update dist api (#2444)

ppdet/engine/callbacks.py

@@ -23,7 +23,7 @@ import six
 import numpy as np
 
 import paddle
-from paddle.distributed import ParallelEnv
+import paddle.distributed as dist
 
 from ppdet.utils.checkpoint import save_model
 from ppdet.optimizer import ModelEMA
@@ -81,7 +81,7 @@ class LogPrinter(Callback):
         super(LogPrinter, self).__init__(model)
 
     def on_step_end(self, status):
-        if ParallelEnv().nranks < 2 or ParallelEnv().local_rank == 0:
+        if dist.get_world_size() < 2 or dist.get_rank() == 0:
             mode = status['mode']
             if mode == 'train':
                 epoch_id = status['epoch_id']
@@ -129,7 +129,7 @@ class LogPrinter(Callback):
                     logger.info("Eval iter: {}".format(step_id))
 
     def on_epoch_end(self, status):
-        if ParallelEnv().nranks < 2 or ParallelEnv().local_rank == 0:
+        if dist.get_world_size() < 2 or dist.get_rank() == 0:
             mode = status['mode']
             if mode == 'eval':
                 sample_num = status['sample_num']
@@ -160,7 +160,7 @@ class Checkpointer(Callback):
         epoch_id = status['epoch_id']
         weight = None
         save_name = None
-        if ParallelEnv().nranks < 2 or ParallelEnv().local_rank == 0:
+        if dist.get_world_size() < 2 or dist.get_rank() == 0:
             if mode == 'train':
                 end_epoch = self.model.cfg.epoch
                 if epoch_id % self.model.cfg.snapshot_epoch == 0 or epoch_id == end_epoch - 1:
@@ -224,7 +224,7 @@ class VisualDLWriter(Callback):
 
     def on_step_end(self, status):
         mode = status['mode']
-        if ParallelEnv().nranks < 2 or ParallelEnv().local_rank == 0:
+        if dist.get_world_size() < 2 or dist.get_rank() == 0:
             if mode == 'train':
                 training_staus = status['training_staus']
                 for loss_name, loss_value in training_staus.get().items():
@@ -248,7 +248,7 @@ class VisualDLWriter(Callback):
 
     def on_epoch_end(self, status):
         mode = status['mode']
-        if ParallelEnv().nranks < 2 or ParallelEnv().local_rank == 0:
+        if dist.get_world_size() < 2 or dist.get_rank() == 0:
             if mode == 'eval':
                 for metric in self.model._metrics:
                     for key, map_value in metric.get_results().items():

ppdet/engine/env.py

@@ -21,7 +21,7 @@ import random
 import numpy as np
 
 import paddle
-from paddle.distributed import ParallelEnv, fleet
+from paddle.distributed import fleet
 
 __all__ = ['init_parallel_env', 'set_random_seed', 'init_fleet_env']
 

ppdet/engine/trainer.py

@@ -24,7 +24,8 @@ import numpy as np
 from PIL import Image
 
 import paddle
-from paddle.distributed import ParallelEnv, fleet
+import paddle.distributed as dist
+from paddle.distributed import fleet
 from paddle import amp
 from paddle.static import InputSpec
 
@@ -83,8 +84,8 @@ class Trainer(object):
             self.optimizer = create('OptimizerBuilder')(self.lr,
                                                         self.model.parameters())
 
-        self._nranks = ParallelEnv().nranks
-        self._local_rank = ParallelEnv().local_rank
+        self._nranks = dist.get_world_size()
+        self._local_rank = dist.get_rank()
 
         self.status = {}
 

ppdet/utils/logger.py

@@ -17,7 +17,7 @@ import logging
 import os
 import sys
 
-from paddle.distributed import ParallelEnv
+import paddle.distributed as dist
 
 __all__ = ['setup_logger']
 
@@ -47,7 +47,7 @@ def setup_logger(name="ppdet", output=None):
         "[%(asctime)s] %(name)s %(levelname)s: %(message)s",
         datefmt="%m/%d %H:%M:%S")
     # stdout logging: master only
-    local_rank = ParallelEnv().local_rank
+    local_rank = dist.get_rank()
     if local_rank == 0:
         ch = logging.StreamHandler(stream=sys.stdout)
         ch.setLevel(logging.DEBUG)

tools/eval.py

@@ -27,7 +27,6 @@ import warnings
 warnings.filterwarnings('ignore')
 
 import paddle
-from paddle.distributed import ParallelEnv
 
 from ppdet.core.workspace import load_config, merge_config
 from ppdet.utils.check import check_gpu, check_version, check_config
@@ -115,8 +114,7 @@ def main():
     check_gpu(cfg.use_gpu)
     check_version()
 
-    place = 'gpu:{}'.format(ParallelEnv().dev_id) if cfg.use_gpu else 'cpu'
-    place = paddle.set_device(place)
+    place = paddle.set_device('gpu' if cfg.use_gpu else 'cpu')
 
     run(FLAGS, cfg)
 

tools/infer.py

@@ -27,7 +27,6 @@ warnings.filterwarnings('ignore')
 import glob
 
 import paddle
-from paddle.distributed import ParallelEnv
 from ppdet.core.workspace import load_config, merge_config
 from ppdet.engine import Trainer
 from ppdet.utils.check import check_gpu, check_version, check_config
@@ -140,8 +139,7 @@ def main():
     check_gpu(cfg.use_gpu)
     check_version()
 
-    place = 'gpu:{}'.format(ParallelEnv().dev_id) if cfg.use_gpu else 'cpu'
-    place = paddle.set_device(place)
+    place = paddle.set_device('gpu' if cfg.use_gpu else 'cpu')
     run(FLAGS, cfg)
 
 

tools/train.py

@@ -29,7 +29,6 @@ import random
 import numpy as np
 
 import paddle
-from paddle.distributed import ParallelEnv
 
 from ppdet.core.workspace import load_config, merge_config, create
 from ppdet.utils.checkpoint import load_weight, load_pretrain_weight
@@ -122,8 +121,7 @@ def main():
     check.check_gpu(cfg.use_gpu)
     check.check_version()
 
-    place = 'gpu:{}'.format(ParallelEnv().dev_id) if cfg.use_gpu else 'cpu'
-    place = paddle.set_device(place)
+    place = paddle.set_device('gpu' if cfg.use_gpu else 'cpu')
 
     run(FLAGS, cfg)