Valueerror: Can't Convert Non-Rectangular Python Sequence to Tensor
I Want to Change List to Tensor with Tf. Convert_To_Tensor, Data Is Following: Data=[ Array([0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0...
I want to change list to tensor with tf.convert_to_tensor, data is following:
data=[
array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
1., 0., 0.]),
array([0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0.]),
array([0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1.,
0., 0., 0.]),
array([0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0.])
]
it didn't work, system says:
ValueError: Can't convert non-rectangular Python sequence to Tensor.
how to solve this problem?
2 Answers
I'm not sure whether they exist in TensorFlow 1 but TensorFlow 2.0 supports RaggedTensors, which the documentation describes as "... the TensorFlow equivalent of nested variable-length lists."
I think it would be trivial to convert your data to RaggedTensors. It might even be as easy as:
data_tensor = tf.ragged.constant(data)
Example:
>>> a = tf.ragged.constant([[1],[2,3]])
>>> a
<tf.RaggedTensor [[1], [2, 3]]>
You can't. Like the error message says, TensorFlow arrays can not have different sizes along one dimension. Try to use a list of TensorFlow arrays instead or the dataset api.
Robert Thorne covers electric vehicle innovations, autonomous driving systems, global mobility trends, and automotive engineering developments.
