parameters: (condition, x, y, name=None)
docstring: Return elements from x or y depending on condition.
  
    See `tf.where` for more details. This function currently only implements the
    three argument version of where.
  
    Args:
      condition: LabeledTensor of type `bool`.
      x: LabeledTensor for values where condition is true.
      y: LabeledTensor for values where condition is false.
      name: Optional op name.
  
    Returns:
      The labeled tensor with values according to condition.
  
    Raises:
      ValueError: if `x` and `y` have different axes, or if the axes of `x` do not
        start with the axes of `condition`.
docstring_summary: Return elements from x or y depending on condition.
docstring_tokens: Return elements from x or y depending on condition .
function: def where(condition, x, y, name=None):
    """Return elements from x or y depending on condition.
  
    See `tf.where` for more details. This function currently only implements the
    three argument version of where.
  
    Args:
      condition: LabeledTensor of type `bool`.
      x: LabeledTensor for values where condition is true.
      y: LabeledTensor for values where condition is false.
      name: Optional op name.
  
    Returns:
      The labeled tensor with values according to condition.
  
    Raises:
      ValueError: if `x` and `y` have different axes, or if the axes of `x` do not
        start with the axes of `condition`.
    """
    with ops.name_scope(name, 'lt_where', [condition, x, y]) as scope:
      condition = core.convert_to_labeled_tensor(condition)
      x = core.convert_to_labeled_tensor(x)
      y = core.convert_to_labeled_tensor(y)
  
      if not condition.axes == x.axes == y.axes:
        raise ValueError('all inputs to `where` must have equal axes')
  
      op = array_ops.where(condition.tensor, x.tensor, y.tensor, name=scope)
      return core.LabeledTensor(op, x.axes)
function_tokens: def where ( condition , x , y , name = None ) : with ops . name_scope ( name , 'lt_where' , [ condition , x , y ] ) as scope : condition = core . convert_to_labeled_tensor ( condition ) x = core . convert_to_labeled_tensor ( x ) y = core . convert_to_labeled_tensor ( y ) if not condition . axes == x . axes == y . axes : raise ValueError ( 'all inputs to `where` must have equal axes' ) op = array_ops . where ( condition . tensor , x . tensor , y . tensor , name = scope ) return core . LabeledTensor ( op , x . axes )