# 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 # limitations under the License. import unittest import paddle import os class TestStrategyConfig(unittest.TestCase): def test_amp(self): strategy = paddle.fleet.DistributedStrategy() strategy.amp = True self.assertEqual(strategy.amp, True) strategy.amp = False self.assertEqual(strategy.amp, False) strategy.amp = "True" self.assertEqual(strategy.amp, False) def test_amp_loss_scaling(self): strategy = paddle.fleet.DistributedStrategy() strategy.amp_loss_scaling = 32768 self.assertEqual(strategy.amp_loss_scaling, 32768) strategy.amp_loss_scaling = 0.1 self.assertEqual(strategy.amp_loss_scaling, 32768) def test_recompute(self): strategy = paddle.fleet.DistributedStrategy() strategy.recompute = True self.assertEqual(strategy.recompute, True) strategy.recompute = False self.assertEqual(strategy.recompute, False) strategy.recompute = "True" self.assertEqual(strategy.recompute, False) def test_recompute_checkpoints(self): strategy = paddle.fleet.DistributedStrategy() strategy.recompute_checkpoints = ["var1", "var2", "var3"] self.assertEqual(len(strategy.recompute_checkpoints), 3) import paddle.fluid as fluid program = fluid.Program() cur_block = program.current_block() var1 = cur_block.create_var(name="var4", shape=[1, 1], dtype="int32") var2 = cur_block.create_var(name="var5", shape=[1, 1], dtype="int32") var3 = cur_block.create_var(name="var6", shape=[1, 1], dtype="int32") strategy.recompute_checkpoints = [var1, var2, var3] self.assertEqual(len(strategy.recompute_checkpoints), 3) self.assertEqual(strategy.recompute_checkpoints[0], "var4") strategy.recompute_checkpoints = [var1, "var2", var3] self.assertEqual(strategy.recompute_checkpoints[1], "var5") def test_pipeline(self): strategy = paddle.fleet.DistributedStrategy() strategy.pipeline = True self.assertEqual(strategy.pipeline, True) strategy.pipeline = False self.assertEqual(strategy.pipeline, False) strategy.pipeline = "True" self.assertEqual(strategy.pipeline, False) def test_pipeline_micro_batch(self): strategy = paddle.fleet.DistributedStrategy() strategy.pipeline_micro_batch = 1 self.assertEqual(strategy.pipeline_micro_batch, 1) strategy.pipeline_micro_batch = 0.1 self.assertEqual(strategy.pipeline_micro_batch, 1) def test_localsgd(self): strategy = paddle.fleet.DistributedStrategy() strategy.localsgd = True self.assertEqual(strategy.localsgd, True) strategy.localsgd = False self.assertEqual(strategy.localsgd, False) strategy.localsgd = "True" self.assertEqual(strategy.localsgd, False) def test_localsgd_k_step(self): strategy = paddle.fleet.DistributedStrategy() strategy.localsgd_k_step = 1 self.assertEqual(strategy.localsgd_k_step, 1) strategy.localsgd_k_step = "2" self.assertEqual(strategy.localsgd_k_step, 1) def test_dgc(self): strategy = paddle.fleet.DistributedStrategy() strategy.dgc = True self.assertEqual(strategy.dgc, True) strategy.dgc = False self.assertEqual(strategy.dgc, False) strategy.dgc = "True" self.assertEqual(strategy.dgc, False) def test_hierachical_allreduce(self): strategy = paddle.fleet.DistributedStrategy() strategy.hierachical_allreduce = True self.assertEqual(strategy.hierachical_allreduce, True) strategy.hierachical_allreduce = False self.assertEqual(strategy.hierachical_allreduce, False) strategy.hierachical_allreduce = "True" self.assertEqual(strategy.hierachical_allreduce, False) def test_nccl_comm_num(self): strategy = paddle.fleet.DistributedStrategy() strategy.nccl_comm_num = 1 self.assertEqual(strategy.nccl_comm_num, 1) strategy.nccl_comm_num = "2" self.assertEqual(strategy.nccl_comm_num, 1) def test_gradient_merge(self): strategy = paddle.fleet.DistributedStrategy() strategy.gradient_merge = True self.assertEqual(strategy.gradient_merge, True) strategy.gradient_merge = False self.assertEqual(strategy.gradient_merge, False) strategy.gradient_merge = "True" self.assertEqual(strategy.gradient_merge, False) def