Pytorch Operation to detect NaNs

Is there a Pytorch-internal procedure to detect NaNs in Tensors? Tensorflow has the tf.is_nan and the tf.check_numerics operations ... Does Pytorch have something similar, somewhere? I could not find something like this in the docs... 

I am looking specifically for a Pytorch internal routine, since I would like this to happen on the GPU as well as on the CPU. This excludes numpy - based solutions (like np.isnan(sometensor.numpy()).any()) ...

You can always leverage the fact that nan != nan:

&gt;&gt;&gt; x = torch.tensor([1, 2, np.nan])
tensor([  1.,   2., nan.])
&gt;&gt;&gt; x != x
tensor([ 0,  0,  1], dtype=torch.uint8)


With pytorch 0.4 there is also torch.isnan:

&gt;&gt;&gt; torch.isnan(x)
tensor([ 0,  0,  1], dtype=torch.uint8)

