libtpu.so 1.5.0 or tpu-vm-tf-2.11.0-pod runtime bug
Could you please try to providing more debug details on this issue, it would help us to investigate further on this issue. 
For more details regarding `tf.data` visit https://www.tensorflow.org/api_docs/python/tf/data
For pipeline related details visit https://www.tensorflow.org/guide/data
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<details><summary>Click to expand!</summary> 
 
 ### Issue Type

Bug

### Have you reproduced the bug with TF nightly?

No

### Source

source

### Tensorflow Version

2.11

### Custom Code

Yes

### OS Platform and Distribution

tpu-vm-tf-2.11.0-pod

### Mobile device

_No response_

### Python version

3.10

### Bazel version

_No response_

### GCC/Compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current Behaviour?

```shell
It appears that when using `tf.data.Dataset` with `libtpu.so 1.5.0` and `tpu-vm-tf-2.11.0-pod` runtime, only half the system resources are being able to get utilized. For a `tpu-v4` if a dataset uses more than 200gb system ram, it will get killed (with just a missing context id provided, no detailed error even gets generated). This problem does not occur using `tpu-vm-tf-2.10.1-pod`. I am sorry I am unable to provide a standalone example but please review build flags / runtime image for `tpu-vm-tf-2.11.0-pod`.
```


### Standalone code to reproduce the issue

```shell
Difficult to provide at this point
```


### Relevant log output

_No response_</details>