape while parameters are not. The default input shape is (1, 3, 224, 224).
- Some operators are not counted into FLOPs like custom operators. Refer to [`fvcore.nn.flop_count._DEFAULT_SUPPORTED_OPS`](https://github.com/facebookresearch/fvcore/blob/main/fvcore/nn/flop_count.py) for details.
```