tensorflow[and-cuda] 2.15.0/2.15.1 compatibility with jax[cuda12]
@attaluris  TensorFlow[and-cuda] 2.15.0/2.15.1 is likely not compatible with jax[cuda12]. There's a version mismatch with respect to the NVIDIA NCCL library, a component needed for GPU support in both TensorFlow and JAX.
TensorFlow 2.15.0/2.15.1 might depend on an older NCCL version (e.g., nvidia-nccl-cu12 version 2.16.5).
For any further queries please raise an issue in [Jax](https://github.com/google/jax/issues) repository.

Thank you! @sushreebarsa Is there a way we could loosen the strict requirement in tensorflow from `=2.16.5` to `>2.16.5`?

I also raised an issue in the Jax repo @attaluris Could you try to update tensorflow to 2.16.1 and jax to 0.4.28?
TF 2.16.1 uses  nvidia-nccl-cu12==2.19.3 (from tensorflow[and-cuda]) which is compatible with JAX's requirement of >=2.18.3.

Thank you!
 @sushreebarsa thanks for the detail! 👀 
I'm seeing the same issue as https://github.com/tensorflow/tensorflow/issues/63362 with tensorflow 2.16.1 so I'm using 2.15.1
can I get a confirmation that the tensorflow 2.16.1 installation will be fixed and maybe a timeline? thanks in advance! @attaluris On ubuntu 20.04LTS machine with Tesla P100 GPU, we tried to install JAX 0.4.28 cuda version first and then installed tensorflow 2.15.1. Both were installed successfully. JAX and tf were able to detect GPUs as well. Please have a look at the below screenshot for reference.
<img width="1505" alt="image (4)" src="https://github.com/tensorflow/tensorflow/assets/84765720/99770c0e-e604-4b24-bd15-e7277214aab4">

Thank you! This issue is stale because it has been open for 7 days with no activity. It will be closed if no further activity occurs. Thank you.
### Issue type

Bug

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

No

### Source

source

### TensorFlow version

2.15.0/2.15.1

### Custom code

Yes

### OS platform and distribution

Debian Bulleye

### Mobile device

_No response_

### Python version

3.9/3.10

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

12.2

### GPU model and memory

v100

### Current behavior?

Hey y'all! I think `tensorflow[and-cuda]` is incompatible with `jax[cuda12]` and just wanted to clarify if this was expected.
The solve error I'm getting is:
```
Because tensorflow[and-cuda] (2.15.0) depends on nvidia-nccl-cu12 (2.16.5)
 and jax[cuda12] (0.4.23) depends on nvidia-nccl-cu12 (>=2.18.3), tensorflow[and-cuda] (2.15.0) is incompatible with jax[cuda12] (0.4.23).
So, because hex-packages depends on both jax[cuda12] (0.4.23) and tensorflow[and-cuda] (2.15.0), version solving failed.
```
and none of the `jax[cuda12]` versions with GPU compatibility support `nvidia-nccl-cu12=2.16.5`; does this requirement need to be hard or can it be looser to accomodate higher versions of `nvidia-nccl-cu12`?

### Standalone code to reproduce the issue

```shell
[tool.poetry]
name = "test-jax-and-poetry"
version = "0.1.0"
description = ""
authors = ["Tim Nonet <tnonet@hex.tech>"]
readme = "README.md"

[tool.poetry.dependencies]
python = ">=3.9,<3.11"
tensorflow = { "version" = "2.15.1", extras = ["and-cuda"] }
jax = {"version" = "*", extras = ["cuda12"] }


[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"
```


### Relevant log output

```shell
Because tensorflow[and-cuda] (2.15.0) depends on nvidia-nccl-cu12 (2.16.5)
 and jax[cuda12] (0.4.23) depends on nvidia-nccl-cu12 (>=2.18.3), tensorflow[and-cuda] (2.15.0) is incompatible with jax[cuda12] (0.4.23).
So, because hex-packages depends on both jax[cuda12] (0.4.23) and tensorflow[and-cuda] (2.15.0), version solving failed.
```

whenever I use a version of `jax` that has the `cuda12` extra
```
