recurrent_layer.py 文件源码

def sequence_iteration(self, in_seq, mask, use_dropout,dropout_value=1):

        in_seq_d = T.switch(use_dropout,
                             (in_seq *
                              self.trng.binomial(in_seq.shape,
                                            p=dropout_value, n=1,
                                            dtype=in_seq.dtype)),
                             in_seq)

        rz_in_seq =  T.add( T.dot(in_seq_d, self.weights[0]) , self.weights[1] )

        out_seq, updates = theano.scan(
                                        fn=self.t_forward_step,
                                        sequences=[mask, rz_in_seq],  # in_seq_d],
                                        outputs_info=[self.t_ol_t00],
                                        non_sequences=[i for i in self.weights][2:] + [self.t_n_out],
                                        go_backwards = self.go_backwards,
                                        truncate_gradient=-1,
                                        #n_steps=50,
                                        strict=True,
                                        allow_gc=False,
                                        )
        return out_seq