Set missing seq_length variable when using inputs_embeds with ALBERT & Remove code duplication (#13152)

* Set seq_length variable when using inputs_embeds

* remove code duplication

src/transformers/models/albert/modeling_albert.py

@@ -693,12 +693,12 @@ class AlbertModel(AlbertPreTrainedModel):
             raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time")
         elif input_ids is not None:
             input_shape = input_ids.size()
-            batch_size, seq_length = input_shape
         elif inputs_embeds is not None:
             input_shape = inputs_embeds.size()[:-1]
         else:
             raise ValueError("You have to specify either input_ids or inputs_embeds")
 
+        batch_size, seq_length = input_shape
         device = input_ids.device if input_ids is not None else inputs_embeds.device
 
         if attention_mask is None:

src/transformers/models/bert/modeling_bert.py

@@ -936,13 +936,12 @@ class BertModel(BertPreTrainedModel):
             raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time")
         elif input_ids is not None:
             input_shape = input_ids.size()
-            batch_size, seq_length = input_shape
         elif inputs_embeds is not None:
             input_shape = inputs_embeds.size()[:-1]
-            batch_size, seq_length = input_shape
         else:
             raise ValueError("You have to specify either input_ids or inputs_embeds")
 
+        batch_size, seq_length = input_shape
         device = input_ids.device if input_ids is not None else inputs_embeds.device
 
         # past_key_values_length

src/transformers/models/bert_generation/modeling_bert_generation.py

@@ -353,13 +353,12 @@ class BertGenerationEncoder(BertGenerationPreTrainedModel):
             raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time")
         elif input_ids is not None:
             input_shape = input_ids.size()
-            batch_size, seq_length = input_shape
         elif inputs_embeds is not None:
             input_shape = inputs_embeds.size()[:-1]
-            batch_size, seq_length = input_shape
         else:
             raise ValueError("You have to specify either input_ids or inputs_embeds")
 
+        batch_size, seq_length = input_shape
         device = input_ids.device if input_ids is not None else inputs_embeds.device
 
         # past_key_values_length

src/transformers/models/big_bird/modeling_big_bird.py

@@ -2024,13 +2024,12 @@ class BigBirdModel(BigBirdPreTrainedModel):
             raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time")
         elif input_ids is not None:
             input_shape = input_ids.size()
-            batch_size, seq_length = input_shape
         elif inputs_embeds is not None:
             input_shape = inputs_embeds.size()[:-1]
-            batch_size, seq_length = input_shape
         else:
             raise ValueError("You have to specify either input_ids or inputs_embeds")
 
+        batch_size, seq_length = input_shape
         device = input_ids.device if input_ids is not None else inputs_embeds.device
 
         # past_key_values_length

src/transformers/models/canine/modeling_canine.py

@@ -1119,13 +1119,12 @@ class CanineModel(CaninePreTrainedModel):
             raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time")
         elif input_ids is not None:
             input_shape = input_ids.size()
-            batch_size, seq_length = input_shape
         elif inputs_embeds is not None:
             input_shape = inputs_embeds.size()[:-1]
-            batch_size, seq_length = input_shape
         else:
             raise ValueError("You have to specify either input_ids or inputs_embeds")
 
+        batch_size, seq_length = input_shape
         device = input_ids.device if input_ids is not None else inputs_embeds.device
 
         if attention_mask is None:

src/transformers/models/ibert/modeling_ibert.py

@@ -803,13 +803,12 @@ class IBertModel(IBertPreTrainedModel):
             raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time")
         elif input_ids is not None:
             input_shape = input_ids.size()
-            batch_size, seq_length = input_shape
         elif inputs_embeds is not None:
             input_shape = inputs_embeds.size()[:-1]
-            batch_size, seq_length = input_shape
         else:
             raise ValueError("You have to specify either input_ids or inputs_embeds")
 
+        batch_size, seq_length = input_shape
         device = input_ids.device if input_ids is not None else inputs_embeds.device
 
         if attention_mask is None:

src/transformers/models/luke/modeling_luke.py

@@ -887,13 +887,12 @@ class LukeModel(LukePreTrainedModel):
             raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time")
         elif input_ids is not None:
             input_shape = input_ids.size()
-            batch_size, seq_length = input_shape
         elif inputs_embeds is not None:
             input_shape = inputs_embeds.size()[:-1]
-            batch_size, seq_length = input_shape
         else:
             raise ValueError("You have to specify either input_ids or inputs_embeds")
 
