@@ -164,36 +164,6 @@ def __init__(self,
164
164
attention_scores = all_attention_scores )
165
165
super ().__init__ (
166
166
inputs = self .inputs , outputs = outputs , ** kwargs )
167
- self ._config = dict (
168
- name = self .name ,
169
- word_vocab_size = word_vocab_size ,
170
- word_embed_size = word_embed_size ,
171
- type_vocab_size = type_vocab_size ,
172
- max_sequence_length = max_sequence_length ,
173
- num_blocks = num_blocks ,
174
- hidden_size = hidden_size ,
175
- num_attention_heads = num_attention_heads ,
176
- intermediate_size = intermediate_size ,
177
- intermediate_act_fn = intermediate_act_fn ,
178
- hidden_dropout_prob = hidden_dropout_prob ,
179
- attention_probs_dropout_prob = attention_probs_dropout_prob ,
180
- intra_bottleneck_size = intra_bottleneck_size ,
181
- initializer_range = initializer_range ,
182
- use_bottleneck_attention = use_bottleneck_attention ,
183
- key_query_shared_bottleneck = key_query_shared_bottleneck ,
184
- num_feedforward_networks = num_feedforward_networks ,
185
- normalization_type = normalization_type ,
186
- classifier_activation = classifier_activation ,
187
- input_mask_dtype = input_mask_dtype ,
188
- ** kwargs ,
189
- )
190
-
191
- def get_config (self ):
192
- return dict (self ._config )
193
-
194
- @classmethod
195
- def from_config (cls , config ):
196
- return cls (** config )
197
167
198
168
def get_embedding_table (self ):
199
169
return self .embedding_layer .word_embedding .embeddings
0 commit comments