attention_gru_cell.py 文件源码

def __call__(self, inputs, state, scope=None):
        """Attention GRU with nunits cells."""
        with vs.variable_scope(scope or "attention_gru_cell"):
            with vs.variable_scope("gates"):  # Reset gate and update gate.
                # We start with bias of 1.0 to not reset and not update.
                if inputs.get_shape()[-1] != self._num_units + 1:
                    raise ValueError("Input should be passed as word input concatenated with 1D attention on end axis")
                # extract input vector and attention
                inputs, g = array_ops.split(inputs,
                        num_or_size_splits=[self._num_units,1],
                        axis=1)
                r = _linear([inputs, state], self._num_units, True)
                r = sigmoid(r)
            with vs.variable_scope("candidate"):
                r = r*_linear(state, self._num_units, False)
            with vs.variable_scope("input"):
                x = _linear(inputs, self._num_units, True)
            h_hat = self._activation(r + x)

            new_h = (1 - g) * state + g * h_hat
        return new_h, new_h