class_docstr: Track Activeloop Deeplake Dataset with versioning.
  
  It is generally advised to commit dataset changes before logging to runs. If dataset is a view on head of
  uncommitted changes, it's recommmended to commit dataset changes first then creating a view and loggging it.
  By default, this is ignored and results in limited traceability. Set both ``auto_commit`` and ``auto_save_view``
  to ``True`` for automatic commit or saves.
  Unsaved views created on a dataset head with changes passed to this class cannot be saved.
  
  :param auto_commit: If dataset head node and uncommitted dataset changes are present an auto_commit
      will trigger a dataset commit ``autocommit on aim run`` to enable reproducibility of the run,
      defaults to ``False``.
  
  :param auto_save_view: Triggers a save of a view if dataset is an unsaved view on a committed head
      to enable reproducibility of the run, defaults to ``False``.
  
  :raises TypeError: if the dataset is not a deeplake.Dataset
  :raises ValueError: if the dataset is a view and has uncommitted changes on its head but should be saved.
  
  .. code-block:: python
  
      import deeplake
  
      from aim.sdk.objects.plugins.deeplake_dataset import DeeplakeDataset
      from aim.sdk import Run
  
      # create dataset object
      ds = deeplake.dataset('hub://activeloop/cifar100-test')
  
      # log dataset metadata
      run = Run(system_tracking_interval=None)
      run['deeplake_ds'] = DeeplakeDataset(ds)
code: def _tensor_meta(self, tensor: deeplake.Tensor):
      meta = tensor.meta
      return {
          "name": tensor.key,
          "num_samples": len(tensor),
          "htype": tensor.htype,
          "dtype": str(tensor.dtype) if tensor.dtype else None,
          "compression_type": "sample_compression"
          if meta.sample_compression
          else (
              "chunk_compression" if meta.chunk_compression else None
          ),
          "compression_format": meta.sample_compression
          or meta.chunk_compression,
          "info": dict(tensor.info),
      }
  
file_path: aim/aim/sdk/objects/plugins/deeplake_dataset.py
imports: from aim.storage.object import CustomObject
  import deeplake
  import warnings
  import logging
  from deeplake.util.exceptions import ReadOnlyModeError
label_desc: Use image node_id 3 for calling the DeeplakeDataset obj's underlying member method code with example usage: obj._tensor_meta(tensor) and returns: dict