Change default value of patch_norm to False in SwinUNETR (#8249)

Fixes #8248

### Description

Update the default value of `patch_norm` to False in `SwinUNETR` to
align with the default value in `SwinTransformer`. This
[change](3ee4cd2#diff-04583cc0f4aed09787775eec8cece2b1fd70290799a7a3a2671353f2a3cf9af3R105)
modifies the default behavior of the model

https://github.com/Project-MONAI/MONAI/blob/e6cae1ced23f32feb2f42943d15b7dd49481c794/monai/networks/nets/swin_unetr.py#L960


### Types of changes
<!--- Put an `x` in all the boxes that apply, and remove the not
applicable items -->
- [x] Non-breaking change (fix or new feature that would not break
existing functionality).
- [ ] Breaking change (fix or new feature that would cause existing
functionality to change).
- [ ] New tests added to cover the changes.
- [ ] Integration tests passed locally by running `./runtests.sh -f -u
--net --coverage`.
- [ ] Quick tests passed locally by running `./runtests.sh --quick
--unittests --disttests`.
- [ ] In-line docstrings updated.
- [ ] Documentation updated, tested `make html` command in the `docs/`
folder.

Signed-off-by: YunLiu <[email protected]>

Author: KumoLiu

monai/networks/nets/swin_unetr.py

@@ -75,7 +75,7 @@ def __init__(
         dropout_path_rate: float = 0.0,
         normalize: bool = True,
         norm_layer: type[LayerNorm] = nn.LayerNorm,
-        patch_norm: bool = True,
+        patch_norm: bool = False,
         use_checkpoint: bool = False,
         spatial_dims: int = 3,
         downsample: str | nn.Module = "merging",
@@ -102,7 +102,7 @@ def __init__(
             dropout_path_rate: drop path rate.
             normalize: normalize output intermediate features in each stage.
             norm_layer: normalization layer.
-            patch_norm: whether to apply normalization to the patch embedding.
+            patch_norm: whether to apply normalization to the patch embedding. Default is False.
             use_checkpoint: use gradient checkpointing for reduced memory usage.
             spatial_dims: number of spatial dims.
             downsample: module used for downsampling, available options are `"mergingv2"`, `"merging"` and a