init

python/paddle/trainer_config_helpers/layers.py

@@ -2542,14 +2542,14 @@ def img_conv_layer(input,
     what-are-deconvolutional-layers/>`_ .
     The num_channel means input image's channel number. It may be 1 or 3 when
     input is raw pixels of image(mono or RGB), or it may be the previous layer's
-    num_filters * num_group.
+    num_filters.
 
     There are several groups of filters in PaddlePaddle implementation.
     Each group will process some channels of the input. For example, if
     num_channel = 256, group = 4, num_filter=32, the PaddlePaddle will create
-    32*4 = 128 filters to process the input. The channels will be split into 4
-    pieces. First 256/4 = 64 channels will be processed by first 32 filters. The
-    rest channels will be processed by the rest groups of filters.
+    32 filters to process the input. The input channels will be split into 4
+    pieces. First 256/4 = 64 channels will be processed by first 32/4 = 8 filters.
+    The rest channels will be processed by the rest groups of filters.
 
     The example usage is:
 
@@ -2575,7 +2575,8 @@ def img_conv_layer(input,
     :param filter_size_y: The dimension of the filter kernel on the y axis. If the parameter
                           is not set, it will be set automatically according to filter_size.
     :type filter_size_y: int
-    :param num_filters: Each filter group's number of filter
+    :param num_filters: The number of filters. It is as same as the output image channel.
+    :type num_filters: int
     :param act: Activation type. ReluActivation is the default activation.
     :type act: BaseActivation
     :param groups: The group number. 1 is the default group number.
@@ -7177,7 +7178,7 @@ def img_conv3d_layer(input,
     :param filter_size: The dimensions of the filter kernel along three axises. If the parameter
                         is set to one integer, the three dimensions will be same.
     :type filter_size: int | tuple | list
-    :param num_filters: The number of filters in each group.
+    :param num_filters: The number of filters. It is as same as the output image channel.
     :type num_filters: int
     :param act: Activation type. ReluActivation is the default activation.
     :type act: BaseActivation