From 996b1de1d83e972870c4a3c6e21b5cc4b0b93014 Mon Sep 17 00:00:00 2001 From: Yi Wang Date: Fri, 3 Feb 2017 23:48:54 +0000 Subject: [PATCH] Rename DataBase into create_data_config_proto --- python/paddle/trainer/config_parser.py | 14 ++++++------ .../trainer_config_helpers/data_sources.py | 22 +++++++++---------- 2 files changed, 18 insertions(+), 18 deletions(-) diff --git a/python/paddle/trainer/config_parser.py b/python/paddle/trainer/config_parser.py index 6701eced60d..e3e2a6899e7 100644 --- a/python/paddle/trainer/config_parser.py +++ b/python/paddle/trainer/config_parser.py @@ -894,7 +894,7 @@ class MaxOut(Cfg): self.add_keys(locals()) -def DataBase(async_load_data=False, +def create_data_config_proto(async_load_data=False, constant_slots=None, data_ratio=1, is_main_data=True, @@ -924,7 +924,7 @@ def SimpleData(files=None, context_len=None, buffer_capacity=None, **xargs): - data_config = DataBase(**xargs) + data_config = create_data_config_proto(**xargs) data_config.type = 'simple' data_config.files = files data_config.feat_dim = feat_dim @@ -946,7 +946,7 @@ def PyData(files=None, constant_slots=None, load_thread_num=None, **xargs): - data_config = DataBase(**xargs) + data_config = create_data_config_proto(**xargs) data_config.type = 'py' if load_data_module in g_py_module_name_list: @@ -997,7 +997,7 @@ def ProtoData(files=None, constant_slots=None, load_thread_num=None, **xargs): - data_config = DataBase(**xargs) + data_config = create_data_config_proto(**xargs) if type is None: data_config.type = 'proto' else: @@ -1036,7 +1036,7 @@ def Data(type, buffer_capacity=None, **xargs): - data_config = DataBase(**xargs) + data_config = create_data_config_proto(**xargs) data_config.type = type data_config.files = files data_config.feat_dim = feat_dim @@ -1927,8 +1927,8 @@ class BatchNormLayer(LayerBase): image_conf = self.config.inputs[0].image_conf parse_image(self.inputs[0].image, input_layer.name, image_conf) - # Only pass the width and height of input to batch_norm layer - # when either of it is non-zero. + # Only pass the width and height of input to batch_norm layer + # when either of it is non-zero. if input_layer.width != 0 or input_layer.height != 0: self.set_cnn_layer(name, image_conf.img_size_y, image_conf.img_size, image_conf.channels, False) diff --git a/python/paddle/trainer_config_helpers/data_sources.py b/python/paddle/trainer_config_helpers/data_sources.py index 622b4fc25cc..0ea8fc77eef 100644 --- a/python/paddle/trainer_config_helpers/data_sources.py +++ b/python/paddle/trainer_config_helpers/data_sources.py @@ -58,8 +58,8 @@ def define_py_data_source(file_list, :param obj: python object name. May be a function name if using PyDataProviderWrapper. :type obj: basestring - :param args: The best practice is using dict to pass arguments into - DataProvider, and use :code:`@init_hook_wrapper` to + :param args: The best practice is using dict to pass arguments into + DataProvider, and use :code:`@init_hook_wrapper` to receive arguments. :type args: string or picklable object :param async: Load Data asynchronously or not. @@ -98,7 +98,7 @@ def define_py_data_sources(train_list, The annotation is almost the same as define_py_data_sources2, except that it can specific train_async and data_cls. - :param data_cls: + :param data_cls: :param train_list: Train list name. :type train_list: basestring :param test_list: Test list name. @@ -111,8 +111,8 @@ def define_py_data_sources(train_list, a tuple or list to this argument. :type obj: basestring or tuple or list :param args: The best practice is using dict() to pass arguments into - DataProvider, and use :code:`@init_hook_wrapper` to receive - arguments. If train and test is different, then pass a tuple + DataProvider, and use :code:`@init_hook_wrapper` to receive + arguments. If train and test is different, then pass a tuple or list to this argument. :type args: string or picklable object or list or tuple. :param train_async: Is training data load asynchronously or not. @@ -163,12 +163,12 @@ def define_py_data_sources2(train_list, test_list, module, obj, args=None): .. code-block:: python - define_py_data_sources2(train_list="train.list", - test_list="test.list", + define_py_data_sources2(train_list="train.list", + test_list="test.list", module="data_provider" # if train/test use different configurations, # obj=["process_train", "process_test"] - obj="process", + obj="process", args={"dictionary": dict_name}) The related data provider can refer to :ref:`api_pydataprovider2_sequential_model` . @@ -185,8 +185,8 @@ def define_py_data_sources2(train_list, test_list, module, obj, args=None): a tuple or list to this argument. :type obj: basestring or tuple or list :param args: The best practice is using dict() to pass arguments into - DataProvider, and use :code:`@init_hook_wrapper` to receive - arguments. If train and test is different, then pass a tuple + DataProvider, and use :code:`@init_hook_wrapper` to receive + arguments. If train and test is different, then pass a tuple or list to this argument. :type args: string or picklable object or list or tuple. :return: None @@ -195,7 +195,7 @@ def define_py_data_sources2(train_list, test_list, module, obj, args=None): def py_data2(files, load_data_module, load_data_object, load_data_args, **kwargs): - data = DataBase() + data = create_data_config_proto() data.type = 'py2' data.files = files data.load_data_module = load_data_module -- GitLab