diff --git a/python/paddle/fluid/parallel_executor.py b/python/paddle/fluid/parallel_executor.py index 44af29d3390e35129d0ee65b31eacad6b28a9d60..57d272cbfb948840679e80e8db40379c57603113 100644 --- a/python/paddle/fluid/parallel_executor.py +++ b/python/paddle/fluid/parallel_executor.py @@ -74,28 +74,7 @@ class ParallelExecutor(object): build_strategy=None, num_trainers=1, trainer_id=0, - scope=None, - **kwargs): - if len(kwargs) != 0: - err_msg = "" - for key in kwargs: - if key in dir(ExecutionStrategy): - err_msg += \ - "Setting {0} by constructor is deprecated. Use " \ - "strategy=ExecutionStrategy(); strategy.{0}=xxx; " \ - "pe=ParallelExecutor(exec_strategy=strategy) " \ - "instead.\n ".format(key) - elif key in dir(BuildStrategy): - err_msg += \ - "Setting {0} by constructor is deprecated. Use " \ - "strategy=BuildStrategy(); See help(" \ - "paddle.fluid.ParallelExecutor.BuildStrategy) \n".format( - key) - else: - err_msg += "Setting {0} by constructor is deprecated. Use strategy.\n".format( - key) - raise ValueError(err_msg) - + scope=None): self._places = [] self._act_places = [] if use_cuda: diff --git a/python/paddle/fluid/param_attr.py b/python/paddle/fluid/param_attr.py index f0be794327f51cbbc4202b8b7b401b712b6d66a3..a51607bfdb1dde3d25f490770cc2ba368ceb27ff 100644 --- a/python/paddle/fluid/param_attr.py +++ b/python/paddle/fluid/param_attr.py @@ -185,7 +185,17 @@ class WeightNormParamAttr(ParamAttr): Args: dim(list): The parameter's name. Default None. - kwargs: Any field in ParamAttr. Default None. + name(str): The parameter's name. Default None. + initializer(Initializer): The method to initial this parameter. Default None. + learning_rate(float): The parameter's learning rate. The learning rate when + optimize is :math:`global\_lr * parameter\_lr * scheduler\_factor`. + Default 1.0. + regularizer(WeightDecayRegularizer): Regularization factor. Default None. + trainable(bool): Whether this parameter is trainable. Default True. + gradient_clip(BaseGradientClipAttr): The method to clip this parameter's + gradient. Default None. + do_model_average(bool): Whether this parameter should do model average. + Default False. Examples: .. code-block:: python @@ -204,6 +214,21 @@ class WeightNormParamAttr(ParamAttr): # these paramters for inference. params_with_weight_norm = [] - def __init__(self, dim=None, **kwargs): - super(WeightNormParamAttr, self).__init__(**kwargs) + def __init__(self, + dim=None, + name=None, + initializer=None, + learning_rate=1.0, + regularizer=None, + trainable=True, + gradient_clip=None, + do_model_average=False): + super(WeightNormParamAttr, self).__init__( + name=name, + initializer=initializer, + learning_rate=learning_rate, + regularizer=regularizer, + trainable=trainable, + gradient_clip=gradient_clip, + do_model_average=do_model_average) self.dim = dim