提交 8c582374 编写于 作者: C chengduozh

update parameter doc

test=develop
上级 16822daa
...@@ -1277,12 +1277,15 @@ def sequence_conv(input, ...@@ -1277,12 +1277,15 @@ def sequence_conv(input,
filter_size (int): the filter size (H and W). filter_size (int): the filter size (H and W).
filter_stride (int): stride of the filter. filter_stride (int): stride of the filter.
padding (bool): if True, add paddings. padding (bool): if True, add paddings.
bias_attr (ParamAttr): The parameter attribute for the bias of this layer. bias_attr (ParamAttr|bool|None): The parameter attribute for the bias of sequence_conv.
If it is set to False, no bias will be added to the output units. If it is set to False, no bias will be added to the output units.
If it is set to None, the bias is initialized zero. Default: None. If it is set to None or one attribute of ParamAttr, sequence_conv
will create ParamAttr as bias_attr. If the Initializer of the bias_attr
is not set, the bias is initialized zero. Default: None.
param_attr (ParamAttr): The parameter attribute for learnable parameters/weights param_attr (ParamAttr): The parameter attribute for learnable parameters/weights
of this layer. If it is set to None, the parameter is initialized with of sequence_conv. If it is set to None or one attribute of ParamAttr, sequence_conv
Xavier. Default: None. will create ParamAttr as param_attr. If the Initializer of the param_attr
is not set, the parameter is initialized with Xavier. Default: None.
act (str): the activation type act (str): the activation type
Returns: Returns:
...@@ -1491,14 +1494,17 @@ def conv2d(input, ...@@ -1491,14 +1494,17 @@ def conv2d(input,
convolution in Alex Krizhevsky's Deep CNN paper: when group=2, convolution in Alex Krizhevsky's Deep CNN paper: when group=2,
the first half of the filters is only connected to the first half the first half of the filters is only connected to the first half
of the input channels, while the second half of the filters is only of the input channels, while the second half of the filters is only
connected to the second half of the input channels. Default: groups=1 connected to the second half of the input channels. Default: groups=1.
param_attr (ParamAttr): The parameter attribute for learnable parameters/weights param_attr (ParamAttr): The parameter attribute for learnable parameters/weights
of this layer. If it is set to None, the parameter is initialized with of conv2d. If it is set to None or one attribute of ParamAttr, conv2d
:math:`Normal(0.0, std)`, and the :math:`std` is :math:`(\\frac{2.0 }{filter\_elem\_num})^{0.5}`. will create ParamAttr as param_attr. If the Initializer of the param_attr
Default: None. is not set, the parameter is initialized with :math:`Normal(0.0, std)`,
bias_attr (ParamAttr): The parameter attribute for the bias of this layer. and the :math:`std` is :math:`(\\frac{2.0 }{filter\_elem\_num})^{0.5}`. Default: None.
bias_attr (ParamAttr|bool|None): The parameter attribute for the bias of conv2d.
If it is set to False, no bias will be added to the output units. If it is set to False, no bias will be added to the output units.
If it is set to None, the bias is initialized zero. Default: None. If it is set to None or one attribute of ParamAttr, conv2d
will create ParamAttr as bias_attr. If the Initializer of the bias_attr
is not set, the bias is initialized zero. Default: None.
use_cudnn (bool): Use cudnn kernel or not, it is valid only when the cudnn use_cudnn (bool): Use cudnn kernel or not, it is valid only when the cudnn
library is installed. Default: True library is installed. Default: True
act (str): Activation type, if it is set to None, activation is not appended. act (str): Activation type, if it is set to None, activation is not appended.
...@@ -1550,8 +1556,8 @@ def conv2d(input, ...@@ -1550,8 +1556,8 @@ def conv2d(input,
filter_shape = [num_filters, int(num_filter_channels)] + filter_size filter_shape = [num_filters, int(num_filter_channels)] + filter_size
def _get_default_param_initializer(): def _get_default_param_initializer():
filter_num_elem = filter_size[0] * filter_size[1] * num_channels filter_elem_num = filter_size[0] * filter_size[1] * num_channels
std = (2.0 / (filter_num_elem))**0.5 std = (2.0 / filter_elem_num)**0.5
return Normal(0.0, std, 0) return Normal(0.0, std, 0)
filter_param = helper.create_parameter( filter_param = helper.create_parameter(
...@@ -1663,12 +1669,15 @@ def conv3d(input, ...@@ -1663,12 +1669,15 @@ def conv3d(input,
of the input channels, while the second half of the filters is only of the input channels, while the second half of the filters is only
connected to the second half of the input channels. Default: groups=1 connected to the second half of the input channels. Default: groups=1
param_attr (ParamAttr): The parameter attribute for learnable parameters/weights param_attr (ParamAttr): The parameter attribute for learnable parameters/weights
of this layer. If it is set to None, the parameter is initialized with of conv3d. If it is set to None or one attribute of ParamAttr, conv3d
:math:`Normal(0.0, std)`, and the :math:`std` is :math:`(\\frac{2.0 }{filter\_elem\_num})^{0.5}`. will create ParamAttr as param_attr. If it is set to None, the parameter
Default: None. is initialized with :math:`Normal(0.0, std)`, and the :math:`std` is
bias_attr (ParamAttr): The parameter attribute for the bias of this layer. :math:`(\\frac{2.0 }{filter\_elem\_num})^{0.5}`. Default: None.
bias_attr (ParamAttr|bool|None): The parameter attribute for the bias of conv3d.
If it is set to False, no bias will be added to the output units. If it is set to False, no bias will be added to the output units.
