core dumped with Conv2DBackpropFilter
@GwiHwan-Go I tried to replicate the issue reported in both TF [v2.14](https://colab.research.google.com/gist/sushreebarsa/4303b9fd7d7e08b6e3d08631d24c9fcd/62142.ipynb#scrollTo=n-zt9Xm8Z7oy) , tf-[nightly](https://colab.research.google.com/gist/sushreebarsa/3260a844f3a8be89da01fce7e053ffbd/untitled890.ipynb#scrollTo=n-zt9Xm8Z7oy) and didn't face the error reported. Could you please have a look at this gists and confirm the same? The error log is attached below;
```
**InvalidArgumentError                      Traceback (most recent call last)
[<ipython-input-2-b326ca390b51>](https://localhost:8080/#) in <cell line: 10>()
      8  'padding': 'VALID', 'strides': [3],
      9  'use_cudnn_on_gpu': True}
---> 10 res = tf.raw_ops.Conv2DBackpropFilter(**args)
     11 print(res)

3 frames
[/usr/local/lib/python3.10/dist-packages/tensorflow/python/eager/execute.py](https://localhost:8080/#) in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
     51   try:
     52     ctx.ensure_initialized()
---> 53     tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
     54                                         inputs, attrs, num_outputs)
     55   except core._NotOkStatusException as e:

InvalidArgumentError: {{function_node __wrapped__Conv2DBackpropFilter_device_/job:localhost/replica:0/task:0/device:CPU:0}} Sliding window strides field must specify 4 dimensions [Op:Conv2DBackpropFilter]**
```
Thank you! I've upgraded TensorFlow from version v1.12.1-100714-gd8e55c05473 to 2.15.0-dev20231005, as indicated in the logs below. Despite the upgrade, I'm still encountering a "core dumped" error, also provided below.
```
023-10-18 15:47:55.233348: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
2023-10-18 15:47:55.233380: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
2023-10-18 15:47:55.234739: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2023-10-18 15:47:55.242401: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-10-18 15:47:56.170911: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
2023-10-18 15:47:58.000540: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1924] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 727 MB memory:  -> device: 0, name: NVIDIA GeForce RTX 2070, pci bus id: 0000:02:00.0, compute capability: 7.5
2023-10-18 15:47:58.001140: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1924] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 6732 MB memory:  -> device: 1, name: NVIDIA GeForce RTX 2070, pci bus id: 0000:04:00.0, compute capability: 7.5
2023-10-18 15:47:58.001643: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1924] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 6732 MB memory:  -> device: 2, name: NVIDIA GeForce RTX 2070, pci bus id: 0000:83:00.0, compute capability: 7.5
2023-10-18 15:47:58.002156: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1924] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 6732 MB memory:  -> device: 3, name: NVIDIA GeForce RTX 2070, pci bus id: 0000:84:00.0, compute capability: 7.5
tf version : 2.15.0-dev20231005
2023-10-18 15:47:58.050863: F ./tensorflow/core/util/tensor_format.h:428] Check failed: index >= 0 && index < num_total_dims Invalid index from the dimension: 3, 0, C
Aborted (core dumped)
```
This is my other environment information :

CUDA used to build PyTorch: 11.8
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.3 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 3.22.1
Libc version: glibc-2.35

Python version: 3.9.17 (main, Jul  5 2023, 20:41:20)  [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-86-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.1.105
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: 
GPU 0: NVIDIA GeForce RTX 2070
GPU 1: NVIDIA GeForce RTX 2070
GPU 2: NVIDIA GeForce RTX 2070
GPU 3: NVIDIA GeForce RTX 2070

Nvidia driver version: 535.104.12
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                       x86_64
CPU op-mode(s):                     32-bit, 64-bit
Address sizes:                      46 bits physical, 48 bits virtual
Byte Order:                         Little Endian
CPU(s):                             32
On-line CPU(s) list:                0-31
Vendor ID:                          GenuineIntel
Model name:                         Intel(R) Xeon(R) CPU E5-2630 v3 @ 2.40GHz
CPU family:                         6
Model:                              63
Thread(s) per core:                 2
Core(s) per socket:                 8
Socket(s):                          2
Stepping:                           2
CPU max MHz:                        3200.0000
CPU min MHz:                        1200.0000
BogoMIPS:                           4793.99
Flags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm cpuid_fault epb invpcid_single pti ssbd ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm xsaveopt cqm_llc cqm_occup_llc dtherm ida arat pln pts md_clear flush_l1d
Virtualization:                     VT-x
L1d cache:                          512 KiB (16 instances)
L1i cache:                          512 KiB (16 instances)
L2 cache:                           4 MiB (16 instances)
L3 cache:                           40 MiB (2 instances)
NUMA node(s):                       2
NUMA node0 CPU(s):                  0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30
NUMA node1 CPU(s):                  1,3,5,7,9,11,13,15,17,19,21,23,25,27,29,31
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit:        KVM: Mitigation: VMX disabled
Vulnerability L1tf:                 Mitigation; PTE Inversion; VMX conditional cache flushes, SMT vulnerable
Vulnerability Mds:                  Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Meltdown:             Mitigation; PTI
Vulnerability Mmio stale data:      Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Retbleed:             Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:           Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP conditional, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected

Versions of relevant libraries:
[pip3] numpy==1.24.3
 @GwiHwan-Go I was able to replicate the issue on colab, please find the [gist](https://colab.research.google.com/gist/sushreebarsa/e894b385f0fa20e264f16c2923df4ab8/62142.ipynb) here.
@sachinprasadhs Could you please have a look at this issue?
Thank you! What is the purpose of this bug report?  If it's to report a security issue see the [security policy](https://github.com/tensorflow/tensorflow/security/policy) and report through the proper channel. Are you satisfied with the resolution of your issue?
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=Yes&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/62142">Yes</a>
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=No&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/62142">No</a>

### Issue type

Bug

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

Yes

### Source

source

### TensorFlow version

v1.12.1-100714-gd8e55c05473 2.15.0-dev20231005

### Custom code

Yes

### OS platform and distribution

Ubuntu 22.04.3 LTS (x86_64)

### Mobile device

_No response_

### Python version

_No response_

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

11.8

### GPU model and memory

_No response_

### Current behavior?

core dumped error with specific input parameters.

### Standalone code to reproduce the issue

```shell
import tensorflow as tf 
args = {'data_format': 'NHWC', 
 'dilations': [1], 
 'explicit_paddings': [2], 
 'filter_sizes': [3], 
 'input': tf.random.normal([2, 7]), 
 'out_backprop': tf.random.normal([10]), 
 'padding': 'VALID', 'strides': [3], 
 'use_cudnn_on_gpu': True}
res = tf.raw_ops.Conv2DBackpropFilter(**args)
print(res)
```


### Relevant log output

```shell
2023-10-18 01:54:46.384973: F ./tensorflow/core/util/tensor_format.h:428] Check failed: index >= 0 && index < num_total_dims Invalid index from the dimension: 3, 0, C
Aborted (core dumped)
```
