def run_model_pipeline_tests(self, task, repo_name, model_architecture, tokenizer_names, processor_names, commit):
        """Run pipeline tests for a specific `task` with the give model class and tokenizer/processor class names

        Args:
            task (`str`):
                A task name. This should be a key in the mapping `pipeline_test_mapping`.
            repo_name (`str`):
                A model repository id on the Hub.
            model_architecture (`type`):
                A subclass of `PretrainedModel` or `PretrainedModel`.
            tokenizer_names (`List[str]`):
                A list of names of a subclasses of `PreTrainedTokenizerFast` or `PreTrainedTokenizer`.
            processor_names (`List[str]`):
                A list of names of subclasses of `BaseImageProcessor` or `FeatureExtractionMixin`.
        """
        # Get an instance of the corresponding class `XXXPipelineTests` in order to use `get_test_pipeline` and
        # `run_pipeline_test`.
        pipeline_test_class_name = pipeline_test_mapping[task]["test"].__name__

        for tokenizer_name in tokenizer_names:
            for processor_name in processor_names:
                if self.is_pipeline_test_to_skip(
                    pipeline_test_class_name,
                    model_architecture.config_class,
                    model_architecture,
                    tokenizer_name,
                    processor_name,
                ):
                    logger.warning(
                        f"{self.__class__.__name__}::test_pipeline_{task.replace('-', '_')} is skipped: test is "
                        f"currently known to fail for: model `{model_architecture.__name__}` | tokenizer "
                        f"`{tokenizer_name}` | processor `{processor_name}`."
                    )
                    continue
                self.run_pipeline_test(task, repo_name, model_architecture, tokenizer_name, processor_name, commit)
Run pipeline tests for a specific `task` with the give model class and tokenizer/processor class names

        Args:
            task (`str`):
                A task name. This should be a key in the mapping `pipeline_test_mapping`.
            repo_name (`str`):
                A model repository id on the Hub.
            model_architecture (`type`):
                A subclass of `PretrainedModel` or `PretrainedModel`.
            tokenizer_names (`List[str]`):
                A list of names of a subclasses of `PreTrainedTokenizerFast` or `PreTrainedTokenizer`.
            processor_names (`List[str]`):
                A list of names of subclasses of `BaseImageProcessor` or `FeatureExtractionMixin`.
        
dpkd/transformers/tests/test_pipeline_mixin.py