dcgan.py
def __create_summaries(self):
        """Helper function to create summaries.
        """
        # histogram summaries
        self.z_sum = tf.summary.histogram("z", self.z)
        self.d_real_sum = tf.summary.histogram("d/output/real", self.D_real)
        self.d_fake_sum = tf.summary.histogram("d/output/fake", self.D_fake)

        # image summaries
        self.g_sum = tf.summary.image("generated",
                                      self.G,
                                      max_outputs=8)
        self.real_sum = tf.summary.image("real",
                                         self.real_images,
                                         max_outputs=8)

        # scalar summaries
        self.d_loss_real_sum = tf.summary.scalar("d/loss/real",
                                                 self.d_loss_real)
        self.d_loss_fake_sum = tf.summary.scalar("d/loss/fake",
                                                 self.d_loss_fake)
        self.d_loss_sum = tf.summary.scalar("d/loss/combined",
                                            self.d_loss)
        self.g_loss_sum = tf.summary.scalar("g/loss/combined",
                                            self.g_loss)
Helper function to create summaries.
        
Helper function to create summaries.
Helper function to create summaries .
def __create_summaries(self):
        self.z_sum = tf.summary.histogram("z", self.z)
        self.d_real_sum = tf.summary.histogram("d/output/real", self.D_real)
        self.d_fake_sum = tf.summary.histogram("d/output/fake", self.D_fake)
        self.g_sum = tf.summary.image("generated",
                                      self.G,
                                      max_outputs=8)
        self.real_sum = tf.summary.image("real",
                                         self.real_images,
                                         max_outputs=8)
        self.d_loss_real_sum = tf.summary.scalar("d/loss/real",
                                                 self.d_loss_real)
        self.d_loss_fake_sum = tf.summary.scalar("d/loss/fake",
                                                 self.d_loss_fake)
        self.d_loss_sum = tf.summary.scalar("d/loss/combined",
                                            self.d_loss)
        self.g_loss_sum = tf.summary.scalar("g/loss/combined",
                                            self.g_loss)
def __create_summaries ( self ) : self . z_sum = tf . summary . histogram ( "z" , self . z ) self . d_real_sum = tf . summary . histogram ( "d/output/real" , self . D_real ) self . d_fake_sum = tf . summary . histogram ( "d/output/fake" , self . D_fake ) self . g_sum = tf . summary . image ( "generated" , self . G , max_outputs = 8 ) self . real_sum = tf . summary . image ( "real" , self . real_images , max_outputs = 8 ) self . d_loss_real_sum = tf . summary . scalar ( "d/loss/real" , self . d_loss_real ) self . d_loss_fake_sum = tf . summary . scalar ( "d/loss/fake" , self . d_loss_fake ) self . d_loss_sum = tf . summary . scalar ( "d/loss/combined" , self . d_loss ) self . g_loss_sum = tf . summary . scalar ( "g/loss/combined" , self . g_loss )
Helper function to create summaries.
Helper function to create summaries .
"""Helper function to create summaries.
        """ # histogram summaries # image summaries # scalar summaries
self