test_gradient_merge_k_step(self): strategy = paddle.fleet.DistributedStrategy() strategy.gradient_merge_k_step = 1 self.assertEqual(strategy.gradient_merge_k_step, 1) strategy.gradient_merge_k_step = "2" self.assertEqual(strategy.gradient_merge_k_step, 1) def test_sequential_execution(self): strategy = paddle.fleet.DistributedStrategy() strategy.sequential_execution = True self.assertEqual(strategy.sequential_execution, True) strategy.sequential_execution = False self.assertEqual(strategy.sequential_execution, False) strategy.sequential_execution = "True" self.assertEqual(strategy.sequential_execution, False) def test_lars(self): strategy = paddle.fleet.DistributedStrategy() strategy.lars = True self.assertEqual(strategy.lars, True) strategy.lars = False self.assertEqual(strategy.lars, False) strategy.lars = "True" self.assertEqual(strategy.lars, False) def test_lamb(self): strategy = paddle.fleet.DistributedStrategy() strategy.lamb = True self.assertEqual(strategy.lamb, True) strategy.lamb = False self.assertEqual(strategy.lamb, False) strategy.lamb = "True" self.assertEqual(strategy.lamb, False) def test_fuse_elewise_add_act_ops(self): strategy = paddle.fleet.DistributedStrategy() strategy.fuse_elewise_add_act_ops = True self.assertEqual(strategy.fuse_elewise_add_act_ops, True) strategy.fuse_elewise_add_act_ops = False self.assertEqual(strategy.fuse_elewise_add_act_ops, False) strategy.fuse_elewise_add_act_ops = "True" self.assertEqual(strategy.fuse_elewise_add_act_ops, False) def test_fuse_bn_act_ops(self): strategy = paddle.fleet.DistributedStrategy() strategy.fuse_bn_act_ops = True self.assertEqual(strategy.fuse_bn_act_ops, True) strategy.fuse_bn_act_ops = False self.assertEqual(strategy.fuse_bn_act_ops, False) strategy.fuse_bn_act_ops = "True" self.assertEqual(strategy.fuse_bn_act_ops, False) def test_enable_auto_fusion(self): strategy = paddle.fleet.DistributedStrategy() strategy.enable_auto_fusion = True self.assertEqual(strategy.enable_auto_fusion, True) strategy.enable_auto_fusion = False self.assertEqual(strategy.enable_auto_fusion, False) strategy.enable_auto_fusion = "True" self.assertEqual(strategy.enable_auto_fusion, False) def test_fuse_relu_depthwise_conv(self): strategy = paddle.fleet.DistributedStrategy() strategy.fuse_relu_depthwise_conv = True self.assertEqual(strategy.fuse_relu_depthwise_conv, True) strategy.fuse_relu_depthwise_conv = False self.assertEqual(strategy.fuse_relu_depthwise_conv, False) strategy.fuse_relu_depthwise_conv = "True" self.assertEqual(strategy.fuse_relu_depthwise_conv, False) def test_enable_inplace(self): strategy = paddle.fleet.DistributedStrategy() strategy.enable_inplace = True self.assertEqual(strategy.enable_inplace, True) strategy.enable_inplace = False self.assertEqual(strategy.enable_inplace, False) strategy.enable_inplace = "True" self.assertEqual(strategy.enable_inplace, False) def test_fuse_all_reduce_ops(self): strategy = paddle.fleet.DistributedStrategy() strategy.fuse_all_reduce_ops = True self.assertEqual(strategy.fuse_all_reduce_ops, True) strategy.fuse_all_reduce_ops = False self.assertEqual(strategy.fuse_all_reduce_ops, False) strategy.fuse_all_reduce_ops = "True" self.assertEqual(strategy.fuse_all_reduce_ops, False) def test_num_iteration_per_drop_scope(self): strategy = paddle.fleet.DistributedStrategy() strategy.num_iteration_per_drop_scope = 1 self.assertEqual(strategy.num_iteration_per_drop_scope, 1) strategy.num_iteration_per_drop_scope = 0.1 self.assertEqual(strategy.num_iteration_per_drop_scope, 1) def test_sync_batch_norm(self): strategy = paddle.fleet.DistributedStrategy() strategy.sync_batch_norm = True self.assertEqual(strategy.sync_batch_norm, True) strategy.sync_batch_norm = False self.assertEqual(strategy.sync_batch_norm, False) strategy.sync_batch_norm = "True" self.assertEqual(strategy.sync_batch_norm, False) def test_fuse_all_optimizer_ops(self): strategy = paddle.fleet.DistributedStrategy() strategy.fuse_all_optimizer_ops = True self.assertEqual(strategy.fuse_all_optimizer_ops, True) strategy.fuse_all_optimizer_ops = False self.assertEqual(strategy.fuse_all_optimizer_ops, False) strategy.fuse_all_optimizer_ops = "True" self.assertEqual(strategy.fuse_all_optimizer_ops, False) def test_sync(self): strategy = paddle.fleet.DistributedStrategy() strategy.sync = True self.assertEqual(strategy.sync, True) strategy.sync = False self.assertEqual(strategy.sync, False) strategy.sync = "True" self.assertEqual(strategy.sync, False) def test_async_k_step(self): strategy = paddle.fleet.DistributedStrategy() strategy.async_k_step = 10000 self.assertEqual(strategy.async_k_step, 10000) strategy.async_k_step = 0.1 self.assertEqual(strategy.async_k_step, 10000) def test_send_queue_size(self): strategy = paddle.fleet.DistributedStrategy() strategy.send_queue_size = 10000 self.assertEqual(strategy.send_queue_size, 10000) strategy.send_queue_size = 0.1 self.assertEqual(strategy.send_queue_size, 10000) def test_independent_recv_thread(self): strategy = paddle.fleet.DistributedStrategy() strategy.independent_recv_thread = True self.assertEqual(strategy.independent_recv_thread, True) strategy.independent_recv_thread = False self.assertEqual(strategy.independent_recv_thread, False) strategy.independent_recv_thread = "True" self.assertEqual(strategy.independent_recv_thread, False) def test_min_send_grad_num_before_recv(self): strategy = paddle.fleet.DistributedStrategy() strategy.min_send_grad_num_before_recv = 10000 self.assertEqual(strategy.min_send_grad_num_before_recv, 10000) strategy.min_send_grad_num_before_recv = 0.1 self.assertEqual(strategy.min_send_grad_num_before_recv, 10000) def test_thread_pool_size(self): strategy = paddle.fleet.DistributedStrategy() strategy.thread_pool_size = 10000 self.assertEqual(strategy.thread_pool_size, 10000) strategy.thread_pool_size = 0.1 self.assertEqual(strategy.thread_pool_size, 10000) def test_send_wait_times(self): strategy = paddle.fleet.DistributedStrategy() strategy.send_wait_times = 10000 self.assertEqual(strategy.send_wait_times, 10000) strategy.send_wait_times = 0.1 self.assertEqual(strategy.send_wait_times, 10000) def test_runtime_split_send_recv(self): strategy = paddle.fleet.DistributedStrategy() strategy.runtime_split_send_recv = True self.assertEqual(strategy.runtime_split_send_recv, True) strategy.runtime_split_send_recv = False self.assertEqual(strategy.runtime_split_send_recv, False) strategy.runtime_split_send_recv = "True" self.assertEqual(strategy.runtime_split_send_recv, False) def use_thread_barrier(self): strategy = paddle.fleet.DistributedStrategy() strategy.thread_barrier = True self.assertEqual(strategy.thread_barrier, True) strategy.thread_barrier = False self.assertEqual(strategy.thread_barrier, False) strategy.thread_barrier = "True" self.assertEqual(strategy.thread_barrier, False) def test_enable_backward_optimizer_op_deps(self): strategy = paddle.fleet.DistributedStrategy() strategy.enable_backward_optimizer_op_deps = True self.assertEqual(strategy.enable_backward_optimizer_op_deps, True) strategy.enable_backward_optimizer_op_deps = False self.assertEqual(strategy.enable_backward_optimizer_op_deps, False) strategy.enable_backward_optimizer_op_deps = "True" self.assertEqual(strategy.enable_backward_optimizer_op_deps, False) def test_elastic(self): strategy = paddle.fleet.DistributedStrategy() strategy.elastic = True self.assertEqual(strategy.elastic, True) strategy.elastic = False self.assertEqual(strategy.elastic, False) strategy.elastic = "True" self.assertEqual(strategy.elastic, False) def test_auto(self): strategy = paddle.fleet.DistributedStrategy() strategy.auto = True self.assertEqual(strategy.auto, True) strategy.auto = False self.assertEqual(strategy.auto, False) strategy.auto = "True" self.assertEqual(strategy.auto, False) if __name__ == '__main__': unittest.main()