(self, callback_data, model, epochs)
Called when training is about to begin

        Arguments:
            callback_data (HDF5 dataset): shared data between callbacks
            model (Model): model object
            epochs (int): Total epochs
Called when training is about to begin
Called when training is about to begin
def on_train_begin(self, callback_data, model, epochs):
        """
        Called when training is about to begin

        Arguments:
            callback_data (HDF5 dataset): shared data between callbacks
            model (Model): model object
            epochs (int): Total epochs
        """
        if 'metrics' not in callback_data:
            callback_data.create_group("metrics")
        for met in self.metric.metric_names:
            group_name = "metrics/%s" % met
            callback_data.create_dataset(group_name, (epochs // self.epoch_freq,))
            callback_data[group_name].attrs['time_markers'] = 'epoch_freq'
            callback_data[group_name].attrs['epoch_freq'] = self.epoch_freq
def on_train_begin ( self , callback_data , model , epochs ) : if 'metrics' not in callback_data : callback_data . create_group ( "metrics" ) for met in self . metric . metric_names : group_name = "metrics/%s" % met callback_data . create_dataset ( group_name , ( epochs // self . epoch_freq , ) ) callback_data [ group_name ] . attrs [ 'time_markers' ] = 'epoch_freq' callback_data [ group_name ] . attrs [ 'epoch_freq' ] = self . epoch_freq