code: def __init__(
      self,
      data=None,
      dtype=None,
      copy=False,
      name=None,
      tupleize_cols=True,
      chunk_size=None,
      gpu=None,
      sparse=None,
      names=None,
      num_partitions=None,
      store_data=False,
  ):
      need_repart = False
      if isinstance(data, INDEX_TYPE):
          if not hasattr(data, "data"):
              # IndexData
              index = _Index(data)
          else:
              index = data
          need_repart = num_partitions is not None
      else:
          if isinstance(data, ENTITY_TYPE):
              name = (
                  name
                  if name is not None
                  else getattr(data, "name", None)
              )
              index = from_tileable_index(
                  data, dtype=dtype, name=name, names=names
              )
              need_repart = num_partitions is not None
          else:
              if not is_index(data):
                  name = (
                      name
                      if name is not None
                      else getattr(data, "name", None)
                  )
                  xdf = cudf if is_cudf(data) or is_cupy(data) else pd
                  try:
                      pd_index = xdf.Index(
                          data=data,
                          dtype=dtype,
                          copy=copy,
                          name=name,
                          tupleize_cols=tupleize_cols,
                      )
                  except TypeError:  # pragma: no cover
                      pd_index = xdf.Index(
                          data=data, dtype=dtype, copy=copy, name=name
                      )
              else:
                  pd_index = data
  
              if num_partitions is not None:
                  chunk_size = ceildiv(len(pd_index), num_partitions)
              index = from_pandas_index(
                  pd_index,
                  chunk_size=chunk_size,
                  gpu=gpu,
                  sparse=sparse,
                  store_data=store_data,
              )
  
      if need_repart:
          index = index.rebalance(num_partitions=num_partitions)
      super().__init__(index.data)
  
imports: import pandas
  from pandas.core.dtypes.common import pandas_dtype
  from ..core import ENTITY_TYPE
  from ..serialization.serializables import SerializableMeta
  from ..tensor import tensor, stack
  from ..tensor.array_utils import is_cupy
  from ..tensor.core import TENSOR_TYPE
  from ..utils import ceildiv, lazy_import
  from .core import DATAFRAME_TYPE, SERIES_TYPE, INDEX_TYPE, DataFrame, Series, Index
  from .datasource.dataframe import from_pandas
  from .datasource.series import from_pandas
  from .datasource.index import from_pandas, from_tileable
  from .datasource.from_tensor import dataframe_from_tensor, series_from_tensor, dataframe_from_1d_tileables
  from .utils import is_index, is_cudf
label_desc: Use image node_id 2 to create a new Index object from inherited base classes: _Index with example: obj = Index(data, dtype, copy, name, tupleize_cols, chunk_size, gpu, sparse, names, num_partitions, store_data)