@@ -142,13 +142,15 @@ def record(self, prev_out: dict[str, Any]):
142142 logger .log_object (self .trace .sota_experiment (), tag = "SOTA experiment" )
143143
144144
145- def main (path = None , output_path = None , step_n = None , loop_n = None , competition = "bms-molecular-translation" ):
145+ def main (
146+ path = None , output_path = None , step_n = None , loop_n = None , competition = "bms-molecular-translation" , do_truncate = True
147+ ):
146148 """
147149
148150 Parameters
149151 ----------
150152 path :
151- path like `$LOG_PATH/__session__/1/0_propose`. It indicates that we restore the state that after finish the step 0 in loop1
153+ path like `$LOG_PATH/__session__/1/0_propose`. It indicates that we restore the state that after finish the step 0 in loop 1
152154 output_path :
153155 path like `$LOG_PATH`. It indicates that where we want to save our session and log information.
154156 step_n :
@@ -158,6 +160,8 @@ def main(path=None, output_path=None, step_n=None, loop_n=None, competition="bms
158160 - if current loop is incomplete, it will be counted as the first loop for completion.
159161 - if both step_n and loop_n are provided, the process will stop as soon as either condition is met.
160162 competition :
163+ do_truncate :
164+ If set to True, the logger will truncate the future log messages by calling `logger.storage.truncate`.
161165
162166
163167 Auto R&D Evolving loop for models in a Kaggle scenario.
@@ -181,7 +185,7 @@ def main(path=None, output_path=None, step_n=None, loop_n=None, competition="bms
181185 if path is None :
182186 kaggle_loop = DataScienceRDLoop (DS_RD_SETTING )
183187 else :
184- kaggle_loop = DataScienceRDLoop .load (path , output_path )
188+ kaggle_loop = DataScienceRDLoop .load (path , output_path , do_truncate )
185189 kaggle_loop .run (step_n = step_n , loop_n = loop_n )
186190
187191
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