This PR adds several improvements for data processing to the random designer:
A timer to recycle Fusion after 5 minutes on any one design generation
Ability to run multiple random designers in parallel on the same machine
Pass arguments to the random designer
Only select from training set sketches
Usage
usage: random_designer.py [-h] [--input INPUT] [--split SPLIT]
[--output OUTPUT] [--machine_id MACHINE_ID]
[--host HOST] [--port PORT]
optional arguments:
-h, --help show this help message and exit
--input INPUT File or folder containing the dataset [default: d7]
--split SPLIT Train/test split file from which to select train
sketches only [default: train_test.json]
--output OUTPUT Folder to save the output to [default:
generated_design]
--machine_id MACHINE_ID
Machine id used in file names [default: 2]
--host HOST Host name to launch Fusion Gym on [default: 127.0.0.1]
--port PORT Port number to launch Fusion Gym on [default: 8080]
For example, to run multiple at the same time you would do something like this in one terminal:
Note that the code now assumes Fusion is not running, and the gym server is set to run on startup.
In general you can run up to ~8 instances on the same computer depending on its specs.
This PR adds several improvements for data processing to the random designer:
Usage
For example, to run multiple at the same time you would do something like this in one terminal:
Then in another terminal:
Note that the code now assumes Fusion is not running, and the gym server is set to run on startup. In general you can run up to ~8 instances on the same computer depending on its specs.