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I have a list of tensors created by

[some_function(x) for x in something]

and this list becomes like this

[<tf.Tensor: shape=(), dtype=string, numpy=b'I have gone and you will go'>, <tf.Tensor: shape=(), dtype=string, numpy=b'we will go'>]

But I want to have an object like this

<tf.Tensor: shape=(3,), dtype=string, numpy=array([b'I have gone and you will go', b'we will go'], dtype=object)>

Which is a tensor of list of strings (Opposite to the previous one). Is there any way to this, assuming that I have access to all these tensors, i.e. some_function(x) for x in something separately.

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In order to stack list of tf tensors you could use the tf function stack hence the name

for ur case,


tf.stack([some_function(x) for x in something],axis=0)


or you could stack them in numpy and then convert the array to a tensor, to do so using numpy np.stack inputting a list and axis

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