class_docstr: Represents data from mars tensor
code: def _call_tensor_none(
      self,
      index: Union[TileableType, pd.Index],
      columns: pd.Index,
      dtypes: pd.Series,
  ):
      inputs = []
      shape = []
      if index is not None:
          index_value = self._process_index(index, inputs)
          shape.append(index.shape[0])
      else:
          index = self.index = pd.Index([], dtype=object)
          index_value = parse_index(index)
          shape.append(0)
  
      if columns is not None:
          if not isinstance(columns, pd.Index):
              if isinstance(columns, ENTITY_TYPE):
                  raise NotImplementedError(
                      "The columns value cannot be a tileable"
                  )
              columns = pd.Index(columns)
          columns_value = parse_index(columns, store_data=True)
          shape.append(columns.shape[0])
      else:
          columns_value = parse_index(
              pd.Index([], dtype=object), store_data=True
          )
          shape.append(0)
  
      return self.new_dataframe(
          inputs,
          shape=tuple(shape),
          dtypes=dtypes,
          index_value=index_value,
          columns_value=columns_value,
      )
  
imports: from collections import OrderedDict
  from typing import Any, Dict, List, Union
  import numpy
  import pandas
  from ...None import opcodes
  from ...core import ENTITY_TYPE, OutputType, recursive_tile
  from ...core.context import Context
  from ...serialization.serializables import KeyField, AnyField
  from ...tensor.core import Tensor
  from ...tensor.datasource import tensor
  from ...tensor.utils import unify_chunks
  from ...typing import EntityType, TileableType
  from ...utils import has_unknown_shape
  from ..core import INDEX_TYPE, SERIES_TYPE
  from ..operands import DataFrameOperand, DataFrameOperandMixin
  from ..utils import parse_index
label_desc: Use image node_id 7 for calling the DataFrameFromTensor obj's underlying member method code with example usage: obj._call_tensor_none(index, columns, dtypes) and returns: self