[Pretrained Model] Add resize_position_embeddings (#13559)

* finish

* delete bogus file

* correct some stuff

* finish

* finish

tests/test_modeling_common.py

@@ -94,6 +94,7 @@ class ModelTesterMixin:
     test_torchscript = True
     test_pruning = True
     test_resize_embeddings = True
+    test_resize_position_embeddings = False
     test_head_masking = True
     test_missing_keys = True
     test_model_parallel = False
@@ -1067,6 +1068,85 @@ class ModelTesterMixin:
             hidden_states_with_chunk = model(**self._prepare_for_class(inputs_dict, model_class))[0]
             self.assertTrue(torch.allclose(hidden_states_no_chunk, hidden_states_with_chunk, atol=1e-3))
 
+    def test_resize_position_vector_embeddings(self):
+        if not self.test_resize_position_embeddings:
+            return
+
+        (
+            original_config,
+            inputs_dict,
+        ) = self.model_tester.prepare_config_and_inputs_for_common()
+
+        for model_class in self.all_model_classes:
+            config = copy.deepcopy(original_config)
+            model = model_class(config)
+            model.to(torch_device)
+
+            if self.model_tester.is_training is False:
+                model.eval()
+
+            max_position_embeddings = config.max_position_embeddings
+
+            # Retrieve the embeddings and clone theme
+            if model.config.is_encoder_decoder:
+                encoder_model_embed, decoder_model_embed = model.get_position_embeddings()
+                encoder_cloned_embeddings = encoder_model_embed.weight.clone()
+                decoder_cloned_embeddings = decoder_model_embed.weight.clone()
+            else:
+                model_embed = model.get_position_embeddings()
+                cloned_embeddings = model_embed.weight.clone()
+
+            # Check that resizing the position embeddings with a larger max_position_embeddings increases
+            # the model's postion embeddings size
+            model.resize_position_embeddings(max_position_embeddings + 10)
+            self.assertEqual(model.config.max_position_embeddings, max_position_embeddings + 10)
+
+            # Check that it actually resizes the embeddings matrix
+            if model.config.is_encoder_decoder:
+                encoder_model_embed, decoder_model_embed = model.get_position_embeddings()
+                self.assertEqual(encoder_model_embed.weight.shape[0], encoder_cloned_embeddings.shape[0] + 10)
+                self.assertEqual(decoder_model_embed.weight.shape[0], decoder_cloned_embeddings.shape[0] + 10)
+            else:
+                model_embed = model.get_position_embeddings()
+                self.assertEqual(model_embed.weight.shape[0], cloned_embeddings.shape[0] + 10)
+
+            # Check that the model can still do a forward pass successfully (every parameter should be resized)
+            model(**self._prepare_for_class(inputs_dict, model_class))
+
+            # Check that resizing the position embeddings with a smaller max_position_embeddings decreases
+            # the model's max_position_embeddings
+            model.resize_position_embeddings(max_position_embeddings - 5)
+            self.assertEqual(model.config.max_position_embeddings, max_position_embeddings - 5)
+
+            # Check that it actually resizes the embeddings matrix
+            if model.config.is_encoder_decoder:
+                encoder_model_embed, decoder_model_embed = model.get_position_embeddings()
+                self.assertEqual(encoder_model_embed.weight.shape[0], encoder_cloned_embeddings.shape[0] - 5)
+                self.assertEqual(decoder_model_embed.weight.shape[0], decoder_cloned_embeddings.shape[0] - 5)
+            else:
+                model_embed = model.get_position_embeddings()
+                self.assertEqual(model_embed.weight.shape[0], cloned_embeddings.shape[0] - 5)
+
+            # Check that the model can still do a forward pass successfully (every parameter should be resized)
+            model(**self._prepare_for_class(inputs_dict, model_class))
+
+            # Check that adding and removing tokens has not modified the first part of the embedding matrix.
+            models_equal = True
+
+            if model.config.is_encoder_decoder:
+                for p1, p2 in zip(encoder_cloned_embeddings, encoder_model_embed.weight):
+                    if p1.data.ne(p2.data).sum() > 0:
+                        models_equal = False
+                for p1, p2 in zip(decoder_cloned_embeddings, decoder_model_embed.weight):
+                    if p1.data.ne(p2.data).sum() > 0:
+                        models_equal = False
+            else:
+                for p1, p2 in zip(cloned_embeddings, model_embed.weight):
+                    if p1.data.ne(p2.data).sum() > 0:
+                        models_equal = False
+
+            self.assertTrue(models_equal)
+
     def test_resize_tokens_embeddings(self):
         (
             original_config,

tests/test_modeling_distilbert.py

@@ -214,6 +214,7 @@ class DistilBertModelTest(ModelTesterMixin, unittest.TestCase):
     test_torchscript = True
     test_resize_embeddings = True
     test_sequence_classification_problem_types = True
+    test_resize_position_embeddings = True
 
     def setUp(self):
         self.model_tester = DistilBertModelTester(self)

tests/test_modeling_pegasus.py

@@ -229,6 +229,7 @@ class PegasusModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCas
     all_model_classes = (PegasusModel, PegasusForConditionalGeneration) if is_torch_available() else ()
     all_generative_model_classes = (PegasusForConditionalGeneration,) if is_torch_available() else ()
     is_encoder_decoder = True
+    test_resize_position_embeddings = True
     test_pruning = False
     test_missing_keys = False
 
@@ -526,6 +527,7 @@ class PegasusStandaloneDecoderModelTester:
 class PegasusStandaloneDecoderModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
     all_model_classes = (PegasusDecoder, PegasusForCausalLM) if is_torch_available() else ()
     all_generative_model_classes = (PegasusForCausalLM,) if is_torch_available() else ()
+    test_resize_position_embeddings = True
     test_pruning = False
     is_encoder_decoder = False