parameters: (self)
return_statement: return tf.constant([self._box_coder.code_size * [0]], tf.float32)
docstring: Returns the default target for anchors to regress to.
  
          Default regression targets are set to zero (though in
          this implementation what these targets are set to should
          not matter as the regression weight of any box set to
          regress to the default target is zero).
  
          Returns:
            default_target: a float32 tensor with shape [1, box_code_dimension]
docstring_summary: Returns the default target for anchors to regress to.
docstring_tokens: Returns the default target for anchors to regress to .
function: def _default_regression_target(self):
          """Returns the default target for anchors to regress to.
  
          Default regression targets are set to zero (though in
          this implementation what these targets are set to should
          not matter as the regression weight of any box set to
          regress to the default target is zero).
  
          Returns:
            default_target: a float32 tensor with shape [1, box_code_dimension]
          """
          return tf.constant([self._box_coder.code_size * [0]], tf.float32)
function_tokens: def _default_regression_target ( self ) : return tf . constant ( [ self . _box_coder . code_size * [ 0 ] ] , tf . float32 )