Merge pull request #701 from PaddlePaddle/ckpt

fix load param

deepspeech/utils/checkpoint.py

@@ -16,8 +16,8 @@ import json
 import os
 import re
 from pathlib import Path
-from typing import Union
 from typing import Text
+from typing import Union
 
 import paddle
 from paddle import distributed as dist
@@ -51,7 +51,7 @@ class Checkpoint():
         Args:
             checkpoint_dir (str): the directory where checkpoint is saved.
             tag_or_iteration (int or str): the latest iteration(step or epoch) number or tag.
-            model (Layer):  model to be checkpointed. 
+            model (Layer):  model to be checkpointed.
             optimizer (Optimizer, optional): optimizer to be checkpointed.
             infos (dict or None)):  any info you want to save.
             metric_type (str, optional): metric type. Defaults to "val_loss".
@@ -72,22 +72,22 @@ class Checkpoint():
 
         if isinstance(tag_or_iteration, int):
             self._save_checkpoint_record(checkpoint_dir, tag_or_iteration)
-            
+
     def load_parameters(self,
-                         model,
-                         optimizer=None,
-                         checkpoint_dir=None,
-                         checkpoint_path=None,
-                         record_file="checkpoint_latest"):
-        """Load a last model checkpoint from disk. 
+                        model,
+                        optimizer=None,
+                        checkpoint_dir=None,
+                        checkpoint_path=None,
+                        record_file="checkpoint_latest"):
+        """Load a last model checkpoint from disk.
         Args:
             model (Layer): model to load parameters.
             optimizer (Optimizer, optional): optimizer to load states if needed.
                 Defaults to None.
             checkpoint_dir (str, optional): the directory where checkpoint is saved.
             checkpoint_path (str, optional): if specified, load the checkpoint
-                stored in the checkpoint_path(prefix) and the argument 'checkpoint_dir' will 
-                be ignored. Defaults to None. 
+                stored in the checkpoint_path(prefix) and the argument 'checkpoint_dir' will
+                be ignored. Defaults to None.
             record_file "checkpoint_latest" or "checkpoint_best"
         Returns:
             configs (dict): epoch or step, lr and other meta info should be saved.
@@ -134,40 +134,40 @@ class Checkpoint():
                                optimizer=None,
                                checkpoint_dir=None,
                                checkpoint_path=None):
-        """Load a last model checkpoint from disk. 
+        """Load a last model checkpoint from disk.
         Args:
             model (Layer): model to load parameters.
             optimizer (Optimizer, optional): optimizer to load states if needed.
                 Defaults to None.
             checkpoint_dir (str, optional): the directory where checkpoint is saved.
             checkpoint_path (str, optional): if specified, load the checkpoint
-                stored in the checkpoint_path(prefix) and the argument 'checkpoint_dir' will 
-                be ignored. Defaults to None. 
+                stored in the checkpoint_path(prefix) and the argument 'checkpoint_dir' will
+                be ignored. Defaults to None.
         Returns:
             configs (dict): epoch or step, lr and other meta info should be saved.
         """
-        return self._load_parameters(model, optimizer, checkpoint_dir,
-                                     checkpoint_path, "checkpoint_latest")
+        return self.load_parameters(model, optimizer, checkpoint_dir,
+                                    checkpoint_path, "checkpoint_latest")
 
     def load_best_parameters(self,
                              model,
                              optimizer=None,
                              checkpoint_dir=None,
                              checkpoint_path=None):
-        """Load a last model checkpoint from disk. 
+        """Load a last model checkpoint from disk.
         Args:
             model (Layer): model to load parameters.
             optimizer (Optimizer, optional): optimizer to load states if needed.
                 Defaults to None.
             checkpoint_dir (str, optional): the directory where checkpoint is saved.
             checkpoint_path (str, optional): if specified, load the checkpoint
-                stored in the checkpoint_path(prefix) and the argument 'checkpoint_dir' will 
-                be ignored. Defaults to None. 
+                stored in the checkpoint_path(prefix) and the argument 'checkpoint_dir' will
+                be ignored. Defaults to None.
         Returns:
             configs (dict): epoch or step, lr and other meta info should be saved.
         """
-        return self._load_parameters(model, optimizer, checkpoint_dir,
-                                     checkpoint_path, "checkpoint_best")
+        return self.load_parameters(model, optimizer, checkpoint_dir,
+                                    checkpoint_path, "checkpoint_best")
 
     def _should_save_best(self, metric: float) -> bool:
         if not self._best_full():