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体验新版 GitCode,发现更多精彩内容 >>
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dd711c37
编写于
6月 14, 2018
作者:
D
dzhwinter
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电子邮件补丁
差异文件
"add beam search"
上级
dbe0fe6d
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1 changed file
with
19 addition
and
7 deletion
+19
-7
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+19
-7
未找到文件。
python/paddle/fluid/layers/nn.py
浏览文件 @
dd711c37
...
...
@@ -834,11 +834,14 @@ def linear_chain_crf(input, label, param_attr=None):
Args:
input(${emission_type}): ${emission_comment}
input(${transition_type}): ${transition_comment}
label(${label_type}): ${label_comment}
param_attr(ParamAttr): The attribute of the learnable parameter.
Returns:
${log_likelihood_comment}
${transitionexps_comment}
${emissionexps_comment}
"""
helper
=
LayerHelper
(
'linear_chain_crf'
,
**
locals
())
...
...
@@ -1170,10 +1173,6 @@ def sequence_conv(input,
Variable: output of sequence_conv
"""
# FIXME(dzh) : want to unify the argument of python layer
# function. So we ignore some unecessary attributes.
# such as, padding_trainable, context_start.
helper
=
LayerHelper
(
'sequence_conv'
,
**
locals
())
dtype
=
helper
.
input_dtype
()
filter_shape
=
[
filter_size
*
input
.
shape
[
1
],
num_filters
]
...
...
@@ -2051,18 +2050,31 @@ def layer_norm(input,
def
beam_search_decode
(
ids
,
scores
,
name
=
None
):
"""
Beam Search Decode
This layers is to pack the output of beam search layer into sentences and
associated scores. It is usually called after the beam search layer.
Typically, the output of beam search layer is a tensor of selected ids, with
a tensor of the score of each id. Beam search layer's output ids, however,
are generated directly during the tree search, and they are stacked by each
level of the search tree. Thus we need to reorganize them into sentences,
based on the score of each id. This layer takes the output of beam search
layer as input and repack them into sentences.
${beam_search_decode}
Args:
ids (Variable): ${ids_comment}
scores (Variable): ${scores_comment}
ids (Variable): The selected ids, output of beam search layer.
scores (Variable): The associated scores of the ids, out put of beam
search layer.
name (str): The name of this layer. It is optional.
Returns:
tuple(Variable): a tuple of two output variable: sentence_ids, sentence_scores
tuple(Variable): a tuple of two output tensors: sentence_ids, sentence_scores.
sentence_ids is a tensor with shape [size, length], where size is the
beam size of beam search, and length is the length of each sentence.
Note that the length of sentences may vary.
sentence_scores is a tensor with the same shape as sentence_ids.
Examples:
.. code-block:: python
...
...
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