mirror of
https://github.com/NicolasBohn/NexQuant.git
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you-n-g
2d4e9c41fc
* scen * scen2 * app * fix * Simplify workflow * We can share more code in new scenarios * rename model to rd loop * Optimize data path * Update rdagent/app/data_mining/model.py * Add TODO * Support GPU * gpu --------- Co-authored-by: SH-Src <suhan.c@outlook.com>
128 lines
4.4 KiB
Python
128 lines
4.4 KiB
Python
"""
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This is a class that try to store/resume/traceback the workflow session
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Postscripts:
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- Originally, I want to implement it in a more general way with python generator.
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However, Python generator is not picklable (dill does not support pickle as well)
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"""
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from pathlib import Path
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import pickle
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from tqdm.auto import tqdm
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from collections import defaultdict
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from dataclasses import dataclass, field
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import datetime
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from typing import Callable
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from rdagent.log import rdagent_logger as logger
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class LoopMeta(type):
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@staticmethod
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def _get_steps(bases):
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"""
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get all the `steps` of base classes and combine them to a single one.
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"""
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steps = []
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for base in bases:
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steps.extend(LoopMeta._get_steps(base.__bases__) + getattr(base,"steps", []))
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return steps
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def __new__(cls, clsname, bases, attrs):
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# move custommized steps into steps
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steps = LoopMeta._get_steps(bases) # all the base classes of parents
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for name, attr in attrs.items():
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if not name.startswith("__") and isinstance(attr, Callable):
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steps.append(name)
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attrs["steps"] = steps
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return super().__new__(cls, clsname, bases, attrs)
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@dataclass
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class LoopTrace:
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start: datetime.datetime # the start time of the trace
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end: datetime.datetime # the end time of the trace
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# TODO: more information about the trace
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class LoopBase:
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steps: list[Callable] # a list of steps to work on
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loop_trace: dict[int, list[LoopTrace]]
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skip_loop_error: tuple[Exception] = field(default_factory=tuple) # you can define a list of error that will skip current loop
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def __init__(self):
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self.loop_idx = 0 # current loop index
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self.step_idx = 0 # the index of next step to be run
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self.loop_prev_out = {} # the step results of current loop
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self.loop_trace = defaultdict(list[LoopTrace]) # the key is the number of loop
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self.session_folder = logger.log_trace_path / "__session__"
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def run(self, step_n: int | None = None):
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"""
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Parameters
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----------
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step_n : int | None
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How many steps to run;
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`None` indicates to run forever until error or KeyboardInterrupt
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"""
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with tqdm(total=len(self.steps), desc="Workflow Progress", unit="step") as pbar:
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while True:
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if step_n is not None:
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if step_n <= 0:
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break
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step_n -= 1
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li, si = self.loop_idx, self.step_idx
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start = datetime.datetime.now(datetime.timezone.utc)
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name = self.steps[si]
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func = getattr(self, name)
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try:
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self.loop_prev_out[name] = func(self.loop_prev_out)
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# TODO: Fix the error logger.exception(f"Skip loop {li} due to {e}")
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except self.skip_loop_error as e:
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logger.warning(f"Skip loop {li} due to {e}")
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self.loop_idx += 1
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self.step_index = 0
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continue
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end = datetime.datetime.now(datetime.timezone.utc)
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self.loop_trace[li].append(LoopTrace(start, end))
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# Update tqdm progress bar
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pbar.set_postfix(loop_index=li, step_index=si, step_name=name)
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pbar.update(1)
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# index increase and save session
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self.step_idx = (self.step_idx + 1) % len(self.steps)
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if self.step_idx == 0: # reset to step 0 in next round
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self.loop_idx += 1
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self.loop_prev_out = {}
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pbar.reset() # reset the progress bar for the next loop
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self.dump(self.session_folder / f"{li}" / f"{si}_{name}") # save a snapshot after the session
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def dump(self, path: str | Path):
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path = Path(path)
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path.parent.mkdir(parents=True, exist_ok=True)
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with path.open("wb") as f:
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pickle.dump(self, f)
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@classmethod
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def load(cls, path: str | Path):
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path = Path(path)
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with path.open("rb") as f:
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session = pickle.load(f)
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logger.set_trace_path(session.session_folder.parent)
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max_loop = max(session.loop_trace.keys())
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logger.storage.truncate(time=session.loop_trace[max_loop][-1].end)
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return session
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