multicnet.py
def save_variables(self, a_file, h_file, stack):
        """
        Saves neural network weight variables for
        debugging purposes
        """
        readout_t = self.readout_act(stack)
        a_file.write(",".join([str(x) for x in readout_t]) + '\n')
        h_file.write(",".join([str(x) for x in self.h_fc1.eval(
            feed_dict={self.input_image:[stack]})[0]]) + '\n')

        Saves neural network weight variables for
        debugging purposes
        
Saves neural network weight variables for
debugging purposes
Saves neural network weight variables for debugging purposes
def save_variables(self, a_file, h_file, stack):
        readout_t = self.readout_act(stack)
        a_file.write(",".join([str(x) for x in readout_t]) + '\n')
        h_file.write(",".join([str(x) for x in self.h_fc1.eval(
            feed_dict={self.input_image:[stack]})[0]]) + '\n')
def save_variables ( self , a_file , h_file , stack ) : readout_t = self . readout_act ( stack ) a_file . write ( "," . join ( [ str ( x ) for x in readout_t ] ) + '\n' ) h_file . write ( "," . join ( [ str ( x ) for x in self . h_fc1 . eval ( feed_dict = { self . input_image : [ stack ] } ) [ 0 ] ] ) + '\n' )
Saves neural network weight variables for
debugging purposes
Saves neural network weight variables for debugging purposes
"""
        Saves neural network weight variables for
        debugging purposes
        """
self
a_file
h_file
stack