EUNN.py 文件源码

def __call__(self, inputs, state, scope=None):
        with vs.variable_scope(scope or "eunn_cell"):

            state = _eunn_loop(state, self._capacity, self.diag_vec, self.off_vec, self.diag, self._fft)

            input_matrix_init = init_ops.random_uniform_initializer(-0.01, 0.01)
            if self._comp:
                input_matrix_re = vs.get_variable("U_re", [inputs.get_shape()[-1], self._hidden_size], initializer=input_matrix_init)
                input_matrix_im = vs.get_variable("U_im", [inputs.get_shape()[-1], self._hidden_size], initializer=input_matrix_init)
                inputs_re = math_ops.matmul(inputs, input_matrix_re)
                inputs_im = math_ops.matmul(inputs, input_matrix_im)
                inputs = math_ops.complex(inputs_re, inputs_im)
            else:
                input_matrix = vs.get_variable("U", [inputs.get_shape()[-1], self._hidden_size], initializer=input_matrix_init)
                inputs = math_ops.matmul(inputs, input_matrix)

            bias = vs.get_variable("modReLUBias", [self._hidden_size], initializer=init_ops.constant_initializer())
            output = self._activation((inputs + state), bias, self._comp)

        return output, output