A Python package that provides LLM-powered naming.
Currently supports automatically naming experiments using information from parser and args (from argparse).
Implemented using APPL.
pip install autonamingfrom argparse import ArgumentParser
from autonaming.exps import name_this_exp
# Create your argument parser as usual
parser = ArgumentParser()
parser.add_argument("--learning_rate", type=float, default=0.001, help="Learning rate for training")
parser.add_argument("--batch_size", type=int, default=32, help="Batch size for training")
parser.add_argument("--model", type=str, default="resnet18", help="Model architecture")
# Parse your arguments
args = parser.parse_args(["--learning_rate", "0.01", "--model", "alexnet"])
# Generate an informative name for your experiment
name = name_this_exp(parser, args, add_timestamp=True)
# Example output: alexnet_lr0.01_bs32__2024_12_11__12_34_56
# You can use this name to name your experiment directory- Generate a descriptive and concise name in snake_case that captures the key parameters
- Keep names under 100 characters
- Include the most important parameters that distinguish this experiment
- Use standard abbreviations where appropriate (e.g. lr for learning_rate)
- Order parameters from most to least important