text: Title: `NotImplementedError` for elastic transformation with probability p < 1
  Body: ### Describe the bug
  
  With the newest kornia release (0.6.11), the random elastic transformation fails if it is not applied to every image in the batch.
  
  The problem is that the `apply_non_transform_mask()` method in `_AugmentationBase` per default raises an `NotImplementedError` and since this method is not overwritten in `RandomElasticTransform`, the error is raised. I see that for the other `apply_non*` methods the default is to just return the input.
  
  I see two different solutions:
  1. Change the default for `apply_non_transform_mask` to return the input in `_AugmentationBase`.
  2. Overwrite the method in `RandomElasticTransform` and just return the input there.
  
  There might be good reasons to keep the `NotImplementedError` in the base class, therefore I wanted to ask first what solution you prefer. I could make a PR for this.
  
  ### Reproduction steps
  
  ```python
  import torch
  import kornia.augmentation as K
  
  features = torch.rand(5, 100, 480, 640, dtype=torch.float32, device="cuda")
  labels = torch.randint(0, 10, (5, 1, 480, 640), dtype=torch.int64, device="cuda")
  
  torch.manual_seed(0)
  aug = K.AugmentationSequential(
      K.RandomElasticTransform(alpha=(0.7, 0.7), sigma=(16, 16), padding_mode="reflection", p=0.2)
  )
  
  features_transformed, labels_transformed = aug(features, labels.float(), data_keys=["input", "mask"])
  ```
  
  
  ### Expected behavior
  
  No `NotImplementedError`.
  
  ### Environment
  
  ```shell
  wget https://raw.githubusercontent.com/pytorch/pytorch/master/torch/utils/collect_env.py
  # For security purposes, please check the contents of collect_env.py before running it.
  python collect_env.py
  ```
  - PyTorch Version (e.g., 1.0): 2.0
  - OS (e.g., Linux): Linux
  - How you installed PyTorch (`conda`, `pip`, source): pip
  - Build command you used (if compiling from source):
  - Python version: 3.10.9
  - CUDA/cuDNN version: 11.8
  - GPU models and configuration: 3090
  - Any other relevant information:
  ```