未验证 提交 fcc50cb4 编写于 作者: C Cao Ying 提交者: GitHub

Merge pull request #5437 from ranqiu92/doc

Update annotations of layers.py.
......@@ -6548,26 +6548,27 @@ def switch_order_layer(input,
@layer_support()
def crop_layer(input, offset, axis=2, shape=None, name=None, layer_attr=None):
"""
This layer crops images by offset and shape. User can set crop shape by
args 'shape' explicitly or by reference input layer.
This layer crops images according to the offset and shape. Users can set
the crop shape through the argument 'shape' explicitly or by specifying a
reference input layer.
The example usage is:
.. code-block:: python
crop = crop_layer(input=[image_input, reference_input], axis=2, offset=[2, 3])
:param input: The input of this layer. If two inputs are given, the second input
will be regarded as reference input.
:param input: The input of this layer. If two inputs are given, the second one
will be regarded as the reference.
:type input: LayerOutput | Sequence
:param offset: The crop offset.
:type offset: Sequence
:param axis: start axis to be cropped. To image input layer:
:param axis: The start axis to be cropped. For image input layer:
- 0: batch size
- 1: channels
- 2: height
- 3: width
:type partial_sum: int
:param shape: The shape to be cropped. Default is None.
:type axis: int
:param shape: The shape to be cropped to. Default is None.
:type shape: Sequence | None
:param name: The name of this layer. It is optional.
:type name: basestring
......@@ -6702,9 +6703,9 @@ def seq_slice_layer(input, starts, ends, name=None):
:type name: basestring
:param input: The input of this layer, which should be a sequence.
:type input: LayerOutput
:param starts: start indices to slice the input sequence.
:param starts: The start indices to slice the input sequence.
:type starts: LayerOutput | None
:param ends: end indices to slice the input sequence.
:param ends: The end indices to slice the input sequence.
:type ends: LayerOutput | None
:return: LayerOutput object.
:rtype: LayerOutput
......@@ -6744,7 +6745,7 @@ def seq_slice_layer(input, starts, ends, name=None):
@layer_support()
def kmax_seq_score_layer(input, name=None, beam_size=1):
"""
This layer accepts one input which are scores over a sequence or a nested
This layer accepts one input which is scores over a sequence or a nested
sequence, and returns indices of beam_size sequences with highest scores.
.. code-block:: python
......@@ -6754,11 +6755,11 @@ def kmax_seq_score_layer(input, name=None, beam_size=1):
:param name: The name of this layer. It is optional.
:type name: basestring
:param input: The input of this layer. It stores scores over a sequence or a nested
sequence and its size must be 1.
:param input: The input of this layer. It stores scores over a sequence or
a nested sequence and its size must be 1.
:type input: LayerOutput
:param beam_size: sequence indices with top beam_size scores are returned.
:type beam_size: double
:param beam_size: The indices of the sequences with top beam_size scores are returned.
:type beam_size: int
:return: LayerOutput object.
:rtype: LayerOutput
"""
......@@ -6814,38 +6815,42 @@ def img_conv3d_layer(input,
:type name: basestring
:param input: The input of this layer.
:type input: LayerOutput
:param filter_size: The x dimension of a filter kernel. Or input a list.
: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: Each filter group's number of filter
:param num_filters: The number of filters in each group.
:type num_filters: int
:param act: Activation type. ReluActivation is the default.
:type act: BaseActivation
:param groups: Group size of filters.
:param groups: The number of the filter groups.
:type groups: int
:param stride: The x dimension of the stride. Or input a tuple for two image
dimension.
:param stride: The strides of the convolution along three axises. If the parameter
is set to one integer, the three strides will be same.
:type stride: int | tuple | list
:param padding: The x dimension of the padding. Or input a tuple for two
image dimension
:param padding: The numbers of padding along three axises. If the parameter is set to
one integer, they will be same.
:type padding: int | tuple | list
:param bias_attr: Convolution bias attribute. None means default bias.
False means no bias.
:param bias_attr: The Bias Attribute. If the parameter is set to
False or something not type of ParameterAttribute,
no bias is defined. If the parameter is set to
True, the bias is initialized to zero.
:type bias_attr: ParameterAttribute | None | bool | Any
:param num_channels: number of input channels. If None will be set
automatically from previous output.
:param num_channels: The number of input channels. If the parameter is not set or
set to None, its actual value will be automatically set to
the channels number of the input .
:type num_channels: int
:param param_attr: Convolution param attribute. None means default attribute
:param param_attr: The parameter attribute of the convolution.
:type param_attr: ParameterAttribute
:param shared_biases: Is biases will be shared between filters or not.
:param shared_biases: Whether biases will be shared between filters or not.
:type shared_biases: bool
:param layer_attr: Layer Extra Attribute.
:param layer_attr: Extra layer attributes.
:type layer_attr: ExtraLayerAttribute
:param trans: true if it is a convTransLayer, false if it is a convLayer
:param trans: True if it is a convTransLayer, False if it is a convLayer
:type trans: bool
:param layer_type: specify the layer_type, default is None. If trans=True,
layer_type has to be "exconvt" or "cudnn_convt",
otherwise layer_type has to be either "exconv" or
"cudnn_conv"
:type layer_type: String
:param layer_type: Specify the layer_type. If the parameter is set, it must be "deconv3d"
when trans=True. If not set, it will be automatically set to "deconv3d"
when trans=True and "conv3d" when trans=False.
:type layer_type: basestring
:return: LayerOutput object.
:rtype: LayerOutput
"""
......@@ -6927,7 +6932,7 @@ def img_conv3d_layer(input,
def scale_shift_layer(input, name=None, param_attr=None, bias_attr=None):
"""
A layer applies a linear transformation to each element in each row of
the input matrix. For each element, the layer first re-scale it and then
the input matrix. For each element, the layer first re-scales it and then
adds a bias to it.
This layer is very like the SlopeInterceptLayer, except the scale and
......@@ -7001,12 +7006,12 @@ def sub_seq_layer(input, offsets, sizes, act=None, bias_attr=None, name=None):
:type name: basestring
:param input: The input of this layer, which should be sequence.
:type input: LayerOutput
:param offsets: offset indices to slice the input sequence, which should be
sequence type.
:param offsets: The offset indices to slice the input sequence, which should
be sequence type.
:type offsets: LayerOutput
:param sizes: sizes of the sub-sequences, which should be sequence type.
:param sizes: The sizes of the sub-sequences, which should be sequence type.
:type sizes: LayerOutput
:param act: Layer activation, default is LinearActivation
:param act: Activation type, LinearActivation is the default.
:type act: BaseActivation.
:param bias_attr: The Bias Attribute. If the parameter is set to
False or something not type of ParameterAttribute,
......
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