Cannot use extended batch shape with channel_first Conv2D
@Yang-Yuan Thanks for reporting an issue!
Could you please elaborate the issue here by stating the example if you are using any. 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. 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?

No

### Source

source

### Tensorflow Version

2.12

### Custom Code

Yes

### OS Platform and Distribution

Ubuntu 1804

### 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

_No response_

### Current Behaviour?

```shell
Given input tensor for shape, say [batch_dim_1 = 4, batch_dim_2 = 5, channels = 6, Height = 7, Width = 8] to a channels_first (keras) Conv2D of stride 2, the "_get_sequence" function at Line 1288 in nn_ops.py sets strides to [1, 2, 2, 1], which is wrong. Strides should be [1, 1, 2, 2] for the input tensor will be reshaped to [batch_dim_1 * batch_dim_2, channels, Height, Width] later in squeeze_batch_dim in nn_ops.py.
```


### Standalone code to reproduce the issue

```shell
As described above.
```


### Relevant log output

_No response_</details>