aecker

class MySaver(tf.train.Saver):
    def __init__(self, var_list, extra_vars=None, extra_chkpt_file=None, **kwargs):
        super().__init__(var_list=var_list, **kwargs)
        self.extra_chkpt_file = extra_chkpt_file
        self.extra_saver = tf.train.Saver(var_list=extra_vars)
    
    def restore(self, sess, save_path):
        super().restore(sess, save_path)
        self.extra_saver.restore(sess, self.extra_chkpt_file)
                

aecker

# Load data
responses_val_raw = np.load(os.path.join(path, 'raw_validation_set.npy'))
prediction = mymodel.prediction()
reps, num_imgs, num_neurons = responses_val_raw.shape

# Calculate normalized noise power
obs_var_raw = (responses_val_raw.var(axis=0, ddof=1)).mean(axis=0)
total_var_raw = responses_val_raw.reshape([-1, num_neurons]).var(axis=0, ddof=1)
nnp = obs_var / total_var