How to convert a pytorch tensor of ints to a tensor of booleans?
I would like to cast a tensor of ints to a tensor of booleans.

Specifically I would like to be able to have a function which transforms tensor([0,10,0,16]) to tensor([0,1,0,1])

This is trivial in Tensorflow by just using tf.cast(x,tf.bool).

I want the cast to change all ints greater than 0 to a 1 and all ints equal to 0 to a 0. This is the equivalent of !! in most languages.

Since pytorch does not seem to have a dedicated boolean type to cast to, what is the best approach here?

Edit: I am looking for a vectorized solution opposed to looping through each element.

What you're looking for is to generate a boolean mask for the given integer tensor. For this, you can simply check for the condition: &quot;whether the values in the tensor are greater than 0&quot; using simple comparison operator (&gt;) or using torch.gt(), which would then give us the desired result.
# input tensor
In [76]: t   
Out[76]: tensor([ 0, 10,  0, 16])

# generate the needed boolean mask
In [78]: t &gt; 0      
Out[78]: tensor([0, 1, 0, 1], dtype=torch.uint8)


# sanity check
In [93]: mask = t &gt; 0      

In [94]: mask.type()      
Out[94]: 'torch.ByteTensor'


Note: In PyTorch version 1.4+, the above operation would return 'torch.BoolTensor'
In [9]: t &gt; 0  
Out[9]: tensor([False,  True, False,  True])

# alternatively, use `torch.gt()` API
In [11]: torch.gt(t, 0)
Out[11]: tensor([False,  True, False,  True])

If you indeed want single bits (either 0s or 1s), cast it using:
In [14]: (t &gt; 0).type(torch.uint8)   
Out[14]: tensor([0, 1, 0, 1], dtype=torch.uint8)

# alternatively, use `torch.gt()` API
In [15]: torch.gt(t, 0).int()
Out[15]: tensor([0, 1, 0, 1], dtype=torch.int32)

The reason for this change has been discussed in this feature-request issue: issues/4764 - Introduce torch.BoolTensor ...

TL;DR: Simple one liner
t.bool().int()

