Trait opencv::dnn::RNNLayer

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pub trait RNNLayer: LayerTrait + RNNLayerConst {
    fn as_raw_mut_RNNLayer(&mut self) -> *mut c_void;

    fn set_weights(
        &mut self,
        wxh: &Mat,
        bh: &Mat,
        whh: &Mat,
        who: &Mat,
        bo: &Mat
    ) -> Result<()> { ... }
    fn set_produce_hidden_output(&mut self, produce: bool) -> Result<()> { ... }
}

Required Methods

source

fn as_raw_mut_RNNLayer(&mut self) -> *mut c_void

Provided Methods

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fn set_weights(
    &mut self,
    wxh: &Mat,
    bh: &Mat,
    whh: &Mat,
    who: &Mat,
    bo: &Mat
) -> Result<()>

Setups learned weights.

Recurrent-layer behavior on each step is defined by current input @f$ x_t @f$, previous state @f$ h_t @f$ and learned weights as follows: @f{eqnarray*}{ h_t &= tanh&(W_{hh} h_{t-1} + W_{xh} x_t + b_h), \ o_t &= tanh&(W_{ho} h_t + b_o), @f}