Add validation for maximum sequence length in modeling_whisper.py (#33196)

* Add validation for maximum sequence length in modeling_whisper.py

Added a validation check to ensure that the sequence length of labels does not exceed the maximum allowed length of 448 tokens. If the sequence length exceeds this limit, a ValueError is raised with a descriptive error message.

This change prevents the model from encountering errors or unexpected behavior due to excessively long sequences during training or fine-tuning, ensuring consistent input dimensions and improving overall robustness.

* Change exception message in src/transformers/models/whisper/modeling_whisper.py

The exception message is for whisper's label's sequence max length.

Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com>

* Change 448 to config.max_target_positions in src/transformers/models/whisper/modeling_whisper.py

It's for whisper's config.max_target_positions.

Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com>

* Change method's documentation in src/transformers/models/whisper/modeling_whisper.py

* Add test for maximum label's sequence length in test_modeling_whisper.py

* Add self to modeling_whisper.py

* Update test_modeling_whisper.py with respect to automatic validations

* Update modeling_whisper.py with respect to ci/circleci: check_code_quality

* Update test_modeling_whisper.py with respect to ci/circleci: check_code_quality

* Update test_modeling_whisper.py with respect to ci/circleci: tests_generate

* Update test_modeling_whisper.py with respect to ci/circleci: tests_generate

* Update test_modeling_whisper.py with respect to ci/circleci: check_code_quality

* Separate test_labels_sequence_max_length tests in test_modeling_whisper.py

* Update test_modeling_whisper.py with respect to ci/circleci: check_code_quality

* Remove assert from test_modeling_whisper.py

* Add max_target_positions to WhisperModelTester in test_modeling_whisper.py

* Update test_modeling_whisper.py with respect to ci/circleci: check_code_quality

* Update test_modeling_whisper.py with respect to ci/circleci: tests_generate

* Update test_modeling_whisper.py

* Change test_labels_sequence_max_length_error_after_changing_config in test_modeling_whisper.py

* Change self.config.max_target_positions to self.max_target_positions modeling_whisper.py

* Add new tests in test_modeling_whisper.py

* Update test_modeling_whisper.py

---------

Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com>

tests/models/whisper/test_modeling_whisper.py

@@ -1676,6 +1676,63 @@ class WhisperModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMi
                     past_key_values=past_key_values,
                 )
 
+    def test_labels_sequence_max_length_correct(self):
+        config, input_dict = self.model_tester.prepare_config_and_inputs_for_common()
+
+        for model_class in self.all_generative_model_classes:
+            input_features = input_dict["input_features"]
+
+            labels_length = config.max_target_positions
+            labels = torch.ones(1, labels_length, dtype=torch.int64)
+
+            model = model_class(config)
+            model(input_features=input_features, labels=labels)
+
+    def test_labels_sequence_max_length_correct_after_changing_config(self):
+        config, input_dict = self.model_tester.prepare_config_and_inputs_for_common()
+
+        for model_class in self.all_generative_model_classes:
+            input_features = input_dict["input_features"]
+
+            config.max_target_positions += 100
+
+            labels_length = config.max_target_positions
+            labels = torch.ones(1, labels_length, dtype=torch.int64)
+
+            model = model_class(config)
+            model(input_features=input_features, labels=labels)
+
+    def test_labels_sequence_max_length_error(self):
+        config, input_dict = self.model_tester.prepare_config_and_inputs_for_common()
+
+        for model_class in self.all_generative_model_classes:
+            input_features = input_dict["input_features"]
+
+            labels_length = config.max_target_positions + 1
+            labels = torch.ones(1, labels_length, dtype=torch.int64)
+
+            model = model_class(config)
+            with self.assertRaises(ValueError):
+                model(input_features=input_features, labels=labels)
+
+    def test_labels_sequence_max_length_error_after_changing_config(self):
+        config, input_dict = self.model_tester.prepare_config_and_inputs_for_common()
+
+        for model_class in self.all_generative_model_classes:
+            model = model_class(config)
+            input_features = input_dict["input_features"]
+
+            labels_length = config.max_target_positions + 1
+            labels = torch.ones(1, labels_length, dtype=torch.int64)
+
+            new_max_length = config.max_target_positions + 100
+            model.config.max_length = new_max_length
+            model.generation_config.max_length = new_max_length
+            config.max_target_positions = new_max_length
+
+            with self.assertRaises(ValueError):
+                model(input_features=input_features, labels=labels)
+
 
 @require_torch
 @require_torchaudio