The `Operation` objects on which this op has a control dependency. Before this op is executed, TensorFlow will ensure that the operations in `self.control_inputs` have finished executing. This mechanism can be used to run ops sequentially for performance reasons, or to ensure that t
(self)
| 2192 | |
| 2193 | @property |
| 2194 | def control_inputs(self): |
| 2195 | """The `Operation` objects on which this op has a control dependency. |
| 2196 | |
| 2197 | Before this op is executed, TensorFlow will ensure that the |
| 2198 | operations in `self.control_inputs` have finished executing. This |
| 2199 | mechanism can be used to run ops sequentially for performance |
| 2200 | reasons, or to ensure that the side effects of an op are observed |
| 2201 | in the correct order. |
| 2202 | |
| 2203 | Returns: |
| 2204 | A list of `Operation` objects. |
| 2205 | |
| 2206 | """ |
| 2207 | control_c_ops = c_api.TF_OperationGetControlInputs_wrapper(self._c_op) |
| 2208 | # pylint: disable=protected-access |
| 2209 | return [ |
| 2210 | self.graph._get_operation_by_name_unsafe(c_api.TF_OperationName(c_op)) |
| 2211 | for c_op in control_c_ops |
| 2212 | ] |
| 2213 | # pylint: enable=protected-access |
| 2214 | |
| 2215 | @property |
| 2216 | def _control_outputs(self): |
nothing calls this directly
no test coverage detected