TensorFlow tf.Variable with dynamic shape

tf_variable_with_dynamic_shape.py

# - prevent the variable to be used as a model parameter: trainable=False, collections=[]
# - allow dynamic variable shape (for the last batch): validate_shape=False

placeholder = tf.placeholder(dtype=tf.float32, shape=(None, 10))
variable = tf.Variable(placeholder, trainable=False, collections=[], validate_shape=False)
with tf.Session() as sess:
    sess.run(variable.initializer, feed_dict={placeholder: np.arange(20).reshape(2,10)})
    print('shape:', sess.run(tf.shape(variable)))
    print(sess.run(variable))
    
    sess.run(variable.initializer, feed_dict={placeholder: np.arange(30).reshape(3,10)})
    print('shape:', sess.run(tf.shape(variable)))
    print(sess.run(variable))