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ddd41582
编写于
12月 22, 2017
作者:
R
ranqiu
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电子邮件补丁
差异文件
Update the annotations of layers.py
上级
76f0bd83
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1
隐藏空白更改
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1 changed file
with
56 addition
and
53 deletion
+56
-53
python/paddle/trainer_config_helpers/layers.py
python/paddle/trainer_config_helpers/layers.py
+56
-53
未找到文件。
python/paddle/trainer_config_helpers/layers.py
浏览文件 @
ddd41582
...
...
@@ -270,7 +270,7 @@ class LayerType(object):
@
staticmethod
def
is_layer_type
(
type_name
):
"""
If
type_name is a layer type.
Whether
type_name is a layer type.
:param type_name: layer type name. Because layer type enumerations are
strings.
...
...
@@ -441,7 +441,7 @@ def full_matrix_projection(input, size=0, param_attr=None):
with mixed_layer(size=100) as m:
m += full_matrix_projection(input=layer)
2. When used as an independ
a
nt object like this, you must set the size:
2. When used as an independ
e
nt object like this, you must set the size:
.. code-block:: python
...
...
@@ -451,11 +451,11 @@ def full_matrix_projection(input, size=0, param_attr=None):
:param input: The input of this layer.
:type input: LayerOutput
:param size: The
parameter size. Means the width of paramet
er.
:param size: The
dimension of this lay
er.
:type size: int
:param param_attr:
Parameter config, None if use default
.
:param param_attr:
The parameter attribute. See ParameterAttribute for details
.
:type param_attr: ParameterAttribute
:return:
A
FullMatrixProjection Object.
:return: FullMatrixProjection Object.
:rtype: FullMatrixProjection
"""
proj
=
FullMatrixProjection
(
...
...
@@ -468,12 +468,12 @@ def full_matrix_projection(input, size=0, param_attr=None):
def
trans_full_matrix_projection
(
input
,
size
=
0
,
param_attr
=
None
):
"""
Different from full_matrix_projection, this projection performs matrix
multiplication, using transpose of weight.
multiplication, using t
he t
ranspose of weight.
.. math::
out.row[i] += in.row[i] * w^\mathrm{T}
:math:`w^\mathrm{T}` means transpose of weight.
:math:`w^\mathrm{T}` means t
he t
ranspose of weight.
The simply usage is:
.. code-block:: python
...
...
@@ -489,9 +489,9 @@ def trans_full_matrix_projection(input, size=0, param_attr=None):
:type input: LayerOutput
:param size: The parameter size. Means the width of parameter.
:type size: int
:param param_attr:
Parameter config, None if use default
.
:param param_attr:
The parameter attribute. See ParameterAttribute for details
.
:type param_attr: ParameterAttribute
:return:
A
TransposedFullMatrixProjection Object.
:return: TransposedFullMatrixProjection Object.
:rtype: TransposedFullMatrixProjection
"""
proj
=
TransposedFullMatrixProjection
(
...
...
@@ -521,7 +521,7 @@ def table_projection(input, size=0, param_attr=None):
with mixed_layer(size=100) as m:
m += table_projection(input=layer)
2. When used as an independ
a
nt object like this, you must set the size:
2. When used as an independ
e
nt object like this, you must set the size:
.. code-block:: python
...
...
@@ -532,11 +532,11 @@ def table_projection(input, size=0, param_attr=None):
:param input: The input of this layer, which must contains id fields.
:type input: LayerOutput
:param size: The
parameter size. Means the width of parameter
.
:param size: The
dimension of the output
.
:type size: int
:param param_attr:
Parameter config, None if use default
.
:param param_attr:
The parameter attribute. See ParameterAttribute for details
.
:type param_attr: ParameterAttribute
:return:
A
TableProjection Object.
:return: TableProjection Object.
:rtype: TableProjection
"""
proj
=
TableProjection
(
...
...
@@ -547,7 +547,7 @@ def table_projection(input, size=0, param_attr=None):
def
identity_projection
(
input
,
offset
=
None
,
size
=
None
):
"""
1. I
dentityProjection if offset=None. It perform
s:
1. I
f offset=None, it performs IdentityProjection as follow
s:
.. math::
out.row[i] += in.row[i]
...
...
@@ -559,9 +559,8 @@ def identity_projection(input, offset=None, size=None):
proj = identity_projection(input=layer)
2. IdentityOffsetProjection if offset!=None. It likes IdentityProjection,
but layer size may be smaller than input size.
It select dimesions [offset, offset+layer_size) from input:
2. If offset!=None, It executes IdentityOffsetProjection and takes the
elements of the input in the range [offset, offset+size) as output.
.. math::
out.row[i] += in.row[i +
\\
textrm{offset}]
...
...
@@ -573,14 +572,20 @@ def identity_projection(input, offset=None, size=None):
proj = identity_projection(input=layer,
offset=10)
Note that
both of two projections should not have any
parameter.
Note that
neither of the projections have trainable
parameter.
:param input: The input of this layer.
:type input: LayerOutput
:param offset: Offset, None if use default.
:param offset: The offset from the start of the input. The input's
elements in the range [offset, offset+size) will be
taken as output. If this parameter is not set or set
to None, the output will be the same as the input.
:type offset: int
:return: A IdentityProjection or IdentityOffsetProjection object
:rtype: IdentityProjection or IdentityOffsetProjection
:param size: The dimension of this layer. It will be neglected
when offset is None or not set.
:type size: int
:return: IdentityProjection or IdentityOffsetProjection object
:rtype: IdentityProjection | IdentityOffsetProjection
"""
if
offset
is
None
:
proj
=
IdentityProjection
(
input_layer_name
=
input
.
name
)
...
