Internal change

PiperOrigin-RevId: 300426073

official/modeling/hyperparams/base_config.py

@@ -24,7 +24,6 @@ import copy
 import functools
 from typing import Any, List, Mapping, Optional, Type
 
-from absl import logging
 import dataclasses
 import tensorflow as tf
 import yaml
@@ -74,8 +73,8 @@ class Config(params_dict.ParamsDict):
     """Returns v with dicts converted to Configs, recursively."""
     if not issubclass(subconfig_type, params_dict.ParamsDict):
       raise TypeError(
-          'Subconfig_type should be subclass of ParamsDict, found %r',
-          subconfig_type)
+          'Subconfig_type should be subclass of ParamsDict, found {!r}'.format(
+              subconfig_type))
     if isinstance(v, cls.IMMUTABLE_TYPES):
       return v
     elif isinstance(v, cls.SEQUENCE_TYPES):
@@ -95,7 +94,7 @@ class Config(params_dict.ParamsDict):
     elif isinstance(v, dict):
       return subconfig_type(v)
     else:
-      raise TypeError('Unknown type: %r' % type(v))
+      raise TypeError('Unknown type: {!r}'.format(type(v)))
 
   @classmethod
   def _export_config(cls, v):
@@ -162,7 +161,9 @@ class Config(params_dict.ParamsDict):
     """
     subconfig_type = self._get_subconfig_type(k)
     if isinstance(v, dict):
-      if k not in self.__dict__:
+      if k not in self.__dict__ or not self.__dict__[k]:
+        # If the key not exist or the value is None, a new Config-family object
+        # sould be created for the key.
         self.__dict__[k] = subconfig_type(v)
       else:
         self.__dict__[k].override(v)
@@ -193,15 +194,16 @@ class Config(params_dict.ParamsDict):
                        'Can not be overridden.'.format(k))
       if k not in self.__dict__:
         if is_strict:
-          raise KeyError('The key {!r} does not exist. '
+          raise KeyError('The key {!r} does not exist in {!r}. '
                          'To extend the existing keys, use '
-                         '`override` with `is_strict` = False.'.format(k))
+                         '`override` with `is_strict` = False.'.format(
+                             k, type(self)))
         else:
           self._set(k, v)
       else:
-        if isinstance(v, dict):
+        if isinstance(v, dict) and self.__dict__[k]:
           self.__dict__[k]._override(v, is_strict)  # pylint: disable=protected-access
-        elif isinstance(v, params_dict.ParamsDict):
+        elif isinstance(v, params_dict.ParamsDict) and self.__dict__[k]:
           self.__dict__[k]._override(v.as_dict(), is_strict)  # pylint: disable=protected-access
         else:
           self._set(k, v)
@@ -268,6 +270,8 @@ class RuntimeConfig(Config):
       multi-worker models with DistributionStrategy.
     task_index: If multi-worker training, the task index of this worker.
     all_reduce_alg: Defines the algorithm for performing all-reduce.
+    num_packs: Sets `num_packs` in the cross device ops used in
+      MirroredStrategy.  For details, see tf.distribute.NcclAllReduce.
   """
   distribution_strategy: str = 'mirrored'
   enable_eager: bool = False
@@ -281,6 +285,7 @@ class RuntimeConfig(Config):
   worker_hosts: Optional[str] = None
   task_index: int = -1
   all_reduce_alg: Optional[str] = None
+  num_packs: int = 1
 
 
 @dataclasses.dataclass
@@ -311,4 +316,3 @@ class CallbacksConfig(Config):
   """
   enable_checkpoint_and_export: bool = True
   enable_tensorboard: bool = True
-