:param d_model: :param d_k: :param d_v: :param sequence_length: :param h: :param batch_size: :param embedded_words: shape:[batch_size*sequence_length,embed_size]
(self,d_model,d_k,d_v,sequence_length,h,batch_size,num_layer,Q,K_s,type='encoder',mask=None,dropout_keep_prob=None,use_residual_conn=True)
| 12 | import time |
| 13 | class Encoder(BaseClass): |
| 14 | def __init__(self,d_model,d_k,d_v,sequence_length,h,batch_size,num_layer,Q,K_s,type='encoder',mask=None,dropout_keep_prob=None,use_residual_conn=True): |
| 15 | """ |
| 16 | :param d_model: |
| 17 | :param d_k: |
| 18 | :param d_v: |
| 19 | :param sequence_length: |
| 20 | :param h: |
| 21 | :param batch_size: |
| 22 | :param embedded_words: shape:[batch_size*sequence_length,embed_size] |
| 23 | """ |
| 24 | super(Encoder, self).__init__(d_model,d_k,d_v,sequence_length,h,batch_size,num_layer=num_layer) |
| 25 | self.Q=Q |
| 26 | self.K_s=K_s |
| 27 | self.type=type |
| 28 | self.mask=mask |
| 29 | self.initializer = tf.random_normal_initializer(stddev=0.1) |
| 30 | self.dropout_keep_prob=dropout_keep_prob |
| 31 | self.use_residual_conn=use_residual_conn |
| 32 | |
| 33 | def encoder_fn(self): |
| 34 | start = time.time() |
nothing calls this directly
no outgoing calls
no test coverage detected