Add pt compression doc (deepmodeling#4299)

<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

- **New Features**
- Added support for the PyTorch backend alongside TensorFlow in the
documentation.
- Introduced a new command for compressing models using PyTorch: `dp
compress -i model.pth -o model-compress.pth`.

- **Documentation**
	- Updated the header to reflect both TensorFlow and PyTorch support.
- Enhanced instructions section with clear guidance for users of both
frameworks.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

doc/freeze/compress.md

@@ -1,7 +1,7 @@
-# Compress a model {{ tensorflow_icon }}
+# Compress a model {{ tensorflow_icon }} {{ pytorch_icon }}
 
 :::{note}
-**Supported backends**: TensorFlow {{ tensorflow_icon }}
+**Supported backends**: TensorFlow {{ tensorflow_icon }}, PyTorch {{ pytorch_icon }}
 :::
 
 ## Theory
@@ -64,10 +64,25 @@ In the compressed DP model, the number of neighbors is precisely indexed at the
 
 Once the frozen model is obtained from DeePMD-kit, we can get the neural network structure and its parameters (weights, biases, etc.) from the trained model, and compress it in the following way:
 
+::::{tab-set}
+
+:::{tab-item} TensorFlow {{ tensorflow_icon }}
+
 ```bash
 dp compress -i graph.pb -o graph-compress.pb
 ```
 
+:::
+
+:::{tab-item} PyTorch {{ pytorch_icon }}
+
+```bash
+dp compress -i model.pth -o model-compress.pth
+```
+
+:::
+::::
+
 where `-i` gives the original frozen model, `-o` gives the compressed model. Several other command line options can be passed to `dp compress`, which can be checked with
 
 ```bash