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体验新版 GitCode,发现更多精彩内容 >>
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aa756a3d
编写于
12月 24, 2017
作者:
R
ranqiu92
提交者:
GitHub
12月 24, 2017
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Merge pull request #6940 from ranqiu92/doc
fix doc
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7e659a0a
b653abad
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python/paddle/trainer_config_helpers/layers.py
python/paddle/trainer_config_helpers/layers.py
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python/paddle/trainer_config_helpers/layers.py
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@@ -6629,7 +6629,7 @@ def row_conv_layer(input,
...
@@ -6629,7 +6629,7 @@ def row_conv_layer(input,
.. math::
.. math::
r_{t,r} = \sum_{j=1}^{k + 1} {w_{i,j}h_{t+j-1, i}}
r_{t,r} = \sum_{j=1}^{k + 1} {w_{i,j}h_{t+j-1, i}}
\quad
\t
ext{for} \quad (1 \leq i \leq d)
\quad
\
\
text{for} \quad (1 \leq i \leq d)
Note:
Note:
The `context_len` is `k + 1`. That is to say, the lookahead step
The `context_len` is `k + 1`. That is to say, the lookahead step
...
@@ -6778,7 +6778,7 @@ def gated_unit_layer(input,
...
@@ -6778,7 +6778,7 @@ def gated_unit_layer(input,
The gated unit layer implements a simple gating mechanism over the input.
The gated unit layer implements a simple gating mechanism over the input.
The input :math:`X` is first projected into a new space :math:`X'`, and
The input :math:`X` is first projected into a new space :math:`X'`, and
it is also used to produce a gate weight :math:`\sigma`. Element-wise
it is also used to produce a gate weight :math:`\sigma`. Element-wise
product between :mat
c
h:`X'` and :math:`\sigma` is finally returned.
product between :math:`X'` and :math:`\sigma` is finally returned.
Reference:
Reference:
`Language Modeling with Gated Convolutional Networks
`Language Modeling with Gated Convolutional Networks
...
@@ -7474,7 +7474,7 @@ def factorization_machine(input,
...
@@ -7474,7 +7474,7 @@ def factorization_machine(input,
Factorization Machine with the formula:
Factorization Machine with the formula:
.. math::
.. math::
y = \sum_{i=1}^{n-1}\sum_{j=i+1}^n\langle v_i, v_j
\r
angle x_i x_j
y = \sum_{i=1}^{n-1}\sum_{j=i+1}^n\langle v_i, v_j
\
\
rangle x_i x_j
Note:
Note:
X is the input vector with size n. V is the factor matrix. Each row of V
X is the input vector with size n. V is the factor matrix. Each row of V
...
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