mirror of
https://github.com/NicolasBohn/NexQuant.git
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77 lines
2.7 KiB
Python
77 lines
2.7 KiB
Python
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"""
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This module provides some useful functions for working with logger folders.
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"""
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import pickle
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from pathlib import Path
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import pandas as pd
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from rdagent.utils.workflow import LoopBase
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def get_first_session_file_after_duration(log_folder: str | Path, duration: str | pd.Timedelta) -> Path:
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log_folder = Path(log_folder)
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duration_dt = pd.Timedelta(duration)
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# iterate the dump steps in increasing order
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files = sorted(
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(log_folder / "__session__").glob("*/*_*"), key=lambda f: (int(f.parent.name), int(f.name.split("_")[0]))
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)
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fp = None
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for fp in files:
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with fp.open("rb") as f:
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session_obj: LoopBase = pickle.load(f)
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timer = session_obj.timer
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all_duration = timer.all_duration
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remain_time_duration = timer.remain_time_duration
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if all_duration is None or remain_time_duration is None:
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msg = "Timer is not configured"
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raise ValueError(msg)
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time_spent = all_duration - remain_time_duration
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if time_spent >= duration_dt:
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break
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if fp is None:
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msg = f"No session file found after duration {duration}"
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raise ValueError(msg)
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return fp
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def first_li_si_after_one_time(log_path: Path, hours: int = 12) -> tuple[int, int, str]:
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"""
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Based on the hours, find the stop loop id and step id (the first step after <hours> hours).
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Args:
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log_path (Path): The path to the log folder (contains many log traces).
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hours (int): The number of hours to stat.
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Returns:
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tuple[int, int, str]: The loop id, step id and function name.
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"""
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session_path = log_path / "__session__"
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max_li = max(int(p.name) for p in session_path.iterdir() if p.is_dir() and p.name.isdigit())
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max_step = max(int(p.name.split("_")[0]) for p in (session_path / str(max_li)).iterdir() if p.is_file())
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rdloop_obj_p = next((session_path / str(max_li)).glob(f"{max_step}_*"))
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rdloop_obj = DataScienceRDLoop.load(rdloop_obj_p, do_truncate=False)
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loop_trace = rdloop_obj.loop_trace
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si2fn = rdloop_obj.steps
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duration = timedelta(seconds=0)
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for li, lts in loop_trace.items():
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for lt in lts:
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si = lt.step_idx
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duration += lt.end - lt.start
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if duration > timedelta(hours=hours):
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return li, si, si2fn[si]
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if __name__ == "__main__":
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from rdagent.app.data_science.loop import DataScienceRDLoop
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f = get_first_session_file_after_duration("<path to log aptos2019-blindness-detection>", pd.Timedelta("12h"))
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with f.open("rb") as f:
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session_obj: LoopBase = pickle.load(f)
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loop_trace = session_obj.loop_trace
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last_loop = loop_trace[max(loop_trace.keys())]
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last_step = last_loop[-1]
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session_obj.steps[last_step.step_idx]
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