diff --git a/python/paddle/distributed/fleet/fleet.py b/python/paddle/distributed/fleet/fleet.py index b0a8c2f69cc96131d424ed56e054030f5b9cf0f5..08f07e34d7298328049204a06c57d66a68e33cf4 100755 --- a/python/paddle/distributed/fleet/fleet.py +++ b/python/paddle/distributed/fleet/fleet.py @@ -1367,18 +1367,6 @@ class Fleet: copy_user_defined_strategy, ) can_not_apply_optimizer_list.append(meta_optimizer) - from .meta_optimizers import ParameterServerGraphOptimizer - - graph_optimizer = ParameterServerGraphOptimizer( - self.user_defined_optimizer - ) - graph_optimizer._set_basic_info( - loss, - self._role_maker, - self.user_defined_optimizer, - copy_user_defined_strategy, - ) - can_not_apply_optimizer_list.append(graph_optimizer) else: # compile time distributed_optimizer_list = ( diff --git a/python/paddle/distributed/fleet/meta_optimizers/__init__.py b/python/paddle/distributed/fleet/meta_optimizers/__init__.py index feb7b125adc1c83cf0c7a5b9719141be74bfa000..1e98b3432f0a24ce9b6131014a8764f6fc74165f 100644 --- a/python/paddle/distributed/fleet/meta_optimizers/__init__.py +++ b/python/paddle/distributed/fleet/meta_optimizers/__init__.py @@ -22,7 +22,6 @@ from .pipeline_optimizer import PipelineOptimizer from .localsgd_optimizer import LocalSGDOptimizer from .localsgd_optimizer import AdaptiveLocalSGDOptimizer from .lars_optimizer import LarsOptimizer -from .parameter_server_graph_optimizer import ParameterServerGraphOptimizer from .dgc_optimizer import DGCOptimizer from .dgc_optimizer import DGCMomentumOptimizer from .lamb_optimizer import LambOptimizer diff --git a/python/paddle/distributed/fleet/meta_optimizers/parameter_server_graph_optimizer.py b/python/paddle/distributed/fleet/meta_optimizers/parameter_server_graph_optimizer.py deleted file mode 100644 index e6bf8b85c202117409873ef30251c0718b522e0e..0000000000000000000000000000000000000000 --- a/python/paddle/distributed/fleet/meta_optimizers/parameter_server_graph_optimizer.py +++ /dev/null @@ -1,78 +0,0 @@ -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and - -import paddle - -from .parameter_server_optimizer import ParameterServerOptimizer - -__all__ = [] - - -class ParameterServerGraphOptimizer(ParameterServerOptimizer): - def __init__(self, optimizer): - super().__init__(optimizer) - self.inner_opt = optimizer - # we do not allow meta optimizer to be inner optimizer currently - self.meta_optimizers_white_list = [] - - def _can_apply(self): - if self.role_maker._is_collective: - return False - - k_steps = self.user_defined_strategy.a_sync_configs["k_steps"] - if k_steps < 0: - return False - - if self.role_maker._is_server(): - return False - - if self.role_maker._is_heter_parameter_server_mode: - return False - - return True - - def _disable_strategy(self, dist_strategy): - return - - def _enable_strategy(self, dist_strategy, context): - # only open up the async mode for auto-parallel - return - - def _is_graph_out(self): - return True - - def _try_to_compile(self, main_program, loss): - dist_strategy = self._get_distributed_strategy() - - build_strategy = dist_strategy.get_build_strategy() - exec_strategy = dist_strategy.get_execute_strategy() - - self._compiled_program = paddle.static.CompiledProgram(main_program) - - self._compiled_program.with_data_parallel( - loss_name=loss.name, - build_strategy=build_strategy, - exec_strategy=exec_strategy, - share_vars_from=None, - ) - - return self._compiled_program - - def minimize( - self, loss, startup_program=None, parameter_list=None, no_grad_set=None - ): - program = loss.block.program - compiled_program = self._try_to_compile(program, loss) - program._graph = compiled_program - # just return self.optimizer_ops and self.param_grads - return None, None