Why did I get "killed" when running 1min of alpha360?
DanielKui opened this issue · 0 comments
DanielKui commented
###################################
# train model
###################################
data_handler_config = {
"start_time":"2020-09-14",
"end_time":"2021-06-20",
"fit_start_time":"2020-09-20",
"fit_end_time":"2021-05-20",
"freq":'1min',
"instruments": market,
}
task = {
"model": {
"class": "LGBModel",
"module_path": "qlib.contrib.model.gbdt",
"kwargs": {
"loss": "mse",
"colsample_bytree": 0.8879,
"learning_rate": 0.0421,
"subsample": 0.8789,
"lambda_l1": 205.6999,
"lambda_l2": 580.9768,
"max_depth": 8,
"num_leaves": 210,
"num_threads": 20,
},
},
"dataset": {
"class": "DatasetH",
"module_path": "qlib.data.dataset",
"kwargs": {
"handler": {
"class": "Alpha360",
"module_path": "qlib.contrib.data.handler",
"kwargs": data_handler_config,
},
"segments": {
"train": ("2020-09-14", "2020-10-15"),
"valid": ("2020-10-16", "2020-12-20"),
"test": ("2020-12-14", "2021-05-20"),
},
},
},
}
h = Alpha360(**data_handler_config)
alpha360_df_feature = h.fetch(col_set="feature")
alpha360_df_feature = alpha360_df_feature.loc[:,~(alpha360_df_feature == 0.0).all()]
alpha360_df_feature = alpha360_df_feature.loc[~(alpha360_df_feature.eq(0.0).all(1))]
print(alpha360_df_feature)
# model initiaiton
model = init_instance_by_config(task["model"])
dataset = init_instance_by_config(task["dataset"])
# start exp to train model
with R.start(experiment_name="train_model"):
R.log_params(**flatten_dict(task))
model.fit(dataset)
R.save_objects(trained_model=model)
rid = R.get_recorder().id
when I try tu run jupyter notebook, it always showed that python kernel has been restarted.
What's datetime range does it support? I tried one day range, it works fine from 2020-09-14 to 2020-09-15,
Most of feature in alpha360 are zero. this range may a little bit short.
My machine:
Debian 11
RAM 64G
4 processors