If it is set to None, the bias is initialized zero. Default: None. If it is set to None or one attribute of ParamAttr, conv3d
will create ParamAttr as bias_attr. If the Initializer of the bias_attr
is not set, the bias is initialized zero. Default: None.
use_cudnn (bool): Use cudnn kernel or not, it is valid only when the cudnn use_cudnn (bool): Use cudnn kernel or not, it is valid only when the cudnn
library is installed. Default: True library is installed. Default: True
act (str): Activation type, if it is set to None, activation is not appended. act (str): Activation type, if it is set to None, activation is not appended.
...@@ -2413,11 +2422,14 @@ def conv2d_transpose(input, ...@@ -2413,11 +2422,14 @@ def conv2d_transpose(input,
filters is only connected to the second half of the input channels. filters is only connected to the second half of the input channels.
Default: groups = 1. Default: groups = 1.
param_attr (ParamAttr): The parameter attribute for learnable parameters/weights param_attr (ParamAttr): The parameter attribute for learnable parameters/weights
of this layer. If it is set to None, the parameter is initialized with of conv2d_transpose. If it is set to None or one attribute of ParamAttr, conv2d_transpose
Xavier. Default: None. will create ParamAttr as param_attr. If the Initializer of the param_attr
bias_attr (ParamAttr): The parameter attribute for the bias of this layer. is not set, the parameter is initialized with Xavier. Default: None.
bias_attr (ParamAttr|bool|None): The parameter attribute for the bias of conv2d_transpose.
If it is set to False, no bias will be added to the output units. If it is set to False, no bias will be added to the output units.
If it is set to None, the bias is initialized zero. Default: None. If it is set to None or one attribute of ParamAttr, conv2d_transpose
will create ParamAttr as bias_attr. If the Initializer of the bias_attr
is not set, the bias is initialized zero. Default: None.
use_cudnn(bool): Use cudnn kernel or not, it is valid only when the cudnn use_cudnn(bool): Use cudnn kernel or not, it is valid only when the cudnn
library is installed. Default: True. library is installed. Default: True.
act (str): Activation type, if it is set to None, activation is not appended. act (str): Activation type, if it is set to None, activation is not appended.
...@@ -2598,11 +2610,14 @@ def conv3d_transpose(input, ...@@ -2598,11 +2610,14 @@ def conv3d_transpose(input,
filters is only connected to the second half of the input channels. filters is only connected to the second half of the input channels.
Default: groups=1 Default: groups=1
param_attr (ParamAttr): The parameter attribute for learnable parameters/weights param_attr (ParamAttr): The parameter attribute for learnable parameters/weights
of this layer. If it is set to None, the parameter is initialized with of conv3d_transpose. If it is set to None or one attribute of ParamAttr, conv3d_transpose
Xavier. Default: None. will create ParamAttr as param_attr. If the Initializer of the param_attr
bias_attr (ParamAttr): The parameter attribute for the bias of this layer. is not set, the parameter is initialized with Xavier. Default: None.
bias_attr (ParamAttr|bool|None): The parameter attribute for the bias of conv3d_transpose.
If it is set to False, no bias will be added to the output units. If it is set to False, no bias will be added to the output units.
If it is set to None, the bias is initialized zero. Default: None. If it is set to None or one attribute of ParamAttr, conv3d_transpose
will create ParamAttr as bias_attr. If the Initializer of the bias_attr
is not set, the bias is initialized zero. Default: None.
use_cudnn(bool): Use cudnn kernel or not, it is valid only when the cudnn use_cudnn(bool): Use cudnn kernel or not, it is valid only when the cudnn
library is installed. Default: True library is installed. Default: True
act (str): Activation type, if it is set to None, activation is not appended. act (str): Activation type, if it is set to None, activation is not appended.
......
...@@ -77,15 +77,20 @@ def simple_img_conv_pool(input, ...@@ -77,15 +77,20 @@ def simple_img_conv_pool(input,
convolution in Alex Krizhevsky's Deep CNN paper: when group=2, convolution in Alex Krizhevsky's Deep CNN paper: when group=2,
the first half of the filters is only connected to the first half the first half of the filters is only connected to the first half
of the input channels, while the second half of the filters is only of the input channels, while the second half of the filters is only
connected to the second half of the input channels. Default: groups=1 connected to the second half of the input channels. Default: groups=1.
param_attr (ParamAttr): The parameter attribute for learnable parameters/weights param_attr (ParamAttr): The parameter attribute for learnable parameters/weights
of conv2d. If it is set to None, the parameter is initialized with of conv2d. If it is set to None or one attribute of ParamAttr, conv2d
:math:`Normal(0.0, std)`, and the :math:`std` is :math:`(\\frac{2.0 }{filter\_elem\_num})^{0.5}`. will create ParamAttr as param_attr. If the Initializer of the param_attr
is not set, the parameter is initialized with :math:`Normal(0.0, std)`,
and the :math:`std` is :math:`(\\frac{2.0 }{filter\_elem\_num})^{0.5}`.
Default: None. Default: None.
bias_attr (ParamAttr): The parameter attribute for the bias of conv2d. bias_attr (ParamAttr|bool|None): The parameter attribute for the bias of conv2d.
If it is set to False, no bias will be added to the output units. If it is set to False, no bias will be added to the output units.
If it is set to None, the bias is initialized zero. Default: None. If it is set to None or one attribute of ParamAttr, conv2d
act (str): Activation type for Conv2d. Default: None will create ParamAttr as bias_attr. If the Initializer of the bias_attr
is not set, the bias is initialized zero. Default: None.
act (str): Activation type for conv2d, if it is set to None, activation is not
appended. Default: None.
use_cudnn (bool): Use cudnn kernel or not, it is valid only when the cudnn use_cudnn (bool): Use cudnn kernel or not, it is valid only when the cudnn
library is installed. Default: True library is installed. Default: True
......
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