parameters: (inputs, attrs)
return_statement: return sym, out_name
docstring: Process the dense operation.
docstring_summary: Process the dense operation.
docstring_tokens: Process the dense operation .
function: def _darknet_dense(inputs, attrs):
      """Process the dense operation."""
      op_name, new_attrs = 'dense', {}
      new_attrs['units'] = _darknet_required_attr(attrs, 'num_hidden')
  
      if attrs.get('use_bias', False) is True:
          new_attrs['use_bias'] = True
      if attrs.get('use_flatten', False) is True:
          inputs[0] = _sym.flatten(inputs[0])
      sym = _darknet_get_nnvm_op(op_name)(*inputs, **new_attrs)
      out_name = sym.list_output_names()[0].replace('_output', '')
      if 'activation' in attrs:
          new_attrs = {}
          new_attrs['activation'] = attrs['activation']
          sym, _ = _darknet_activations(sym, new_attrs)
      return sym, out_name
function_tokens: def _darknet_dense ( inputs , attrs ) : op_name , new_attrs = 'dense' , { } new_attrs [ 'units' ] = _darknet_required_attr ( attrs , 'num_hidden' ) if attrs . get ( 'use_bias' , False ) is True : new_attrs [ 'use_bias' ] = True if attrs . get ( 'use_flatten' , False ) is True : inputs [ 0 ] = _sym . flatten ( inputs [ 0 ] ) sym = _darknet_get_nnvm_op ( op_name ) ( * inputs , * * new_attrs ) out_name = sym . list_output_names ( ) [ 0 ] . replace ( '_output' , '' ) if 'activation' in attrs : new_attrs = { } new_attrs [ 'activation' ] = attrs [ 'activation' ] sym , _ = _darknet_activations ( sym , new_attrs ) return sym , out_name