diff --git a/develop/doc/api/v2/fluid/layers.html b/develop/doc/api/v2/fluid/layers.html index 2be7444eca0f234229f4d799332c759d7366f37d..b0200798185247f99b05332fda1cbfcd4d0a38a6 100644 --- a/develop/doc/api/v2/fluid/layers.html +++ b/develop/doc/api/v2/fluid/layers.html @@ -2020,15 +2020,18 @@ explain how sequence_expand works:

GRU unit layer. The equation of a gru step is:

-\[ \begin{align}\begin{aligned}u_t & = actGate(xu_{t} + W_u h_{t-1} + b_u)\\r_t & = actGate(xr_{t} + W_r h_{t-1} + b_r)\\ch_t & = actNode(xc_t + W_c dot(r_t, h_{t-1}) + b_c)\\h_t & = dot((1-u_t), ch_{t-1}) + dot(u_t, h_t)\end{aligned}\end{align} \]
+\[ \begin{align}\begin{aligned}u_t & = actGate(xu_{t} + W_u h_{t-1} + b_u)\\r_t & = actGate(xr_{t} + W_r h_{t-1} + b_r)\\m_t & = actNode(xm_t + W_c dot(r_t, h_{t-1}) + b_m)\\h_t & = dot((1-u_t), m_t) + dot(u_t, h_{t-1})\end{aligned}\end{align} \]

The inputs of gru unit includes \(z_t\), \(h_{t-1}\). In terms of the equation above, the \(z_t\) is split into 3 parts - -\(xu_t\), \(xr_t\) and \(xc_t\). This means that in order to +\(xu_t\), \(xr_t\) and \(xm_t\). This means that in order to implement a full GRU unit operator for an input, a fully connected layer has to be applied, such that \(z_t = W_{fc}x_t\).

-

This layer has three outputs \(h_t\), \(dot(r_t, h_{t - 1})\) -and concatenation of \(u_t\), \(r_t\) and \(ch_t\).

+

The terms \(u_t\) and \(r_t\) represent the update and reset gates +of the GRU cell. Unlike LSTM, GRU has one lesser gate. However, there is +an intermediate candidate hidden output, which is denoted by \(m_t\). +This layer has three outputs \(h_t\), \(dot(r_t, h_{t-1})\) +and concatenation of \(u_t\), \(r_t\) and \(m_t\).

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\ No newline at end of file diff --git a/develop/doc_cn/api/v2/fluid/layers.html b/develop/doc_cn/api/v2/fluid/layers.html index 4e66efd868153852df2ce0f2070df670e5a975d5..91ab91bf6af363d02e7384d1c8a224bda5ef8edb 100644 --- a/develop/doc_cn/api/v2/fluid/layers.html +++ b/develop/doc_cn/api/v2/fluid/layers.html @@ -2033,15 +2033,18 @@ explain how sequence_expand works:

GRU unit layer. The equation of a gru step is:

-\[ \begin{align}\begin{aligned}u_t & = actGate(xu_{t} + W_u h_{t-1} + b_u)\\r_t & = actGate(xr_{t} + W_r h_{t-1} + b_r)\\ch_t & = actNode(xc_t + W_c dot(r_t, h_{t-1}) + b_c)\\h_t & = dot((1-u_t), ch_{t-1}) + dot(u_t, h_t)\end{aligned}\end{align} \]
+\[ \begin{align}\begin{aligned}u_t & = actGate(xu_{t} + W_u h_{t-1} + b_u)\\r_t & = actGate(xr_{t} + W_r h_{t-1} + b_r)\\m_t & = actNode(xm_t + W_c dot(r_t, h_{t-1}) + b_m)\\h_t & = dot((1-u_t), m_t) + dot(u_t, h_{t-1})\end{aligned}\end{align} \]

The inputs of gru unit includes \(z_t\), \(h_{t-1}\). In terms of the equation above, the \(z_t\) is split into 3 parts - -\(xu_t\), \(xr_t\) and \(xc_t\). This means that in order to +\(xu_t\), \(xr_t\) and \(xm_t\). This means that in order to implement a full GRU unit operator for an input, a fully connected layer has to be applied, such that \(z_t = W_{fc}x_t\).

-

This layer has three outputs \(h_t\), \(dot(r_t, h_{t - 1})\) -and concatenation of \(u_t\), \(r_t\) and \(ch_t\).

+

The terms \(u_t\) and \(r_t\) represent the update and reset gates +of the GRU cell. Unlike LSTM, GRU has one lesser gate. However, there is +an intermediate candidate hidden output, which is denoted by \(m_t\). +This layer has three outputs \(h_t\), \(dot(r_t, h_{t-1})\) +and concatenation of \(u_t\), \(r_t\) and \(m_t\).

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