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you-n-g
f9bd19179f
* init trail * Add spec info * auto unzip mlebench prepared data for out scenario * successfully run example * successfully run main * simplify load traing * extract load_from_raw_data * split the fies(still buggy) It should stop on ~20 epoch and reach the end * some changes * Fix bug to run example * (success) until feature * refine model and ensemble * add metrics in ens.py * update README & spec.md * ens change * fix ens bug * Delete rdagent/scenarios/kaggle/tpl_ex/aerial-cactus-identification/train.py * add template_path in KG_conf * fix test kaggle * CI * make test_import not check kaggle template codes --------- Co-authored-by: Bowen Xian <xianbowen@outlook.com>
37 lines
1.2 KiB
Python
37 lines
1.2 KiB
Python
import unittest
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from pathlib import Path
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import nbformat
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from rich import print
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from rdagent.app.kaggle.conf import KAGGLE_IMPLEMENT_SETTING
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from rdagent.oai.llm_utils import APIBackend
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from rdagent.scenarios.kaggle.experiment.workspace import KGFBWorkspace
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from rdagent.scenarios.kaggle.kaggle_crawler import download_data
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from rdagent.utils.agent.ret import PythonAgentOut
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from rdagent.utils.agent.tpl import T
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class TestTpl(unittest.TestCase):
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def test_competition_template(self):
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"""
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export KG_COMPETITION=<competition_name> before running this test
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"""
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competition = KAGGLE_IMPLEMENT_SETTING.competition
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print(f"[bold orange]{competition}[/bold orange]")
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download_data(competition)
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ws = KGFBWorkspace(
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template_folder_path=Path(__file__).parent.parent.parent
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/ KAGGLE_IMPLEMENT_SETTING.template_path
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/ f"{competition}",
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)
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print(ws.workspace_path)
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ws.execute()
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success = (ws.workspace_path / "submission.csv").exists()
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self.assertTrue(success, "submission.csv is not generated")
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# ws.clear()
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if __name__ == "__main__":
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unittest.main()
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