[python-package] using lgb.Booster(model_file='model.txt') hangs when loading gbdt regression model about lightgbm HOT 8 OPEN

maybe it's better for the team to maintain the conda installation with higher versions.

from lightgbm.

It hungs at

bst = lgb.train(params, train_data, num_boost_round=10)

from lightgbm.

Thanks for using LightGBM.

If it hands on lgb.train(), then I guess the code after that line is not necessary, correct? If so, please remove it from the example.

Can you please share any logs produced by lightgbm prior to it "hanging"?

from lightgbm.

ok, thanks for your help. In fact, i had a model file and i just wanted to load it at beginning. It hanged at "lgb.Booster(model_file=model_path)" when loading, after that i tried the mini-case and it hanged at "lgb.train()".

By the way, what's the default log path by lightgbm? I will try to find more information tonight~

from lightgbm.

By the way, what's the default log path by lightgbm?

By default, lightgbm does not write logs to a file. It writes them directly to standard output (for example, printed in the terminal or the output below an executing Jupyter notebook cell).

from lightgbm.

it hangs at after print(1), at code _safe_call(_LIB.LGBM_BoosterCreateFromModelfile( _c_str(str(model_file)), ctypes.byref(out_num_iterations), ctypes.byref(self._handle)))

        elif model_file is not None:
            # Prediction task
            out_num_iterations = ctypes.c_int(0)
            print(1)
            _safe_call(_LIB.LGBM_BoosterCreateFromModelfile(
                _c_str(str(model_file)),
                ctypes.byref(out_num_iterations),
                ctypes.byref(self._handle)))
            print(2)
            out_num_class = ctypes.c_int(0)
            _safe_call(_LIB.LGBM_BoosterGetNumClasses(
                self._handle,
                ctypes.byref(out_num_class)))
            print(3)
            self.__num_class = out_num_class.value
            print(4)
            self.pandas_categorical = _load_pandas_categorical(file_name=model_file)
            print(5)
            if params:
                _log_warning('Ignoring params argument, using parameters from model file.')
            params = self._get_loaded_param()
            print(6)

from lightgbm.

ok, I find the problem. It's because of my numpy, scipy, pandas version is not compatible to the model file.

should make sure that these compute libs are compatible to the model files.

from lightgbm.

ok, I find the problem. It's because of my numpy, scipy, pandas version is not compatible to the model file.

Can you please provide specific details about this? I don't understand this statement.

You may want to see "How to create a reproducible example" (link) for some advice on reporting software problems in a way that others can help confirm and investigate them.

from lightgbm.