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体验新版 GitCode,发现更多精彩内容 >>
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797249bc
编写于
11月 09, 2017
作者:
C
Cao Ying
提交者:
GitHub
11月 09, 2017
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差异文件
Merge pull request #5494 from lcy-seso/fix_nce
NCE does not need to set its activation.
上级
53cb4df0
a3a158c5
变更
1
隐藏空白更改
内联
并排
Showing
1 changed file
with
35 addition
and
30 deletion
+35
-30
python/paddle/trainer_config_helpers/layers.py
python/paddle/trainer_config_helpers/layers.py
+35
-30
未找到文件。
python/paddle/trainer_config_helpers/layers.py
浏览文件 @
797249bc
...
...
@@ -5479,7 +5479,11 @@ def crf_decoding_layer(input,
return
LayerOutput
(
name
,
LayerType
.
CRF_DECODING_LAYER
,
parents
,
size
=
1
)
@
wrap_act_default
(
act
=
SigmoidActivation
())
"""
Following are cost Layers.
"""
@
wrap_bias_attr_default
(
has_bias
=
True
)
@
wrap_param_attr_default
()
@
wrap_name_default
()
...
...
@@ -5487,7 +5491,6 @@ def crf_decoding_layer(input,
def
nce_layer
(
input
,
label
,
num_classes
=
None
,
act
=
None
,
param_attr
=
None
,
weight
=
None
,
num_neg_samples
=
10
,
...
...
@@ -5496,9 +5499,12 @@ def nce_layer(input,
bias_attr
=
None
,
layer_attr
=
None
):
"""
Noise-contrastive estimation.
Implements the method in the following paper:
A fast and simple algorithm for training neural probabilistic language models.
Noise-contrastive estimation. This layer implements the method in the
following paper:
Reference:
A fast and simple algorithm for training neural probabilistic language
models. https://www.cs.toronto.edu/~amnih/papers/ncelm.pdf
The example usage is:
...
...
@@ -5510,31 +5516,37 @@ def nce_layer(input,
:param name: The name of this layer. It is optional.
:type name: basestring
:param input: The input layers. It could be a LayerOutput of list/tuple of LayerOutput.
:param input: The input layers. It should be a LayerOutput or a list/tuple
of LayerOutput.
:type input: LayerOutput | list | tuple | collections.Sequence
:param label:
label layer
:param label:
The ground truth.
:type label: LayerOutput
:param weight: weight layer, can be None(default)
:param weight: The weight layer defines a weight for each sample in the
mini-batch. The default value is None.
:type weight: LayerOutput
:param num_classes:
number of classes
.
:param num_classes:
The class number
.
:type num_classes: int
:param act: Activation type. SigmoidActivation is the default.
:type act: BaseActivation
:param param_attr: The Parameter Attribute|list.
:type param_attr: ParameterAttribute
:param num_neg_samples: number of negative samples. Default is 10.
:param param_attr: The parameter attributes.
:type param_attr: ParameterAttribute|list
:param num_neg_samples: The number of sampled negative labels. The default
value is 10.
:type num_neg_samples: int
:param neg_distribution: The distribution for generating the random negative labels.
A uniform distribution will be used if not provided.
If not None, its length must be equal to num_classes.
:param neg_distribution: The discrete noisy distribution over the output
space from which num_neg_samples negative labels
are sampled. If this parameter is not set, a
uniform distribution will be used. A user defined
distribution is a list whose length must be equal
to the num_classes. Each member of the list defines
the probability of a class given input x.
:type neg_distribution: list | tuple | collections.Sequence | None
:param bias_attr: The bias attribute. If the parameter is set to False or an object
whose type is not ParameterAttribute, no bias is defined. If the
parameter is set to True, the bias is initialized to zero.
:param bias_attr: The attribute for bias. If this parameter is set False or
any object whose type is not ParameterAttribute, no bias
is added. If this parameter is set True, the bias is
initialized to zero.
:type bias_attr: ParameterAttribute | None | bool | Any
:param layer_attr: Extra Layer Attribute.
:type layer_attr: ExtraLayerAttribute
:return:
layer name
.
:return:
The LayerOutput object
.
:rtype: LayerOutput
"""
if
isinstance
(
input
,
LayerOutput
):
...
...
@@ -5557,8 +5569,6 @@ def nce_layer(input,
assert
isinstance
(
neg_distribution
,
collections
.
Sequence
)
assert
len
(
neg_distribution
)
==
num_classes
assert
abs
(
sum
(
neg_distribution
)
-
1.0
)
<
1e-5
if
not
isinstance
(
act
,
BaseActivation
):
raise
TypeError
()
ipts_for_layer
=
[]
parents
=
[]
...
...
@@ -5580,7 +5590,7 @@ def nce_layer(input,
type
=
LayerType
.
NCE_LAYER
,
num_classes
=
num_classes
,
neg_sampling_dist
=
neg_distribution
,
active_type
=
act
.
name
,
active_type
=
SigmoidActivation
()
.
name
,
num_neg_samples
=
num_neg_samples
,
inputs
=
ipts_for_layer
,
bias
=
ParamAttr
.
to_bias
(
bias_attr
),
...
...
@@ -5590,12 +5600,7 @@ def nce_layer(input,
LayerType
.
NCE_LAYER
,
parents
=
parents
,
size
=
l
.
config
.
size
,
activation
=
act
)
"""
following are cost Layers.
"""
activation
=
SigmoidActivation
())
@
wrap_name_default
()
...
...
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