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pythonpytorch

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()) ...

Solution

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

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

    With pytorch 0.4 there is also torch.isnan:

    >>> torch.isnan(x)
tensor([ 0,  0,  1], dtype=torch.uint8)