Improve save_for_mobile cxx binary (#43721)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/43721
We can combine optimization pass and save_for_mobile together to reduce friction. Since lite interpreter model can also be used in full JIT, I don't think we need the option to save it as full JIT model.
Also
- improved usage message
- print op list before and after optimization pass
Test Plan:
```
buck run //xplat/caffe2:optimize_for_mobile -- --model=/home/linbin/sparkspot.pt
Building: finished in 12.4 sec (100%) 2597/2597 jobs, 2 updated
Total time: 12.5 sec
pt_operator_library(
name = "old_op_library",
ops = [
"aten::_convolution",
"aten::adaptive_avg_pool2d",
"aten::add_.Tensor",
"aten::batch_norm",
"aten::mul.Tensor",
"aten::relu_",
"aten::softplus",
"aten::sub.Tensor",
],
)
pt_operator_library(
name = "new_op_library",
ops = [
"aten::adaptive_avg_pool2d",
"aten::add_.Tensor",
"aten::batch_norm",
"aten::mul.Tensor",
"aten::relu_",
"aten::softplus",
"aten::sub.Tensor",
"prepacked::conv2d_clamp_run",
],
)
The optimized model for lite interpreter was saved to /home/linbin/sparkspot_mobile_optimized.bc
```
```
buck run //xplat/caffe2:optimize_for_mobile -- --model=/home/linbin/sparkspot.pt --backend=vulkan
```
Reviewed By: kimishpatel
Differential Revision: D23363533
fbshipit-source-id: f7fd61aaeda5944de5bf198e7f93cacf8368babd
