How to get the dimensions of a tensor (in TensorFlow) at graph construction time?

Question

I am trying an Op that is not behaving as expected.

graph = tf.Graph()
with graph.as_default():
  train_dataset = tf.placeholder(tf.int32, shape=[128, 2])
  embe         


        

Answer 1

Let's make it simple as hell. If you want a single number for the number of dimensions like 2, 3, 4, etc., then just use tf.rank(). But, if you want the exact shape of the tensor then use tensor.get_shape()

with tf.Session() as sess:
   arr = tf.random_normal(shape=(10, 32, 32, 128))
   a = tf.random_gamma(shape=(3, 3, 1), alpha=0.1)
   print(sess.run([tf.rank(arr), tf.rank(a)]))
   print(arr.get_shape(), ", ", a.get_shape())     


# for tf.rank()    
[4, 3]

# for tf.get_shape()
Output: (10, 32, 32, 128) , (3, 3, 1)