In many cases, including hyperparameter search, we want to check whether the same config has been already finished or not, This is a short examples for checking it when we uses wandb as a backend.

args_to_wandb_query.py

""" Argparser to wandb query. 

References
----------
Short tutorial: https://docs.wandb.ai/ref/export-api
Wandb API: https://docs.wandb.ai/ref/export-api/api
  - Api.runs
  - RUN class
Mongodb query: https://docs.mongodb.com/manual/reference/operator/query/
"""

import argparse
import wandb


# Argparser
parser = argparse.ArgumentParser(description='NAM Example')
parser.add_argument('--batch-size', type=int, default=128, metavar='N',
                    help='input batch size for training (default: 128)')
parser.add_argument('--epochs', type=int, default=10, metavar='N',
                    help='number of epochs to train (default: 10)')
parser.add_argument('--no-cuda', action='store_true', default=False,
                    help='disables CUDA training')
parser.add_argument('--seed', type=int, default=1, metavar='S',
                    help='random seed (default: 1)')
parser.add_argument('--log-interval', type=int, default=10, metavar='N',
                    help='how many batches to wait before logging training status')
args = parser.parse_args()

# Wandb
project_path = "{user_name}/{project_name}"
api = wandb.Api()
query = [{"config." + str(key): val} for key, val in vars(args).items()]
query.append({"state": {'$in': ["finished", "running"]}})  # You can also add state condition. The strings may be depend on the version of wandb. 
runs = api.runs(project_path, {'$and': query})

exist_same_exp = len(runs) > 0  # You can check if the same experiments has been started/finished or not