提交 b653abad 编写于 作者: R ranqiu

fix doc

上级 ddd41582
......@@ -6615,7 +6615,7 @@ def row_conv_layer(input,
.. math::
r_{t,r} = \sum_{j=1}^{k + 1} {w_{i,j}h_{t+j-1, i}}
\quad \text{for} \quad (1 \leq i \leq d)
\quad \\text{for} \quad (1 \leq i \leq d)
Note:
The `context_len` is `k + 1`. That is to say, the lookahead step
......@@ -6764,7 +6764,7 @@ def gated_unit_layer(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
it is also used to produce a gate weight :math:`\sigma`. Element-wise
product between :match:`X'` and :math:`\sigma` is finally returned.
product between :math:`X'` and :math:`\sigma` is finally returned.
Reference:
`Language Modeling with Gated Convolutional Networks
......@@ -7460,7 +7460,7 @@ def factorization_machine(input,
Factorization Machine with the formula:
.. math::
y = \sum_{i=1}^{n-1}\sum_{j=i+1}^n\langle v_i, v_j \rangle 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:
X is the input vector with size n. V is the factor matrix. Each row of V
......
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