Env->ParalleEnv

callbacks.py

@@ -16,7 +16,7 @@ import six
 import copy
 
 from progressbar import ProgressBar
-from paddle.fluid.dygraph.parallel import Env
+from paddle.fluid.dygraph.parallel import ParallelEnv
 
 
 def config_callbacks(callbacks=None,
@@ -195,7 +195,7 @@ class ProgBarLogger(Callback):
         self.steps = self.params['steps']
         self.epoch = epoch
         self.train_step = 0
-        if self.verbose and self.epochs and Env().local_rank == 0:
+        if self.verbose and self.epochs and ParallelEnv().local_rank == 0:
             print('Epoch %d/%d' % (epoch + 1, self.epochs))
         self.train_progbar = ProgressBar(num=self.steps, verbose=self.verbose)
 
@@ -213,7 +213,8 @@ class ProgBarLogger(Callback):
         logs = logs or {}
         self.train_step += 1
 
-        if self.train_step % self.log_freq == 0 and self.verbose and Env().local_rank == 0:
+        if self.train_step % self.log_freq == 0 and self.verbose and ParallelEnv(
+        ).local_rank == 0:
             # if steps is not None, last step will update in on_epoch_end
             if self.steps and self.train_step < self.steps:
                 self._updates(logs, 'train')
@@ -222,7 +223,7 @@ class ProgBarLogger(Callback):
 
     def on_epoch_end(self, epoch, logs=None):
         logs = logs or {}
-        if self.verbose and Env().local_rank == 0:
+        if self.verbose and ParallelEnv().local_rank == 0:
             self._updates(logs, 'train')
 
     def on_eval_begin(self, logs=None):
@@ -232,7 +233,7 @@ class ProgBarLogger(Callback):
         self.evaled_samples = 0
         self.eval_progbar = ProgressBar(
             num=self.eval_steps, verbose=self.verbose)
-        if Env().local_rank == 0:
+        if ParallelEnv().local_rank == 0:
             print('Eval begin...')
 
     def on_eval_batch_end(self, step, logs=None):
@@ -243,7 +244,7 @@ class ProgBarLogger(Callback):
 
     def on_eval_end(self, logs=None):
         logs = logs or {}
-        if self.verbose and Env().local_rank == 0:
+        if self.verbose and ParallelEnv().local_rank == 0:
             self._updates(logs, 'eval')
             print('Eval samples: %d' % (self.evaled_samples))
 
@@ -257,7 +258,7 @@ class ModelCheckpoint(Callback):
         self.epoch = epoch
 
     def _is_save(self):
-        return self.model and self.save_dir and Env().local_rank == 0
+        return self.model and self.save_dir and ParallelEnv().local_rank == 0
 
     def on_epoch_end(self, epoch, logs=None):
         if self._is_save() and self.epoch % self.save_freq == 0: