Lambda transform should allow type conversion based on user-defined function

[surajpaib]

Is your feature request related to a problem? Please describe.
In the current implementation of Lambda transform, it always forces a conversion to MetaTensor when the output type is a numpy.ndarray or torch.Tensor and metadata tracking is enabled (default). This behavior may not be suitable for every use case, as it can lead to unnecessary conversions in certain scenarios.

In my current use case, my last transform attempts to convert from MetaTensor to Tensor so that I can use it for DDP with SyncBatchNorm #5198

I'd expect it to convert to whatever format is specified in the lambda function by the user.

Describe the solution you'd like
Allow the Lambda transform to return the initial output type without forcing a conversion to MetaTensor. This could be achieved by introducing an optional parameter (e.g., track_meta: bool = True) in the constructor and modifying the code accordingly. This parameter seems to already exist for other functions like convert_to_tensor

Describe alternatives you've considered
I now use torchvision.transforms.Lambda as a replacement.

[surajpaib]

Happy to make a PR for this as well!