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65 lines
2.2 KiB
65 lines
2.2 KiB
# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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from paddle import fluid
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from paddle.fluid import compiler
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from .async_optimizer import AsyncMetaOptimizer
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class AsyncGraphExecutionOptimizer(AsyncMetaOptimizer):
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def __init__(self, optimizer):
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super(AsyncGraphExecutionOptimizer, self).__init__(optimizer)
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self.inner_opt = optimizer
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# we do not allow meta optimizer to be inner optimizer currently
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self.meta_optimizers_white_list = []
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def _can_apply(self):
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k_steps = self.user_defined_strategy.a_sync_configs["k_steps"]
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if k_steps < 0:
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return False
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if self.role_maker.is_server():
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return False
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return True
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def _is_graph_out(self):
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return True
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def _try_to_compile(self, main_program, loss):
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dist_strategy = self._get_distributed_strategy()
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build_strategy = dist_strategy.get_build_strategy()
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exec_strategy = dist_strategy.get_execute_strategy()
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self._compiled_program = compiler.CompiledProgram(main_program)
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self._compiled_program.with_data_parallel(
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loss_name=loss.name,
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build_strategy=build_strategy,
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exec_strategy=exec_strategy,
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share_vars_from=None)
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return self._compiled_program
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def minimize(self,
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loss,
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startup_program=None,
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parameter_list=None,
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no_grad_set=None):
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program = loss.block.program
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compiled_program = self._try_to_compile(program, loss)
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program._graph = compiled_program
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# just return self.optimizer_ops and self.param_grads
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return None, None
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