[TF models] Common attributes as per #1721

transformers/modeling_tf_gpt2.py

@@ -219,6 +219,9 @@ class TFGPT2MainLayer(tf.keras.layers.Layer):
                           name='h_._{}'.format(i)) for i in range(config.n_layer)]
         self.ln_f = tf.keras.layers.LayerNormalization(epsilon=config.layer_norm_epsilon, name='ln_f')
 
+    def get_input_embeddings(self):
+        return self.wte
+
     def _resize_token_embeddings(self, new_num_tokens):
         raise NotImplementedError
 
@@ -490,6 +493,9 @@ class TFGPT2LMHeadModel(TFGPT2PreTrainedModel):
         super(TFGPT2LMHeadModel, self).__init__(config, *inputs, **kwargs)
         self.transformer = TFGPT2MainLayer(config, name='transformer')
 
+    def get_output_embeddings(self):
+        return self.transformer.wte
+
     def call(self, inputs, **kwargs):
         transformer_outputs = self.transformer(inputs, **kwargs)
         hidden_states = transformer_outputs[0]
@@ -560,6 +566,9 @@ class TFGPT2DoubleHeadsModel(TFGPT2PreTrainedModel):
         self.transformer = TFGPT2MainLayer(config, name='transformer')
         self.multiple_choice_head = TFSequenceSummary(config, initializer_range=config.initializer_range, name='multiple_choice_head')
 
+    def get_output_embeddings(self):
+        return self.transformer.wte
+
     def call(self, inputs, past=None, attention_mask=None, token_type_ids=None, position_ids=None, head_mask=None, mc_token_ids=None, training=False):
         if isinstance(inputs, (tuple, list)):
             input_ids = inputs[0]