Integer overflow when running tf.linalg.diag
Hi @dmc1778 ,  

The reported behaviour is replicated with Tf2.13v and tf-nightly and attached gists [2.13v](https://colab.sandbox.google.com/gist/SuryanarayanaY/75444d6d31c9738cca13b7d11862aa02/61600.ipynb) and [nightly](https://colab.sandbox.google.com/gist/SuryanarayanaY/c0c3dfa68858d2f0abe6e3398c26f192/61600-tf-nightly.ipynb) for reference. @dmc1778 ,

Please refer to the responses of Developer team related to the exception raised https://github.com/tensorflow/tensorflow/issues/61630#issuecomment-1685333019 and https://github.com/tensorflow/tensorflow/issues/61629#issuecomment-1686504422 stating it as intended behaviour.

The Op tries to allocate the memory for the inputs and outputs before performing computations and it fails. The same error returned to python and its adding more details to error log.

As requested please read [SECURITY.md](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) to disclose these types of issues 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. This issue was closed because it has been inactive for 7 days since being marked as stale. Please reopen if you'd like to work on this further. Are you satisfied with the resolution of your issue?
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### Issue type

Bug

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

No

### Source

binary

### TensorFlow version

2.13.0

### Custom code

Yes

### OS platform and distribution

PRETTY_NAME="Ubuntu 22.04.2 LTS" NAME="Ubuntu" VERSION_ID="22.04" VERSION="22.04.2 LTS (Jammy Jellyfish)" VERSION_CODENAME=jammy ID=ubuntu ID_LIKE=debian HOME_URL="https://www.ubuntu.com/" SUPPORT_URL="https://help.ubuntu.com/" BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/" PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy" UBUNTU_CODENAME=jammy

### Mobile device

_No response_

### Python version

3.10.12 (main, Jun 11 2023, 05:26:28)

### Bazel version

_No response_

### GCC/compiler version

[GCC 11.4.0]

### CUDA/cuDNN version

[nvidia-cudnn-cu11==8.6.0.163, cudatoolkit=11.8.0](nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2022 NVIDIA Corporation Built on Wed_Sep_21_10:33:58_PDT_2022 Cuda compilation tools, release 11.8, V11.8.89 Build cuda_11.8.r11.8/compiler.31833905_0)

### GPU model and memory

T4

### Current behavior?

Due to the large list of elements

### Standalone code to reproduce the issue

```shell
import tensorflow as tf
import os
import numpy as np
try:
  diagonal_0_0_0 = []
  diagonal_0_0_1_0 = True
  diagonal_0_0_1_1 = 1122
  diagonal_0_0_1 = [diagonal_0_0_1_0,diagonal_0_0_1_1,]
  diagonal_0_0 = [diagonal_0_0_0,diagonal_0_0_1,]
  diagonal_0_1_0_0 = 1211
  diagonal_0_1_0_1 = 1212
  diagonal_0_1_0 = [diagonal_0_1_0_0,diagonal_0_1_0_1,]
  diagonal_0_1_1_0 = 1221
  diagonal_0_1_1_1 = 1222
  diagonal_0_1_1 = [diagonal_0_1_1_0,diagonal_0_1_1_1,]
  diagonal_0_1 = [diagonal_0_1_0,diagonal_0_1_1,]
  diagonal_0 = [diagonal_0_0,diagonal_0_1,]
  diagonal_1_0_0_0 = True
  diagonal_1_0_0_1 = ""
  diagonal_1_0_0 = [diagonal_1_0_0_0,diagonal_1_0_0_1,]
  diagonal_1_0_1_0 = 2121
  diagonal_1_0_1_1 = 2122
  diagonal_1_0_1 = [diagonal_1_0_1_0,diagonal_1_0_1_1,]
  diagonal_1_0 = [diagonal_1_0_0,diagonal_1_0_1,]
  diagonal_1_1_0_0 = 2211
  diagonal_1_1_0_1 = 2212
  diagonal_1_1_0 = [diagonal_1_1_0_0,diagonal_1_1_0_1,]
  diagonal_1_1_1_0 = 30.0
  diagonal_1_1_1_1 = 2222
  diagonal_1_1_1 = [diagonal_1_1_1_0,diagonal_1_1_1_1,]
  diagonal_1_1 = [diagonal_1_1_0,diagonal_1_1_1,]
  diagonal_1 = [diagonal_1_0,diagonal_1_1,]
  diagonal = [diagonal_0,diagonal_1,]
  name = "None"
  k = 1610612736
  padding_value = 0
  align = "RIGHT_LEFT"
  out = tf.linalg.diag(diagonal=diagonal,name=name,k=k,padding_value=padding_value,align=align,)
except Exception as e:
  print("Error:"+str(e))
```
```


### Relevant log output

```shell
Error:{{function_node __wrapped__MatrixDiagV3_device_/job:localhost/replica:0/task:0/device:GPU:0}} Encountered overflow when multiplying 12884901888 with 1610612736, result: -1
	 [[{{node MatrixDiagV3}}]] [Op:MatrixDiagV3]
```
```
