Unified memory support for ROCm?

[tony9959]

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System information

• Have I written custom code (as opposed to using a stock example script
  provided in TensorFlow):No
• OS Platform and Distribution (e.g., Linux Ubuntu 16.04):Linux Ubuntu 22.04.2 LTS
• Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue
  happens on a mobile device:
• TensorFlow installed from (source or binary):binary
• TensorFlow version (use command below):2.11.0
• Python version:3.8
• Bazel version (if compiling from source):
• GCC/Compiler version (if compiling from source):
• CUDA/cuDNN version:ROCm 5.4.3
• GPU model and memory:RX 6800XT
• Exact command to reproduce:

You can collect some of this information using our environment capture script:

https://github.com/tensorflow/tensorflow/tree/master/tools/tf_env_collect.sh

You can obtain the TensorFlow version with:

python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"

Describe the problem

Describe the problem clearly here. Be sure to convey here why it's a bug in TensorFlow or a feature request.
Whenever I tryi to use unified memory feature, it gives me a
E external/org_tensorflow/tensorflow/compiler/xla/stream_executor/rocm/rocm_driver.cc:635] Feature not supported on ROCm platform (UnifiedMemoryAllocate)
As far as I know, ROCm supports unified memory, so I would be very happy if Tensorflow also supports unified memory.

Source code / logs

Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached. Try to provide a reproducible test case that is the bare minimum necessary to generate the problem.