For my application, I am trying to convert a list with [None, 1, 1, 64]
to a tensor using tf.convert_to_tensor([None, 1, 1, 64])
, but this gives me
Use tf.convert_to_tensor([-1, 1, 1, 64]) instead of None, since you are already specifying 3 out of 4 dimensions, this should be fine.
No, because None
and 64
have different types, and all tensors are typed: You can't have elements of different types in one tensor.
The closest thing you could do is nan
:
tf.convert_to_tensor([np.nan, 1, 1, 64])
although I can't imagine why you'd want that.
You can however create a TensorShape
:
tf.TensorShape([None, 1, 1, 64])