tf.shape() get wrong shape in tensorflow

Question

I define a tensor like this:

x = tf.get_variable(\"x\", [100])

But when I try to print shape of tensor :

print( tf.shape(x) )

Answer 1

Simply, use tensor.shape to get the static shape:

In [102]: a = tf.placeholder(tf.float32, [None, 128])

# returns [None, 128]
In [103]: a.shape.as_list()
Out[103]: [None, 128]

Whereas to get the dynamic shape, use tf.shape():

dynamic_shape = tf.shape(a)

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You can also get the shape as you'd in NumPy with your_tensor.shape as in the following example.

In [11]: tensr = tf.constant([[1, 2, 3, 4, 5], [2, 3, 4, 5, 6]])

In [12]: tensr.shape
Out[12]: TensorShape([Dimension(2), Dimension(5)])

In [13]: list(tensr.shape)
Out[13]: [Dimension(2), Dimension(5)]

In [16]: print(tensr.shape)
(2, 5)

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Also, this example, for tensors which can be evaluated.

In [33]: tf.shape(tensr).eval().tolist()
Out[33]: [2, 5]