code: def _coordinate_where(condition):
      """Ragged version of tf.where(condition)."""
      if not isinstance(condition, ragged_tensor.RaggedTensor):
          return array_ops.where(condition)
  
      # The coordinate for each `true` value in condition.values.
      selected_coords = _coordinate_where(condition.values)
  
      # Convert the first index in each coordinate to a row index and column index.
      condition = condition.with_row_splits_dtype(selected_coords.dtype)
      first_index = selected_coords[:, 0]
      selected_rows = array_ops.gather(
          condition.value_rowids(), first_index
      )
      selected_row_starts = array_ops.gather(
          condition.row_splits, selected_rows
      )
      selected_cols = first_index - selected_row_starts
  
      # Assemble the row & column index with the indices for inner dimensions.
      return array_ops.concat(
          [
              array_ops.expand_dims(selected_rows, 1),
              array_ops.expand_dims(selected_cols, 1),
              selected_coords[:, 1:],
          ],
          axis=1,
      )
  
file_path: tensorflow/tensorflow/python/ops/ragged/ragged_where_op.py
imports: import typing
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops.ragged import ragged_concat_ops
  from tensorflow.python.ops.ragged import ragged_functional_ops
  from tensorflow.python.ops.ragged import ragged_gather_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.ops.ragged import ragged_tensor_shape
  from tensorflow.python.util import dispatch
label_desc: Use image node_id 5 for calling a global function with example usage: _coordinate_where(condition) and returns: array_ops, array_ops