...
@@ -596,8 +601,8 @@ def identity_projection(input, offset=None, size=None):
def
slice_projection
(
input
,
slices
):
"""
slice_projection
can slice
the input value into multiple parts,
and then select some of them to merge
into a new output.
slice_projection
slices
the input value into multiple parts,
then selects and merges some of them
into a new output.
.. math::
output = [input.slices()]
...
...
@@ -608,15 +613,13 @@ def slice_projection(input, slices):
proj = slice_projection(input=layer, slices=[(0, 10), (20, 30)])
Note that slice_projection
should not have any
parameter.
Note that slice_projection
has no trainable
parameter.
:param input: The input of this layer.
:type input: LayerOutput
:param slices: An array of slice parameters.
Each slice contains the start and end offsets based
on the input.
:type slices: pair of int
:return: A SliceProjection object
:param slices: A list of start and end offsets of each slice.
:type slices: list of tuple
:return: SliceProjection object.
:rtype: SliceProjection
"""
assert
len
(
slices
)
>=
1
...
...
@@ -636,8 +639,7 @@ def slice_projection(input, slices):
@
wrap_param_attr_default
()
def
scaling_projection
(
input
,
param_attr
=
None
):
"""
scaling_projection multiplies the input with a scalar parameter and add to
the output.
scaling_projection multiplies the input with a scalar parameter.
.. math::
out += w * in
...
...
@@ -650,9 +652,9 @@ def scaling_projection(input, param_attr=None):
:param input: The input of this layer.
:type input: LayerOutput
:param param_attr:
Parameter config, None if use default
.
:param param_attr:
The parameter attribute. See ParameterAttribute for details
.
:type param_attr: ParameterAttribute
:return:
A ScalingProjection object
:return:
ScalingProjection object.
:rtype: ScalingProjection
"""
proj
=
ScalingProjection
(
input_layer_name
=
input
.
name
,
**
param_attr
.
attr
)
...
...
@@ -663,8 +665,8 @@ def scaling_projection(input, param_attr=None):
@
wrap_param_attr_default
()
def
dotmul_projection
(
input
,
param_attr
=
None
):
"""
DotMulProjection
with a layer as input.
It performs
element-wise multiplication with weight.
DotMulProjection
takes a layer as input and performs
element-wise multiplication with weight.
.. math::
out.row[i] += in.row[i] .* weight
...
...
@@ -679,9 +681,9 @@ def dotmul_projection(input, param_attr=None):
:param input: The input of this layer.
:type input: LayerOutput
:param param_attr:
Parameter config, None if use default
.
:param param_attr:
The parameter attribute. See ParameterAttribute for details
.
:type param_attr: ParameterAttribute
:return:
A DotMulProjection O
bject.
:return:
DotMulProjection o
bject.
:rtype: DotMulProjection
"""
proj
=
DotMulProjection
(
...
...
@@ -698,7 +700,7 @@ def dotmul_operator(a=None, b=None, scale=1, **kwargs):
out.row[i] += scale * (a.row[i] .* b.row[i])
where :math:`.*` means element-wise multiplication, and
scale is a config scalar, its default value is
one
.
scale is a config scalar, its default value is
1
.
The example usage is:
...
...
@@ -706,13 +708,13 @@ def dotmul_operator(a=None, b=None, scale=1, **kwargs):
op = dotmul_operator(a=layer1, b=layer2, scale=0.5)
:param a:
Input layer1
:param a:
The first input of this layer.
:type a: LayerOutput
:param b:
Input layer2
:param b:
The second input of this layer.
:type b: LayerOutput
:param scale:
config scalar, default value is one
.
:param scale:
A scalar to scale the product. Its default value is 1
.
:type scale: float
:return:
A DotMulOperator O
bject.
:return:
DotMulOperator o
bject.
:rtype: DotMulOperator
"""
if
'x'
in
kwargs
or
'y'
in
kwargs
:
...
...
@@ -738,28 +740,29 @@ def context_projection(input,
"""
Context Projection.
It just
simply reorganizes input sequence, combines "context_len" sequenc
e
to one context from context_start. "context_start" will be set to
-(context_len - 1) / 2 by default.
If context position
out of sequence
It just
reorganizes input sequence, combines "context_len" elements of th
e
sequence
to one context from context_start. "context_start" will be set to
-(context_len - 1) / 2 by default.
When context position is
out of sequence
length, padding will be filled as zero if padding_attr = False, otherwise
it is trainable.
For example, origin sequence is [A B C D E F G], context len is 3,
then
after context projection and not set padding_attr
, sequence will
For example, origin sequence is [A B C D E F G], context len is 3,
padding_attr
is not set, then after context projection
, sequence will
be [ 0AB ABC BCD CDE DEF EFG FG0 ].
:param input: The input of this layer, which should be a sequence.
:type input: LayerOutput
:param context_len:
context length
.
:param context_len:
The length of the context
.
:type context_len: int
:param context_start:
context start position. Default
is
:param context_start:
The start position of the context. The default value
is
-(context_len - 1)/2
:type context_start: int
:param padding_attr: Padding Parameter Attribute. If false, it means padding
always be zero. Otherwise Padding is learnable, and
parameter attribute is set by this parameter.
:param padding_attr: Parameter attribute of the padding. If the parameter is
set to False, padding will be zero. In other cases, the
padding is trainable, and its parameter attribute is set
by this parameter.
:type padding_attr: bool | ParameterAttribute
:return: Projection
:return: Projection
object.
:rtype: Projection
"""
context_start
=
-
(
...
...
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