diff --git a/cifar100_network_trainer.py b/cifar100_network_trainer.py index 4376c53..2683530 100644 --- a/cifar100_network_trainer.py +++ b/cifar100_network_trainer.py @@ -78,8 +78,6 @@ with tf.Session() as sess: val_saver = tf.train.Saver() # training or inference - continue_from_epoch = -1 - if continue_from_epoch != -1: train_saver.restore(sess, "{}/{}_{}.ckpt".format(saved_models_filepath, experiment_name, continue_from_epoch)) # restore previous graph to continue operations diff --git a/cifar10_network_trainer.py b/cifar10_network_trainer.py index 70dfd30..0f1554f 100644 --- a/cifar10_network_trainer.py +++ b/cifar10_network_trainer.py @@ -78,8 +78,6 @@ with tf.Session() as sess: val_saver = tf.train.Saver() # training or inference - continue_from_epoch = -1 - if continue_from_epoch != -1: train_saver.restore(sess, "{}/{}_{}.ckpt".format(saved_models_filepath, experiment_name, continue_from_epoch)) # restore previous graph to continue operations diff --git a/emnist_network_trainer.py b/emnist_network_trainer.py index 2554318..1111408 100644 --- a/emnist_network_trainer.py +++ b/emnist_network_trainer.py @@ -78,8 +78,6 @@ with tf.Session() as sess: val_saver = tf.train.Saver() # training or inference - continue_from_epoch = -1 - if continue_from_epoch != -1: train_saver.restore(sess, "{}/{}_{}.ckpt".format(saved_models_filepath, experiment_name, continue_from_epoch)) # restore previous graph to continue operations diff --git a/msd10_network_trainer.py b/msd10_network_trainer.py index 16653be..87b8eec 100644 --- a/msd10_network_trainer.py +++ b/msd10_network_trainer.py @@ -78,7 +78,6 @@ with tf.Session() as sess: val_saver = tf.train.Saver() # training or inference - continue_from_epoch = -1 if continue_from_epoch != -1: train_saver.restore(sess, "{}/{}_{}.ckpt".format(saved_models_filepath, experiment_name, diff --git a/msd25_network_trainer.py b/msd25_network_trainer.py index 16653be..94337b9 100644 --- a/msd25_network_trainer.py +++ b/msd25_network_trainer.py @@ -78,8 +78,6 @@ with tf.Session() as sess: val_saver = tf.train.Saver() # training or inference - continue_from_epoch = -1 - if continue_from_epoch != -1: train_saver.restore(sess, "{}/{}_{}.ckpt".format(saved_models_filepath, experiment_name, continue_from_epoch)) # restore previous graph to continue operations