Tf_nightly fails to install in docker
It looks like it would be due to the nightly getting a version flagged as a release version when we switched over how we built the pip package for 2.16's release.  We will need to fix that but in the mean time you should be able to get around this by changing the install to 
`pip install tf-nightly --pre` I have pulled the bad release from the tf-nightly repo.  The replication code provided now correctly pulls the latest nightly for me on the first attempt.
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### Issue type

Build/Install

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

binary

### TensorFlow version

tf-nightly

### Custom code

No

### OS platform and distribution

Linux

### Mobile device

_No response_

### Python version

_No response_

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

Nvidia 3090 ti

### Current behavior?

Actual Behavior: When trying to install tf_nightly in a docker container, pip starts iterating backwards in time, downloading previous days' tensorflow nightly versions. I stopped the process after it made it back to March 9th...

Expected behavior: tf_nightly installs or produces an error

Note that I can install tf_nightly_cpu just fine. IIRC, GPUs are not available during build-time for docker by default, so maybe the error is related to the build environment silently failing a check for some gpu-related support? If so, (1) this shouldn't happen silently and (2) it's unlikely to be something that downloading a previous version would fix?

### Standalone code to reproduce the issue

```shell
from nvidia/cuda:12.3.2-cudnn9-devel-ubuntu22.04
RUN apt-get update && apt-get install python3 python3-pip python3-dev --yes
RUN pip install tf_nightly
```


### Relevant log output

_No response_