如何在图构建时获取张量(在 TensorFlow 中)的维度? [英] How to get the dimensions of a tensor (in TensorFlow) at graph construction time?

问题描述

我正在尝试一个行为不符合预期的操作.

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)

所以我需要知道张量 embed 的尺寸.我知道它可以在运行时完成，但是对于这样一个简单的操作来说工作量太大了.什么是更简单的方法?

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?

推荐答案

Tensor.get_shape() 来自 这篇文章.

来自文档:

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

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