Skip to content

fix doc #6940

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Dec 24, 2017
Merged

fix doc #6940

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 3 additions & 3 deletions python/paddle/trainer_config_helpers/layers.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -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
Expand Down Expand Up @@ -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
Expand Down Expand Up @@ -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
Expand Down