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])
  embeddings = tf.Variable(
    tf.random_uniform([50000, 64], -1.0, 1.0))
  embed = tf.nn.embedding_lookup(embeddings, train_dataset)
  embed = tf.reduce_sum(embed, reduction_indices=0)

So I need to know the dimensions of the Tensor embed. I know that it can be done at the run time but it's too much work for such a simple operation. What's the easier way to do it?

Answer

Tensor.get_shape() from [this post](https://stackoverflow.com/questions/34079787/tensor-with-unspecified- dimension-in-tensorflow).

From documentation:

c = tf.constant([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
print(c.get_shape())
==> TensorShape([Dimension(2), Dimension(3)])