class_docstr: _BigtableDataset represents a dataset that retrieves keys and values.
class_docstr_tok: ["_BigtableDataset","represents","a","dataset","that","retrieves","keys","and","values","."]
code: def __init__(
      self,
      client_resource,
      table_id: str,
      columns: List[str],
      row_set: bigtable_row_set.RowSet,
      filter,
      output_type,
  ):
      self._table_id = table_id
      self._columns = columns
      self._filter = filter
      self._element_spec = tf.TensorSpec(
          shape=[len(columns)], dtype=output_type
      )
  
      variant_tensor = core_ops.bigtable_dataset(
          client_resource,
          row_set._impl,
          filter._impl,
          table_id,
          columns,
          output_type,
      )
      super().__init__(variant_tensor)
  
imports: from typing import List
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.framework import tensor_spec
  from tensorflow_io.python.ops import core_ops
  import tensorflow_io.python.ops.bigtable.bigtable_version_filters
  import tensorflow_io.python.ops.bigtable.bigtable_row_set
  import tensorflow_io.python.ops.bigtable.bigtable_row_range
  from tensorflow.python.framework import dtypes
  import tensorflow
  from tensorflow.python.data.ops import dataset_ops
label_desc: Use image node_id 1 to create a new _BigtableDataset object from inherited base classes: dataset_ops with example: obj = _BigtableDataset(client_resource, table_id, columns, row_set, filter, output_type)