microsoft / microsoft/qlib

MemoryError triggered when importing 'TopkDropoutStrategy' from qlib.contrib.strategy

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bug
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Python
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Description

from typing import Tuple

import pandas as pd
import qlib
from qlib.contrib.strategy import TopkDropoutStrategy
from qlib.data import D
from qlib.utils import hash_args, init_instance_by_config

if __name__ == "__main__":
    qlib.init(
        provider_uri=r"D:\qlib_data",
        region="cn",
    )
    TRAIN_PERIODS: Tuple = ("2013-01-01", "2017-12-31")
    VALID_PERIODS: Tuple = ("2018-01-01", "2019-12-31")
    TEST_PERIODS: Tuple = ("2020-01-01", "2023-05-31")
    dataset_config = {
        "class": "DatasetH",
        "module_path": "qlib.data.dataset",
        "kwargs": {
            "handler": {
                "class": "Alpha158",
                "module_path": "qlib.contrib.data.handler",
                "kwargs": {
                    "start_time": TRAIN_PERIODS[0],
                    "end_time": TEST_PERIODS[1],
                    "fit_start_time": TRAIN_PERIODS[0],
                    "fit_end_time": TRAIN_PERIODS[1],
                    "instruments": "csi300",
                },
            },
            "segments": {
                "train": TRAIN_PERIODS,
                "valid": VALID_PERIODS,
                "test": TEST_PERIODS,
            },
        },
    }
    dataset = init_instance_by_config(dataset_config)

此时会报错
image
image
qlib版本为0.9.3
在注释掉from qlib.contrib.strategy import TopkDropoutStrategy后便不会有问题

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  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Reproduce the issue with the supplied Python script and qlib 0.9.3, first importing TopkDropoutStrategy and then repeating with that import commented out. Start at the qlib.contrib.strategy import path and use the traceback shown in the linked screenshots to identify the cause; done means the import and subsequent dataset initialization complete without MemoryError.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
data, machine-learning
Issue type
Bug
Difficulty
3/5
Estimated time
1-2 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
38/100

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