class_docstr: Multi-Node Multi-GPU implementation of DBSCAN.
  
  The whole dataset is copied to all the workers but the work is then
  divided by giving "ownership" of a subset to each worker: each worker
  computes a clustering by considering the relationships between those
  points and the rest of the dataset, and partial results are merged at
  the end to obtain the final clustering.
  
  Parameters
  ----------
  client : dask.distributed.Client
      Dask client to use
  verbose : int or boolean, default=False
      Sets logging level. It must be one of `cuml.common.logger.level_*`.
      See :ref:`verbosity-levels` for more info.
  min_samples : int (default = 5)
      The number of samples in a neighborhood such that this group can be
      considered as an important core point (including the point itself).
  max_mbytes_per_batch : (optional) int64
      Calculate batch size using no more than this number of megabytes for
      the pairwise distance computation. This enables the trade-off between
      runtime and memory usage for making the N^2 pairwise distance
      computations more tractable for large numbers of samples.
      If you are experiencing out of memory errors when running DBSCAN, you
      can set this value based on the memory size of your device.
      Note: this option does not set the maximum total memory used in the
      DBSCAN computation and so this value will not be able to be set to
      the total memory available on the device.
  output_type : {'input', 'array', 'dataframe', 'series', 'df_obj',         'numba', 'cupy', 'numpy', 'cudf', 'pandas'}, default=None
      Return results and set estimator attributes to the indicated output
      type. If None, the output type set at the module level
      (`cuml.global_settings.output_type`) will be used. See
      :ref:`output-data-type-configuration` for more info.
  calc_core_sample_indices : (optional) boolean (default = True)
      Indicates whether the indices of the core samples should be calculated.
      The the attribute `core_sample_indices_` will not be used, setting this
      to False will avoid unnecessary kernel launches
  
  Notes
  -----
  For additional docs, see the documentation of the single-GPU DBSCAN model
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code: def get_param_names(self):
      return list(self.kwargs.keys())
  
file_path: cuml/python/cuml/dask/cluster/dbscan.py
imports: from cuml.internals.memory_utils import with_cupy_rmm
  from cuml.dask.common.utils import wait_and_raise_from_futures
  from raft_dask.common.comms import get_raft_comm_state
  from raft_dask.common.comms import Comms
  from cuml.dask.common.base import mnmg_import
  from dask.distributed import get_worker
  from cuml.dask.common.base import DelayedTransformMixin
  from cuml.dask.common.base import DelayedPredictionMixin
  from cuml.dask.common.base import BaseEstimator
  from cuml.internals.safe_imports import cpu_only_import
label_desc: Use image node_id 5 for calling the DBSCAN obj's underlying member method code with example usage: obj.get_param_names() and returns: list