p36281094
/
topology-optimization-benchmark
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

Update README.md

This commit is contained in:
LIYu 2021-12-03 10:51:16 +08:00 committed by GitHub
parent 20cfe6b350
commit 17e8e86d99
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 2 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
README.md
View File

@ -25,7 +25,7 @@ This project aims to establish a deep neural network (DNN) surrogate modeling be
The training, test and visualization can be accessed by running `main.py` file. The training, test and visualization can be accessed by running `main.py` file.
- The data is available at the server address: `\\192.168.2.1\mnt/share1/layout_data/v1.0/data/`（refer to [Readme for samples](https://git.idrl.site/gongzhiqiang/supervised_layout_benchmark/blob/master/samples/README.md)). Remember to modify variable `data_root` in the configuration file `config/config_complex_net.yml` to the right server address. - The data is available at the server address: `\\192.168.2.1\mnt/share1/layout_data/v1.0/data/`（refer to [Readme for samples](https://github.com/idrl-lab/topology-optimization-benchmark/blob/master/samples/README.md)). Remember to modify variable `data_root` in the configuration file `config/config_complex_net.yml` to the right server address.
- Training - Training
@ -84,4 +84,4 @@ The training, test and visualization can be accessed by running `main.py` file.
One tiny example for training and testing can be accessed based on the following instruction. One tiny example for training and testing can be accessed based on the following instruction.
* Some training and testing data are available at `samples/data`. * Some training and testing data are available at `samples/data`.
* Based on the original configuration file, run `python main.py` directly for a quick experience of this tiny example. * Based on the original configuration file, run `python main.py` directly for a quick experience of this tiny example.