examples/attention_models/baseline_model.py
def _glimpse_network(self, x_t, l_p):
        """
        Parameters:
            x_t - 28x28 image
            l_p - 2x1 focus vector
        Returns:
            4x12 matrix
        """
        sensor_output = self._refined_glimpse_sensor(x_t, l_p)
        sensor_output = T.flatten(sensor_output)
        h_g = self._relu(T.dot(sensor_output, self.W_g0))
        h_l = self._relu(T.dot(l_p, self.W_g1))
        g = self._relu(T.dot(h_g, self.W_g2_hg) + T.dot(h_l, self.W_g2_hl))
        return g
def _glimpse_network(self, x_t, l_p):
        """
        Parameters:
            x_t - 28x28 image
            l_p - 2x1 focus vector
        Returns:
            4x12 matrix
        """
        sensor_output = self._refined_glimpse_sensor(x_t, l_p)
        sensor_output = T.flatten(sensor_output)
        h_g = self._relu(T.dot(sensor_output, self.W_g0))
        h_l = self._relu(T.dot(l_p, self.W_g1))
        g = self._relu(T.dot(h_g, self.W_g2_hg) + T.dot(h_l, self.W_g2_hl))
        return g
Parameters:
            x_t - 28x28 image
            l_p - 2x1 focus vector
        Returns:
            4x12 matrix