+        batch_size, seq_length = input_shape
         device = input_ids.device if input_ids is not None else inputs_embeds.device
 
         if attention_mask is None:

src/transformers/models/megatron_bert/modeling_megatron_bert.py

@@ -924,13 +924,12 @@ class MegatronBertModel(MegatronBertPreTrainedModel):
             raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time")
         elif input_ids is not None:
             input_shape = input_ids.size()
-            batch_size, seq_length = input_shape
         elif inputs_embeds is not None:
             input_shape = inputs_embeds.size()[:-1]
-            batch_size, seq_length = input_shape
         else:
             raise ValueError("You have to specify either input_ids or inputs_embeds")
 
+        batch_size, seq_length = input_shape
         device = input_ids.device if input_ids is not None else inputs_embeds.device
 
         # past_key_values_length

src/transformers/models/rembert/modeling_rembert.py

@@ -829,13 +829,12 @@ class RemBertModel(RemBertPreTrainedModel):
             raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time")
         elif input_ids is not None:
             input_shape = input_ids.size()
-            batch_size, seq_length = input_shape
         elif inputs_embeds is not None:
             input_shape = inputs_embeds.size()[:-1]
-            batch_size, seq_length = input_shape
         else:
             raise ValueError("You have to specify either input_ids or inputs_embeds")
 
+        batch_size, seq_length = input_shape
         device = input_ids.device if input_ids is not None else inputs_embeds.device
 
         # past_key_values_length

src/transformers/models/roberta/modeling_roberta.py

@@ -789,13 +789,12 @@ class RobertaModel(RobertaPreTrainedModel):
             raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time")
         elif input_ids is not None:
             input_shape = input_ids.size()
-            batch_size, seq_length = input_shape
         elif inputs_embeds is not None:
             input_shape = inputs_embeds.size()[:-1]
-            batch_size, seq_length = input_shape
         else:
             raise ValueError("You have to specify either input_ids or inputs_embeds")
 
+        batch_size, seq_length = input_shape
         device = input_ids.device if input_ids is not None else inputs_embeds.device
 
         # past_key_values_length

src/transformers/models/roformer/modeling_roformer.py

@@ -888,13 +888,12 @@ class RoFormerModel(RoFormerPreTrainedModel):
             raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time")
         elif input_ids is not None:
             input_shape = input_ids.size()
-            batch_size, seq_length = input_shape
         elif inputs_embeds is not None:
             input_shape = inputs_embeds.size()[:-1]
-            batch_size, seq_length = input_shape
         else:
             raise ValueError("You have to specify either input_ids or inputs_embeds")
 
+        batch_size, seq_length = input_shape
         device = input_ids.device if input_ids is not None else inputs_embeds.device
 
         # past_key_values_length

src/transformers/models/splinter/modeling_splinter.py

@@ -683,13 +683,12 @@ class SplinterModel(SplinterPreTrainedModel):
             raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time")
         elif input_ids is not None:
             input_shape = input_ids.size()
-            batch_size, seq_length = input_shape
         elif inputs_embeds is not None:
             input_shape = inputs_embeds.size()[:-1]
-            batch_size, seq_length = input_shape
         else:
             raise ValueError("You have to specify either input_ids or inputs_embeds")
 
+        batch_size, seq_length = input_shape
         device = input_ids.device if input_ids is not None else inputs_embeds.device
 
         # past_key_values_length

src/transformers/models/visual_bert/modeling_visual_bert.py

@@ -767,10 +767,8 @@ class VisualBertModel(VisualBertPreTrainedModel):
             raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time")
         elif input_ids is not None:
             input_shape = input_ids.size()
-            batch_size, seq_length = input_shape
         elif inputs_embeds is not None:
             input_shape = inputs_embeds.size()[:-1]
-            batch_size, seq_length = input_shape
         else:
             raise ValueError("You have to specify either input_ids or inputs_embeds")
 
@@ -779,6 +777,7 @@ class VisualBertModel(VisualBertPreTrainedModel):
                 f"`visual_embeds` can not be of type {type(visual_embeds)} when using a VisualBert Model."
             )
 
+        batch_size, seq_length = input_shape
         device = input_ids.device if input_ids is not None else inputs_embeds.device
 
         visual_input_shape = visual_embeds.size()[:-1]

templates/adding_a_new_model/cookiecutter-template-{{cookiecutter.modelname}}/modeling_{{cookiecutter.lowercase_modelname}}.py

@@ -846,13 +846,12 @@ class {{cookiecutter.camelcase_modelname}}Model({{cookiecutter.camelcase_modelna
             raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time")
         elif input_ids is not None:
             input_shape = input_ids.size()
-            batch_size, seq_length = input_shape
         elif inputs_embeds is not None:
             input_shape = inputs_embeds.size()[:-1]
-            batch_size, seq_length = input_shape
         else:
             raise ValueError("You have to specify either input_ids or inputs_embeds")
 
+        batch_size, seq_length = input_shape
         device = input_ids.device if input_ids is not None else inputs_embeds.device
 
         # past_key_values_length