Error while trying to create library

[nurudeen95]

I am really new to using alphapeptdeep. I wanted to generate a predicted library for some sequences using the GUI. The list contains 1755 sequences.

To Reproduce Since this is my first time using alphapeptdeep, I tried to keep things simple and leave all the settings as is. However, I got this error some minutes into the run:

Logs Traceback (most recent call last): File "multiprocessing\pool.py", line 125, in worker File "peptdeep\pretrained_models.py", line 936, in _predict_func_for_mp return self.predict_all( File "peptdeep\pretrained_models.py", line 1130, in predict_all fragment_intensity_df = self.predict_ms2( File "peptdeep\pretrained_models.py", line 870, in predict_ms2 return self.ms2_model.predict(precursor_df, File "peptdeep\model\ms2.py", line 582, in predict return super().predict( File "peptdeep\model\model_interface.py", line 543, in predict features = self._get_features_from_batch_df( File "peptdeep\model\ms2.py", line 444, in _get_features_from_batch_df mod_x = self._get_mod_features(batch_df) File "peptdeep\model\model_interface.py", line 967, in _get_mod_features get_batch_mod_feature(batch_df) File "peptdeep\model\featurize.py", line 75, in get_batch_mod_feature mod_x_batch = np.zeros( numpy.core._exceptions._ArrayMemoryError: Unable to allocate 2.35 MiB for an array with shape (166, 17, 109) and data type float64 """

The above exception was the direct cause of the following exception:

Traceback (most recent call last): File "peptdeep\pipeline_api.py", line 428, in generate_library lib_maker.make_library(lib_settings["infiles"]) File "peptdeep\spec_lib\library_factory.py", line 105, in make_library self._predict() File "peptdeep\spec_lib\library_factory.py", line 68, in _predict self.spec_lib.predict_all() File "peptdeep\spec_lib\predict_lib.py", line 123, in predict_all res = self.model_manager.predict_all( File "peptdeep\pretrained_models.py", line 1155, in predict_all return self.predict_all_mp( File "peptdeep\pretrained_models.py", line 991, in predict_all_mp for ret_dict in process_bar( File "peptdeep\utils__init__.py", line 18, in process_bar for i,iter in enumerate(iterator): File "multiprocessing\pool.py", line 870, in next numpy.core._exceptions._ArrayMemoryError: Unable to allocate 2.35 MiB for an array with shape (166, 17, 109) and data type float64

Expected Result It seems like there is a memory issue but I wanted to be sure before I troubleshoot further.

Version (please complete the following information): GUI: Version 1.2.1

[jalew188]

Yes, it looks like a memory issue

[nurudeen95]

Alright. Thank you for the response. Are there recommended specification to run the GUI on?

[jalew188]

Try less process number or less batch size in GUI