process_builders.py 文件源码

def build_step(self, signals):
        input = signals.gather(self.input_data)
        input = tf.reshape(input, (self.n_ops, -1))

        state = signals.gather(self.state_sig)

        # compute output
        if self.C is None:
            output = tf.zeros_like(input)
        else:
            output = state * self.C
            output = tf.reshape(
                output,
                (self.n_ops, -1, signals.minibatch_size * self.signal_d))
            output = tf.reduce_sum(output, axis=1)

        if self.D is not None:
            output += self.D * input

        signals.scatter(self.output_data, output)

        # update state
        r = gen_sparse_ops._sparse_tensor_dense_mat_mul(
            self.A_indices, self.A, self.A_shape, state)

        with tf.control_dependencies([output]):
            state = r + tf.scatter_nd(self.offsets, input,
                                      self.state_sig.shape)
            # TODO: tensorflow does not yet support sparse_tensor_dense_add
            # on the GPU
            # state = gen_sparse_ops._sparse_tensor_dense_add(
            #     self.offsets, input, self.state_sig.shape, r)
        state.set_shape(self.state_sig.shape)

        signals.mark_gather(self.input_data)
        signals.mark_gather(self.state_sig)
        signals.scatter(self.state_sig, state)