56 lines
1.6 KiB
Python
56 lines
1.6 KiB
Python
import glob
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import shutil
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from pathlib import Path
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from check import make_image
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def get_exps(pattern: str, splitter: str = "_", dry_run: bool = True):
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basedir = "/teamspace/jobs/"
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chkpt_basedir = "/work/colors/lightning_logs/"
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location = basedir + pattern
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res = glob.glob(location)
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location = location.replace("*", "")
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H = [] # hyperparams used
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# print(res)
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for r in res:
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d = r.replace(location, "").split(splitter)
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d = list(float(_d) for _d in d)
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d[0] = int(d[0])
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H.append(d)
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for i, r in enumerate(res):
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dir_path = Path(
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f"/teamspace/studios/this_studio/colors/lightning_logs/version_{i}/"
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)
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dir_path.mkdir(parents=True, exist_ok=True)
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g = glob.glob(r + chkpt_basedir + "*")
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logs = glob.glob(g[0] + "/events*")[-1]
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source_path = Path(logs)
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print(logs)
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if not dry_run:
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c = g[0] + "/checkpoints"
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latest_checkpoint = glob.glob(c + "/*")[-1]
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print(latest_checkpoint)
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if not dry_run:
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shutil.copy(source_path, dir_path)
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make_image(latest_checkpoint, f"out/version_{i}")
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# make_image(latest_checkpoint, f"out/version_{i}b", color=False)
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else:
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print("Would copy", source_path, dir_path)
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return H
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if __name__ == "__main__":
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D = get_exps("color_*", "_")
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import numpy as np
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D = np.array(D)
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# print(len(D), "\n", D)
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import pandas as pd
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df = pd.DataFrame(D)
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df.columns = ["batch_size", "alpha", "learning_rate"]
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df.to_csv("experiments.csv")
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print(df)
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