Tensor.tensorOf methods can return unzeroed memory

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Assessment

Difficulty
2/5
Estimated time
1-3 hours
Newbie friendliness
45/100
Issue type
Bug
Clarity
Clearly specified
Activity status
Stale
Tech stack
java
Domain
machine-learning

Research direction

Start with Tensor.of(Class, Shape, long) and Tensor.of(Class, Shape), then reproduce the issue using TFloat32.tensorOf(Shape.of(2,2)). Confirm that newly created tensors contain only zeros, including tensors created through the related tensorOf methods, and add or run a regression check if the surrounding code provides one.

Written by the indexing model from the issue text.

Description

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.

Dominant language
Java
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Forks
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