If you want to access a placeholder
or a tensor
directly you can call get_tensor_by_name
:
import tensorflow as tf
def f():
a=tf.placeholder(dtype=tf.float32, name='name_a')
b=tf.placeholder(dtype=tf.float32, name='name_b')
addition=tf.add(a,b)
return addition
if __name__ == '__main__':
var = f()
a = tf.get_default_graph().get_tensor_by_name('name_a:0')
b = tf.get_default_graph().get_tensor_by_name('name_b:0')
with tf.Session() as sess:
print(sess.run(var, feed_dict={a:[1],b:[2]}))
[3.]