Add new training loop with PyTorch Lightning, remove stale files

1 files changed, 0 insertions, 92 deletions

diff --git a/training/run_sweep.py b/training/run_sweep.py
deleted file mode 100644
index a578592..0000000
--- a/training/run_sweep.py
+++ /dev/null
@@ -1,92 +0,0 @@
-"""W&B Sweep Functionality."""
-from ast import literal_eval
-import json
-import os
-from pathlib import Path
-import signal
-import subprocess  # nosec
-import sys
-from typing import Dict, List, Tuple
-
-import click
-import yaml
-
-EXPERIMENTS_DIRNAME = Path(__file__).parents[0].resolve() / "experiments"
-
-
-def load_config() -> Dict:
-    """Load base hyperparameter config."""
-    with open(str(EXPERIMENTS_DIRNAME / "default_config_emnist.yml"), "r") as f:
-        default_config = yaml.safe_load(f)
-    return default_config
-
-
-def args_to_json(
-    default_config: dict, preserve_args: tuple = ("gpu", "save")
-) -> Tuple[dict, list]:
-    """Convert command line arguments to nested config values.
-
-    i.e. run_sweep.py --dataset_args.foo=1.7
-    {
-        "dataset_args": {
-            "foo": 1.7
-        }
-    }
-
-    Args:
-        default_config (dict): The base config used for every experiment.
-        preserve_args (tuple): Arguments preserved for all runs. Defaults to ("gpu", "save").
-
-    Returns:
-        Tuple[dict, list]: Tuple of config dictionary and list of arguments.
-
-    """
-
-    args = []
-    config = default_config.copy()
-    key, val = None, None
-    for arg in sys.argv[1:]:
-        if "=" in arg:
-            key, val = arg.split("=")
-        elif key:
-            val = arg
-        else:
-            key = arg
-        if key and val:
-            parsed_key = key.lstrip("-").split(".")
-            if parsed_key[0] in preserve_args:
-                args.append("--{}={}".format(parsed_key[0], val))
-            else:
-                nested = config
-                for level in parsed_key[:-1]:
-                    nested[level] = config.get(level, {})
-                    nested = nested[level]
-                try:
-                    # Convert numerics to floats / ints
-                    val = literal_eval(val)
-                except ValueError:
-                    pass
-                nested[parsed_key[-1]] = val
-            key, val = None, None
-    return config, args
-
-
-def main() -> None:
-    """Runs a W&B sweep."""
-    default_config = load_config()
-    config, args = args_to_json(default_config)
-    env = {
-        k: v for k, v in os.environ.items() if k not in ("WANDB_PROGRAM", "WANDB_ARGS")
-    }
-    # pylint: disable=subprocess-popen-preexec-fn
-    run = subprocess.Popen(
-        ["python", "training/run_experiment.py", *args, json.dumps(config)],
-        env=env,
-        preexec_fn=os.setsid,
-    )  # nosec
-    signal.signal(signal.SIGTERM, lambda *args: run.terminate())
-    run.wait()
-
-
-if __name__ == "__main__":
-    main()