clean-up some deprecation

docs/conf.py

@@ -353,7 +353,6 @@ def process_signature(app, what, name, obj, options, signature,
 
 def autodoc_skip_member(app, what, name, obj, skip, options):
     if name in [
-        'DistributedReplicatedTrainer',
         'SingleCostFeedfreeTrainer',
         'SimpleFeedfreeTrainer',
         'FeedfreeTrainerBase',
@@ -369,7 +368,6 @@ def autodoc_skip_member(app, what, name, obj, skip, options):
         'GaussianDeform',
         'dump_chkpt_vars',
         'VisualQA',
-        'ParamRestore',
         'huber_loss'
         ]:
         return True

tensorpack/tfutils/sessinit.py

@@ -8,14 +8,12 @@ import tensorflow as tf
 import six
 
 from ..utils import logger
-from ..utils.develop import deprecated
 from .common import get_op_tensor_name
 from .varmanip import (SessionUpdate, get_savename_from_varname,
                        is_training_name, get_checkpoint_path)
 
 __all__ = ['SessionInit', 'ChainInit',
-           'SaverRestore', 'SaverRestoreRelaxed',
-           'ParamRestore', 'DictRestore',
+           'SaverRestore', 'SaverRestoreRelaxed', 'DictRestore',
            'JustCurrentSession', 'get_model_loader', 'TryResumeTraining']
 
 
@@ -191,24 +189,24 @@ class DictRestore(SessionInit):
     Restore variables from a dictionary.
     """
 
-    def __init__(self, param_dict):
+    def __init__(self, variable_dict):
         """
         Args:
-            param_dict (dict): a dict of {name: value}
+            variable_dict (dict): a dict of {name: value}
         """
-        assert isinstance(param_dict, dict), type(param_dict)
+        assert isinstance(variable_dict, dict), type(variable_dict)
         # use varname (with :0) for consistency
-        self.prms = {get_op_tensor_name(n)[1]: v for n, v in six.iteritems(param_dict)}
+        self._prms = {get_op_tensor_name(n)[1]: v for n, v in six.iteritems(variable_dict)}
 
     def _run_init(self, sess):
         variables = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES)
 
         variable_names = set([k.name for k in variables])
-        param_names = set(six.iterkeys(self.prms))
+        param_names = set(six.iterkeys(self._prms))
 
         intersect = variable_names & param_names
 
-        logger.info("Params to restore: {}".format(', '.join(map(str, intersect))))
+        logger.info("Variables to restore from dict: {}".format(', '.join(map(str, intersect))))
 
         mismatch = MismatchLogger('graph', 'dict')
         for k in sorted(variable_names - param_names):
@@ -222,12 +220,7 @@ class DictRestore(SessionInit):
 
         upd = SessionUpdate(sess, [v for v in variables if v.name in intersect])
         logger.info("Restoring from dict ...")
-        upd.update({name: value for name, value in six.iteritems(self.prms) if name in intersect})
-
-
-@deprecated("Use `DictRestore` instead!", "2017-09-01")
-def ParamRestore(d):
-    return DictRestore(d)
+        upd.update({name: value for name, value in six.iteritems(self._prms) if name in intersect})
 
 
 class ChainInit(SessionInit):

tensorpack/train/distributed.py

@@ -16,7 +16,7 @@ from .multigpu import MultiGPUTrainerBase
 from .utility import override_to_local_variable
 
 
-__all__ = ['DistributedReplicatedTrainer', 'DistributedTrainerReplicated']
+__all__ = ['DistributedTrainerReplicated']
 
 
 class DistributedTrainerReplicated(MultiGPUTrainerBase):
@@ -336,8 +336,3 @@ class DistributedTrainerReplicated(MultiGPUTrainerBase):
     @property
     def vs_name_for_predictor(self):
         return "tower0"
-
-
-def DistributedReplicatedTrainer(*args, **kwargs):
-    logger.warn("DistributedReplicatedTrainer was renamed to DistributedTrainerReplicated!")
-    return DistributedTrainerReplicated(*args, **kwargs)