diff --git a/python/paddle/trainer_config_helpers/networks.py b/python/paddle/trainer_config_helpers/networks.py index 1032569b2bfa500996f5d85e382e849fd04e97d2..95f3a3f8f3c0664bac7b194a250ce1273417ea41 100755 --- a/python/paddle/trainer_config_helpers/networks.py +++ b/python/paddle/trainer_config_helpers/networks.py @@ -345,21 +345,34 @@ def img_conv_group(input, """ Image Convolution Group, Used for vgg net. - TODO(yuyang18): Complete docs - - :param conv_batchnorm_drop_rate: - :param input: - :param conv_num_filter: - :param pool_size: - :param num_channels: - :param conv_padding: - :param conv_filter_size: - :param conv_act: - :param conv_with_batchnorm: - :param pool_stride: - :param pool_type: - :param param_attr: - :return: + :param conv_batchnorm_drop_rate: if conv_with_batchnorm[i] is true, + conv_batchnorm_drop_rate[i] represents the drop rate of each batch norm. + :type conv_batchnorm_drop_rate: list + :param input: layer's input. + :type input: LayerOutput + :param conv_num_filter: output channels num. + :type conv_num_filter: int + :param pool_size: pooling filter size. + :type pool_size: int + :param num_channels: input channels num. + :type num_channels: int + :param conv_padding: convolution padding size. + :type conv_padding: int + :param conv_filter_size: convolution filter size. + :type conv_filter_size: int + :param conv_act: activation funciton after convolution. + :type conv_act: BaseActivation + :param conv_with_batchnorm: conv_with_batchnorm[i] represents + if there is a batch normalization after each convolution. + :type conv_with_batchnorm: list + :param pool_stride: pooling stride size. + :type pool_stride: int + :param pool_type: pooling type. + :type pool_type: BasePoolingType + :param param_attr: see img_conv_layer for details. + :type param_attr: ParameterAttribute + :return: Layer's output + :type: LayerOutput """ tmp = input @@ -399,7 +412,7 @@ def img_conv_group(input, padding=conv_padding[i], filter_size=conv_filter_size[i], num_filters=conv_num_filter[i], - param_attr = param_attr, + param_attr=param_attr, **extra_kwargs) # logger.debug("tmp.num_filters = %d" % tmp.num_filters) @@ -1392,7 +1405,7 @@ def inputs(layers, *args): if len(args) != 0: layers.extend(args) - Inputs(*[l.name for l in layers]) + Inputs(* [l.name for l in layers]) def outputs(layers, *args): @@ -1442,7 +1455,7 @@ def outputs(layers, *args): assert len(layers) > 0 if HasInputsSet(): # input already set - Outputs(*[l.name for l in layers]) + Outputs(* [l.name for l in layers]) return # just return outputs. if len(layers) != 1: