parameters: (labels, name='')
return_statement: return labels_to_graph(labels, name)
docstring: Conversion node from labels to graph. Typically used as an input to ForwardBackward node.
      This node's objective is to transform input labels into a graph representing exact forward-backward criterion.
  
      Example:
          >>> num_classes = 2
          >>> labels = C.input_variable((num_classes))
          >>> graph = C.labels_to_graph(labels)
  
      Args:
          labels: input training labels
      Returns:
          :class:`~cntk.ops.functions.Function`
docstring_summary: Conversion node from labels to graph. Typically used as an input to ForwardBackward node.
      This node's objective is to transform input labels into a graph representing exact forward-backward criterion.
docstring_tokens: Conversion node from labels to graph . Typically used as an input to ForwardBackward node . This node s objective is to transform input labels into a graph representing exact forward - backward criterion .
function: def labels_to_graph(labels, name=''):
      '''
      Conversion node from labels to graph. Typically used as an input to ForwardBackward node.
      This node's objective is to transform input labels into a graph representing exact forward-backward criterion.
  
      Example:
          >>> num_classes = 2
          >>> labels = C.input_variable((num_classes))
          >>> graph = C.labels_to_graph(labels)
  
      Args:
          labels: input training labels
      Returns:
          :class:`~cntk.ops.functions.Function`
      '''
      from cntk.cntk_py import labels_to_graph
      dtype = get_data_type(labels)
      labels = sanitize_input(labels, dtype)
      return labels_to_graph(labels, name)
function_tokens: def labels_to_graph ( labels , name = '' ) : from cntk . cntk_py import labels_to_graph dtype = get_data_type ( labels ) labels = sanitize_input ( labels , dtype ) return labels_to_graph ( labels , name )