#NEWLINE# def handle( self , * args , **options ) : #NEWLINE# #INDENT# pool = Pool ( settings . NUM_THREADS ) #NEWLINE# conf = settings . TRAINER_CURRENCY_CONFIG [ 'supervised_nn' ] #NEWLINE# print ( 'Starting V2 run' ) #NEWLINE# for ticker in conf [ 'ticker' ] : #NEWLINE# #INDENT# for hidden_layers in conf [ 'hidden_layers' ] : #NEWLINE# #INDENT# for min_back in conf [ 'min_back' ] : #NEWLINE# #INDENT# for epochs in conf [ 'epochs' ] : #NEWLINE# #INDENT# for granularity in conf [ 'granularity' ] : #NEWLINE# #INDENT# for datasetinputs in conf [ 'datasetinputs' ] : #NEWLINE# #INDENT# for bias in conf [ 'bias' ] : #NEWLINE# #INDENT# for momentum in conf [ 'momentum' ] : #NEWLINE# #INDENT# for learningrate in conf [ 'learningrate' ] : #NEWLINE# #INDENT# for weightdecay in conf [ 'weightdecay' ] : #NEWLINE# #INDENT# for recurrent in conf [ 'recurrent' ] : #NEWLINE# #INDENT# for timedelta_back_in_granularity_increments in conf [ 'timedelta_back_in_granularity_increments' ] : #NEWLINE# #INDENT# pool . apply_async ( do_prediction_test , args = ( ticker , hidden_layers , min_back , epochs , granularity , datasetinputs , learningrate , bias , momentum , recurrent , weightdecay , timedelta_back_in_granularity_increments ) ) #NEWLINE# #UNINDENT# #UNINDENT# #UNINDENT# #UNINDENT# #UNINDENT# #UNINDENT# #UNINDENT# #UNINDENT# #UNINDENT# #UNINDENT# #UNINDENT# #UNINDENT# print ( 'All V2 jobs queued' ) #NEWLINE# pool . close ( ) #NEWLINE# pool . join ( ) #NEWLINE# print ( 'V2 run complete' )