Trick_2

Save & restore

# save

X = tf.placeholder('float', [None, 4000], name='input_X')
Y = tf.placeholder('float', [None, 2], name='label_Y')
is_training = tf.placeholder(tf.bool, name='is_training')

logits = build_model(is_training, X)
tf.identity(logits, name='output_Y')

# ...

tf.saved_model.simple_save(
    sess,
    save_dir.as_posix(),
    inputs={
        'input_X': X,
        'is_training': is_training
    },
    outputs={'output_Y': logits}
)

# restore
with tf.Session() as sess:
    tf.saved_model.loader.load(
        sess, 
        ['serve'], 
        save_dir.as_posix()
    )

    X = sess.graph.get_tensor_by_name('input_X:0')
    Y = sess.graph.get_tensor_by_name('output_Y:0')
    is_training = sess.graph.get_tensor_by_name('is_training:0')

    valid_pos_predictions = sess.run(
        Y,
        feed_dict={
            X: valid_pos[:, 0:4000],
            is_training: False
        }
    )

Tensorboard

with tf.name_scope('Inputs'):
    ...

with tf.variable_scope('fc_1'):
    ...

tf.summary.scalar('loss', loss_op)
tf.summary.scalar('acc', acc_op)

tf.summary.histogram(name='1st output', values=out)

merged = tf.summary.merge_all()

init = tf.global_variables_initializer()

with tf.Session() as sess:
    writer_valid_pos = tf.summary.FileWriter('TensorBoard/valid_pos/', graph=sess.graph)
    writer_valid_neg = tf.summary.FileWriter('TensorBoard/valid_neg/', graph=sess.graph)

    ...

    for step in range(1, num_steps+1):    
        _, _, summ_valid_pos = sess.run(
            [loss_op, acc_op, merged], 
            feed_dict={
                X: valid_pos[:, 0:4000],
                Y: valid_pos[:, 4000:4002],
                is_training: False
            })

        _, _, summ_valid_neg = sess.run(
            [loss_op, acc_op, merged], 
            feed_dict={
                X: valid_neg[:, 0:4000],
                Y: valid_neg[:, 4000:4002],
                is_training: False
            })

        writer_valid_pos.add_summary(summ_valid_pos, step)
        writer_valid_neg.add_summary(summ_valid_neg, step)