[heterps]remove api for heter pipeline ps (PaddlePaddle#37396)

* fix api. test=develop * fix api. test=develop
zmxdream · Nov 22, 2021 · 17a4b50 · 17a4b50
1 parent 7f020d9
commit 17a4b50
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diff --git a/python/paddle/distributed/fleet/__init__.py b/python/paddle/distributed/fleet/__init__.py
@@ -68,14 +68,11 @@
 server_index = fleet.server_index
 server_endpoints = fleet.server_endpoints
 is_server = fleet.is_server
-is_heter_worker = fleet.is_heter_worker
 util = UtilBase()
 barrier_worker = fleet.barrier_worker
 init_worker = fleet.init_worker
-init_heter_worker = fleet.init_heter_worker
 init_server = fleet.init_server
 run_server = fleet.run_server
-run_heter_worker = fleet.run_heter_worker
 stop_worker = fleet.stop_worker
 distributed_optimizer = fleet.distributed_optimizer
 save_inference_model = fleet.save_inference_model

diff --git a/python/paddle/distributed/fleet/base/fleet_base.py b/python/paddle/distributed/fleet/base/fleet_base.py
@@ -565,24 +565,6 @@ def is_server(self):
         """
         return self._role_maker._is_server()
 
-    def is_heter_worker(self):
-        """
-        Check whether the node is an instance of heter worker.
-
-        Returns:
-            bool: True if this is a node of heter worker,
-                  False if not.
-
-        Examples:
-
-            .. code-block:: python
-
-                import paddle.distributed.fleet as fleet
-                fleet.init()
-                fleet.is_heter_worker()
-        """
-        return self._role_maker._is_heter_worker()
-
     def barrier_worker(self):
         """
         barrier all workers
@@ -617,30 +599,6 @@ def init_worker(self):
         """
         self._runtime_handle._init_worker()
 
-    @is_non_distributed_check
-    @inited_runtime_handler
-    def init_heter_worker(self):
-        """
-        init_heter_worker executor to initialize startup program,
-
-        Returns:
-            None
-
-        Examples:
-
-            .. code-block:: python
-
-                import paddle.distributed.fleet as fleet
-                fleet.init()
-
-                # build net
-                # fleet.distributed_optimizer(...)
-
-                fleet.init_heter_worker()
-
-        """
-        self._runtime_handle._init_heter_worker()
-
     @is_non_distributed_check
     @inited_runtime_handler
     def init_server(self, *args, **kwargs):
@@ -690,31 +648,6 @@ def load_model(self, path, mode):
         """
         self._runtime_handle.load_model(path, mode)
 
-    @is_non_distributed_check
-    @inited_runtime_handler
-    def run_heter_worker(self, dataset):
-        """
-        run_heter_worker will run heter trainer main program with executor.
-
-        Returns:
-            None
-
-        Examples:
-
-            .. code-block:: python
-
-                import paddle.distributed.fleet as fleet
-                fleet.init()
-
-                # build net
-                # fleet.distributed_optimizer(...)
-                dataset = "" 
-                if fleet.is_heter_worker():
-                    fleet.run_heter_worker(dataset)
-
-        """
-        self._runtime_handle._run_heter_worker(dataset)
-
     @is_non_distributed_check
     @inited_runtime_handler
     def run_server(self):

diff --git a/python/paddle/distributed/fleet/runtime/the_one_ps.py b/python/paddle/distributed/fleet/runtime/the_one_ps.py
@@ -880,33 +880,6 @@ def _run_server(self):
         host, port = ep.split(":")
         self._server.run_server(host, int(port))
 
-    def _init_heter_worker(self):
-        executor = self._get_executor()
-        startup_program = fluid.default_startup_program()
-        #real_startup_program = startup_program._heter_pipeline_opt[
-        #    "startup_program"]
-        executor.run(startup_program)
-        self._init_worker()
-
-    def _run_heter_worker(self,
-                          dataset=None,
-                          scope=None,
-                          thread=0,
-                          debug=False,
-                          fetch_list=None,
-                          fetch_info=None,
-                          print_period=100,
-                          fetch_handler=None):
-        executor = self._get_executor()
-        # dataset is not needed for heter worker
-        executor.train_from_dataset(
-            program=fluid.default_main_program(),
-            dataset=None,
-            debug=debug,
-            fetch_list=fetch_list,
-            fetch_info=fetch_info,
-            print_period=print_period)
-
     def _stop_worker(self):
         self._communicator.stop()
         if self.role_maker._is_heter_parameter_server_mode: