Tensor.tensorOf methods can return unzeroed memory

System information

• Have I written custom code (as opposed to using a stock example script provided in TensorFlow): Yep
• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): macOS
• TensorFlow installed from (source or binary): binary
• TensorFlow version (use command below): 0.3.1

Describe the current behavior

Tensor.of(Class,Shape,long) and Tensor.of(Class,Shape) return a Tensor which has not been zeroed. This is used by the various tensorOf methods on things like TFloat32.

Describe the expected behavior

Tensors should be initialised to be all zero the same way any other Java object is.

Code to reproduce the issue

Run TFloat32.tensorOf(Shape.of(2,2)) and you'll likely get some junk in there. I was allocating things (16,10) but the size is irrelevant.

I was building a one hot vector to use as the target for a training run, and I expected to get an all zero tensor back, so I only set the 1s. The model was very confused by the true labels having NaNs in.

Commencez par Tensor.of(Class, Shape, long) et Tensor.of(Class, Shape), puis reproduisez le problème avec TFloat32.tensorOf(Shape.of(2,2)). Vérifiez que les tenseurs nouvellement créés ne contiennent que des zéros, y compris les tenseurs créés via les méthodes tensorOf associées, et ajoutez ou exécutez une vérification de régression si le code environnant en fournit une.