A check fail can be triggered in DepthwiseConv2dNativeBackpropInput
@shijy16,
I tried to execute the mentioned code on both tensorflow v2.12 [CPU](https://colab.research.google.com/gist/tilakrayal/567f4b305c69b199c9db8448f6763eab/untitled1064.ipynb) and [GPU](https://colab.research.google.com/gist/tilakrayal/047904e5371c1ffd7bdfe92a024b490f/untitled1065.ipynb) & it was executing with the different error where it was mentioned that **Current implementation only supports equal length strides in the row and column dimensions** and also I was not able to get any crash/abort for the mentioned code. Thank you!  @tilakrayal 
Hi, I can still replicate this bug on my local machine. I think this is a **Intel OneDNN library** related bug, and Intel OneDNN is not supported on Colab. 
Intel OneDNN is enabled by default on my local machine, thus the crash can be replicated. If I disable Intel OneDNN as the code bellow, the same error in Colab is thrown.
````python
import os
os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'
import tensorflow as tf
print(tf.__version__)
with tf.device("CPU"):
    strides = [1, 0, 1, 1]
    padding = "VALID"
    explicit_paddings = []
    data_format = "NHWC"
    dilations = [1, 0, 77, 1, 64]
    input_sizes = tf.saturate_cast(tf.random.uniform([3], minval=-1024, maxval=1024, dtype=tf.int64), dtype=tf.int32)
    filter = tf.random.uniform([16, 3, 3, 5], dtype=tf.bfloat16, minval=-1024, maxval=1024)
    out_backprop = tf.random.uniform([1, 0, 0, 1], dtype=tf.bfloat16, minval=-1024, maxval=1024)
    res = tf.raw_ops.DepthwiseConv2dNativeBackpropInput(
        strides=strides,
        padding=padding,
        explicit_paddings=explicit_paddings,
        data_format=data_format,
        dilations=dilations,
        input_sizes=input_sizes,
        filter=filter,
        out_backprop=out_backprop,
    )
```` @shijy16 Please don't file vulnerabilities on GitHub. Please consult https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md and follow rules for responsible disclosure. Hi @shijy16 
This has been fixed. tested with TF2.16v and found raising an exception rather than check fail.Please refer attached [gist](https://colab.sandbox.google.com/gist/SuryanarayanaY/09759376b26be8e89764152672ae2eaa/60201_nightly_success.ipynb).

Thanks! 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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<details><summary>Click to expand!</summary> 
 
 ### Issue Type

Bug

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

Yes

### Source

binary

### Tensorflow Version

2.13.0-dev20230331

### Custom Code

Yes

### OS Platform and Distribution

Linux Ubuntu 20.04

### Mobile device

_No response_

### Python version

3.10

### Bazel version

_No response_

### GCC/Compiler version

_No response_

### CUDA/cuDNN version

CUDA 11.8

### GPU model and memory

_No response_

### Current Behaviour?

```shell
The following code can trigger a crash in `tf.raw_ops.DepthwiseConv2dNativeBackpropInput` due to check-fail in the latest version of TensorFlow.
```


### Standalone code to reproduce the issue

```shell
import tensorflow as tf
with tf.device("CPU"):
    strides = [1, 0, 1, 1]
    padding = "VALID"
    explicit_paddings = []
    data_format = "NHWC"
    dilations = [1, 0, 77, 1, 64]
    input_sizes = tf.saturate_cast(tf.random.uniform([3], minval=-1024, maxval=1024, dtype=tf.int64), dtype=tf.int32)
    filter = tf.random.uniform([16, 3, 3, 5], dtype=tf.bfloat16, minval=-1024, maxval=1024)
    out_backprop = tf.random.uniform([1, 0, 0, 1], dtype=tf.bfloat16, minval=-1024, maxval=1024)
    res = tf.raw_ops.DepthwiseConv2dNativeBackpropInput(
        strides=strides,
        padding=padding,
        explicit_paddings=explicit_paddings,
        data_format=data_format,
        dilations=dilations,
        input_sizes=input_sizes,
        filter=filter,
        out_backprop=out_backprop,
    )
```


### Relevant log output

```shell
2023-04-01 16:37:53.415934: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2023-04-01 16:37:53.465275: 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 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-04-01 16:37:54.257156: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
2023-04-01 16:37:55.809665: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1635] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 14561 MB memory:  -> device: 0, name: Tesla V100-PCIE-16GB, pci bus id: 0000:2f:00.0, compute capability: 7.0
2023-04-01 16:37:55.854746: F tensorflow/core/kernels/mkl/mkl_conv_grad_input_ops.cc:537] Non-OK-status: tensor::MakeShape(input_tensor, &input_tf_shape) status: INVALID_ARGUMENT: Dimension -510 must be >= 0
Aborted (core dumped)
```
</details>