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.

从 Tensor.of(Class, Shape, long) 和 Tensor.of(Class, Shape) 开始，然后使用 TFloat32.tensorOf(Shape.of(2,2)) 重现该问题。确认新创建的张量只包含零，包括通过相关 tensorOf 方法创建的张量；如果周围的代码提供了回归检查，则添加或运行该检查。