<div align="center">
<h1>EasyRunner</h1>
</div>
<div align="center">
<a></a>
[](#license)
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</div>
---
EasyRunner is a lightweight tool for managing and executing multiple parallel experiments. It simplifies the process of running multiple experiments with different configurations or hyperparameters, while monitoring system resources.
## Features
- Run multiple experiments in parallel
- Monitor system resources (CPU and memory usage) during experiments
- Early termination of experiments by inputting the experiment number
- Colorized display of experiment status and resource usage
- Generate a list of instructions from a template and arguments
## Installation
To use EasyRunner, simply download or clone this repository and then:
```
pip install -e .
```
## Usage
1. Initialize an `EasyRunner` object with the required parameters.
2. Specificy a list of commandline instructions to run.
3. Use the `start` method to run experiments. You can specify a list of GPU IDs for running experiments (or `None` by default).
3. Optionally, use the `compose` method to generate a list of instructions from a template and arguments.
A simple example for running a list of instructions (2 parallel) on cuda 0, 1:
```python
from easy_runner import EasyRunner
# Initialize the EasyRunner
runner = EasyRunner(log_name="experiment_logs")
# Create a list of instructions
instructions = [
"python script1.py --param1 0.1 --param2 100",
"python script1.py --param1 0.2 --param2 200",
"python script2.py --param1 0.3 --param2 300",
"python script2.py --param1 0.4 --param2 400",
"python script3.py --param1 0.5 --param2 500"
]
# Run experiments
runner.start(instructions, gpus=[0, 1], max_parallel=2)
```
Anoter example of how to use the `compose` feature to perform grid search:
```python
from easy_runner import EasyRunner
# Initialize the EasyRunner
runner = EasyRunner(log_name="experiment_logs")
# List of seeds, and tasks
seeds = [0, 10, 20]
tasks = ["TaskA-v0 --epoch 30", "TaskB-v0 --epoch 150", "TaskC-v0 --epoch 80"]
# Define the command template
template = "nohup python train_script.py --project my_project --seed {} --task {} "
# Generate a list of instructions using the compose method
instructions = runner.compose(template, [agents, seeds, tasks])
# Run the experiments
runner.start(instructions, max_parallel=4)
```
You can try the example scripts in the `examples` folder:
```bash
cd examples
python test_easy_runner.py
```
Demo video:
<div align="center">
<img width="600px" height="auto" src="https://github.com/liuzuxin/easy-runner/raw/main/examples/demo.gif">
</div>
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
## Contributing
We welcome contributions to the Experiment Grid Tool. Please open an issue or submit a pull request on the GitHub repository.
Feel free to customize this template according to your specific requirements or add any additional information you think would be helpful for users.
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"description": "<div align=\"center\">\n <h1>EasyRunner</h1>\n</div>\n<div align=\"center\">\n\n <a></a>\n [](#license)\n [](https://pypi.org/project/dsrl)\n <!-- [](https://github.com/liuzuxin/dsrl/stargazers) -->\n <!-- [](https://pepy.tech/project/dsrl) -->\n <!-- [](https://fsrl.readthedocs.io) -->\n <!-- [](https://codecov.io/github/liuzuxin/fsrl)\n [](https://github.com/liuzuxin/fsrl/actions/workflows/test.yml) -->\n <!-- [](https://app.codecov.io/gh/liuzuxin/fsrl) -->\n <!-- [](https://github.com/liuzuxin/fsrl/tree/HEAD/tests) -->\n \n</div>\n\n---\n\nEasyRunner is a lightweight tool for managing and executing multiple parallel experiments. It simplifies the process of running multiple experiments with different configurations or hyperparameters, while monitoring system resources.\n\n## Features\n\n- Run multiple experiments in parallel\n- Monitor system resources (CPU and memory usage) during experiments\n- Early termination of experiments by inputting the experiment number\n- Colorized display of experiment status and resource usage\n- Generate a list of instructions from a template and arguments\n\n## Installation\n\nTo use EasyRunner, simply download or clone this repository and then:\n\n```\npip install -e .\n```\n\n## Usage\n\n1. Initialize an `EasyRunner` object with the required parameters.\n2. Specificy a list of commandline instructions to run.\n3. Use the `start` method to run experiments. You can specify a list of GPU IDs for running experiments (or `None` by default).\n3. Optionally, use the `compose` method to generate a list of instructions from a template and arguments.\n\nA simple example for running a list of instructions (2 parallel) on cuda 0, 1:\n\n```python\nfrom easy_runner import EasyRunner\n\n# Initialize the EasyRunner\nrunner = EasyRunner(log_name=\"experiment_logs\")\n\n# Create a list of instructions\ninstructions = [\n \"python script1.py --param1 0.1 --param2 100\",\n \"python script1.py --param1 0.2 --param2 200\",\n \"python script2.py --param1 0.3 --param2 300\",\n \"python script2.py --param1 0.4 --param2 400\",\n \"python script3.py --param1 0.5 --param2 500\"\n]\n\n# Run experiments\nrunner.start(instructions, gpus=[0, 1], max_parallel=2)\n```\n\nAnoter example of how to use the `compose` feature to perform grid search:\n\n```python\nfrom easy_runner import EasyRunner\n\n# Initialize the EasyRunner\nrunner = EasyRunner(log_name=\"experiment_logs\")\n\n# List of seeds, and tasks\nseeds = [0, 10, 20]\ntasks = [\"TaskA-v0 --epoch 30\", \"TaskB-v0 --epoch 150\", \"TaskC-v0 --epoch 80\"]\n\n# Define the command template\ntemplate = \"nohup python train_script.py --project my_project --seed {} --task {} \"\n\n# Generate a list of instructions using the compose method\ninstructions = runner.compose(template, [agents, seeds, tasks])\n\n# Run the experiments\nrunner.start(instructions, max_parallel=4)\n```\n\nYou can try the example scripts in the `examples` folder:\n```bash\ncd examples\npython test_easy_runner.py\n```\n\nDemo video:\n<div align=\"center\">\n <img width=\"600px\" height=\"auto\" src=\"https://github.com/liuzuxin/easy-runner/raw/main/examples/demo.gif\">\n</div>\n\n## License\n\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.\n\n## Contributing\n\nWe welcome contributions to the Experiment Grid Tool. Please open an issue or submit a pull request on the GitHub repository.\n\n\nFeel free to customize this template according to your specific requirements or add any additional information you think would be helpful for users.\n",
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