parameters: (self, name, input_names, output_name)
return_statement: return spec_layer
docstring: Add a broadcast_to_dynamic layer to the model that broadcasts a tensor
          to a compatible shape.
          Refer to the **BroadcastToDynamicLayerParams** message in specification
          (NeuralNetwork.proto) for more details.
  
          Parameters
          ----------
          name: str
              The name of this layer.
          input_names: list of str
              The input blob names of this layer.
          output_name: str
              The output blob name of this layer.
  
          See Also
          --------
          add_broadcast_to_like, add_broadcast_to_static
docstring_summary: Add a broadcast_to_dynamic layer to the model that broadcasts a tensor
          to a compatible shape.
          Refer to the **BroadcastToDynamicLayerParams** message in specification
          (NeuralNetwork.proto) for more details.
docstring_tokens: Add a broadcast_to_dynamic layer to the model that broadcasts a tensor to a compatible shape . Refer to the ** BroadcastToDynamicLayerParams ** message in specification ( NeuralNetwork . proto ) for more details .
function: def add_broadcast_to_dynamic(self, name, input_names, output_name):
          """
          Add a broadcast_to_dynamic layer to the model that broadcasts a tensor
          to a compatible shape.
          Refer to the **BroadcastToDynamicLayerParams** message in specification
          (NeuralNetwork.proto) for more details.
  
          Parameters
          ----------
          name: str
              The name of this layer.
          input_names: list of str
              The input blob names of this layer.
          output_name: str
              The output blob name of this layer.
  
          See Also
          --------
          add_broadcast_to_like, add_broadcast_to_static
          """
  
          spec_layer = self._add_generic_layer(name, input_names, [output_name])
          spec_layer.broadcastToDynamic.MergeFromString(b"")
          # Setting rank to -1 is a hint that Rank was not computed
          # converter can modify if it's a constant and known
          self.rank_dict[output_name] = -1
          return spec_layer
function_tokens: def add_broadcast_to_dynamic ( self , name , input_names , output_name ) : spec_layer = self . _add_generic_layer ( name , input_names , [ output_name ] ) spec_layer . broadcastToDynamic . MergeFromString ( b"" ) # Setting rank to -1 is a hint that Rank was not computed # converter can modify if it's a constant and known self . rank_dict [ output_name ] = - 1 return spec_layer