Tensorflow snippets

cond_dependency.py

v1 = tf.get_variable("v1", shape=(), initializer=tf.zeros_initializer())
v2 = tf.get_variable("v2", shape=(), initializer=tf.zeros_initializer())

switch = tf.placeholder(tf.bool)
cond = tf.cond(switch, lambda: tf.assign(v1, 1.0), lambda: tf.assign(v2, 2.0))

with tf.train.MonitoredSession() as session:
    session.run(cond, feed_dict={switch: True})
    print(session.run([v1, v2]))

control_dependency.py

# Control Dependency
x = tf.get_variable("x", shape=(), initializer=tf.zeros_initializer())
assign_x = tf.assign(x, 10)

# z value depends on the assign_x tensor
with tf.control_dependencies([assign_x]):
    z = x + 1

with tf.train.MonitoredSession() as session:
    print(session.run(z))

tf_iterator.py

# Iterate over input using Tensorflow

X_tensor = tf.placeholder(tf.float64, (None, 32, 128))
dataset = tf.data.Dataset.from_tensor_slices(X_tensor)
iterator = dataset.make_initializable_iterator()
next_element = iterator.get_next()

with tf.Session() as sess:
    sess.run(iterator.initializer, feed_dict={X_tensor: X})
    sess.run(next_element)