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lazy import autogluon

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Yizhou Chi 2024-09-14 21:58:53 +08:00
parent 3c50575ff7
commit ce73f4c25a
1 changed files with 10 additions and 4 deletions
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14
expo/experimenter/autogluon.py
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@ -1,17 +1,19 @@
from datetime import datetime
from autogluon.tabular import TabularDataset, TabularPredictor
from expo.experimenter.custom import CustomExperimenter
class AGRunner:
preset = "best_quality"
time_limit = 1000 # 1000s
time_limit = 1000 # 1000s
def __init__(self, state=None):
self.state = state
self.datasets = self.state["datasets_dir"]
def run(self):
from autogluon.tabular import TabularDataset, TabularPredictor
train_path = self.datasets["train"]
dev_wo_target_path = self.datasets["dev_wo_target"]
test_wo_target_path = self.datasets["test_wo_target"]
@ -21,7 +23,11 @@ class AGRunner:
test_data = TabularDataset(test_wo_target_path)
eval_metric = self.state["dataset_config"]["metric"].replace(" ", "_")
# predictor = TabularPredictor(label=target_col, eval_metric=eval_metric, path="AutogluonModels/ag-{}-{}".format(self.state['task'], datetime.now().strftime("%y%m%d_%H%M"))).fit(train_data, presets=self.preset, time_limit=self.time_limit, fit_weighted_ensemble=False, num_gpus=1)
predictor = TabularPredictor(label=target_col, eval_metric=eval_metric, path="AutogluonModels/ag-{}-{}".format(self.state['task'], datetime.now().strftime("%y%m%d_%H%M"))).fit(train_data, num_gpus=1)
predictor = TabularPredictor(
label=target_col,
eval_metric=eval_metric,
path="AutogluonModels/ag-{}-{}".format(self.state["task"], datetime.now().strftime("%y%m%d_%H%M")),
).fit(train_data, num_gpus=1)
dev_preds = predictor.predict(dev_data)
test_preds = predictor.predict(test_data)
return {"test_preds": test_preds, "dev_preds": dev_preds}
@ -44,4 +50,4 @@ class GluonExperimenter(CustomExperimenter):
"test_score": self.evaluate_predictions(test_preds, "test"),
}
results = [0, {"score_dict": score_dict, "user_requirement": user_requirement, "args": vars(self.args)}]
self.save_result(results)
self.save_result(results)