inhibit copying base model dependencies for summ, and translation (#3285)

* inhibit copying base model dependencies for summ, and translation

* comments fix

---------

Co-authored-by: Anubha Jain <anubhajain@microsoft.com>

assets/training/finetune_acft_hf_nlp/src/model_converter/model_converter_adapters.py

@@ -20,7 +20,7 @@ from azureml.acft.common_components.utils.mlflow_utils import update_acft_metada
 
 from azureml.acft.contrib.hf.nlp.utils.common_utils import deep_update
 from azureml.acft.contrib.hf.nlp.constants.constants import (
-    MLFlowHFFlavourConstants, MLFlowHFFlavourTasks, SaveFileConstants, HfModelTypes
+    MLFlowHFFlavourConstants, MLFlowHFFlavourTasks, SaveFileConstants, HfModelTypes, Tasks
 )
 
 import mlflow
@@ -269,10 +269,10 @@ class Pytorch_to_OSS_MlFlow_ModelConverter(ModelConverter, PyTorch_to_MlFlow_Mod
                         yaml.safe_dump(conda_dict, f)
                     logger.info("Updated conda.yaml file")
 
-    def is_t5_text_classification_finetune(self, model_type) -> bool:
-        """Check for t5 text-classification."""
-        return self.mlflow_task_type == MLFlowHFFlavourTasks.SINGLE_LABEL_CLASSIFICATION and \
-            model_type == HfModelTypes.T5
+    def is_t5_finetune(self, model_type) -> bool:
+        """Check for t5 text-classification, translation, summarization."""
+        return self.component_args.task_name in [Tasks.SINGLE_LABEL_CLASSIFICATION, Tasks.TRANSLATION,
+                                                 Tasks.SUMMARIZATION] and model_type == HfModelTypes.T5
 
     def convert_model(self) -> None:
         """Convert pytorch model to oss mlflow model."""
@@ -282,9 +282,9 @@ class Pytorch_to_OSS_MlFlow_ModelConverter(ModelConverter, PyTorch_to_MlFlow_Mod
         self.set_mlflow_model_parameters(model)
 
         # Temp Fix:
-        # specific check for t5 text-classification so that base model dependencies doesn't get pass
-        # and use transformers version 4.40.0 from infer dependencies
-        if not self.is_t5_text_classification_finetune(model.config.model_type):
+        # specific check for t5 text-classification, translation, summarization so that base model
+        # dependencies doesn't get pass and use transformers version 4.44.0 from infer dependencies
+        if not self.is_t5_finetune(model.config.model_type):
             conda_file_path = Path(self.ft_pytorch_model_path, MLFlowHFFlavourConstants.CONDA_YAML_FILE)
             if conda_file_path.is_file():
                 self.mlflow_save_model_kwargs.update({"conda_env": str(conda_file_path)})
@@ -316,8 +316,8 @@ class Pytorch_to_OSS_MlFlow_ModelConverter(ModelConverter, PyTorch_to_MlFlow_Mod
         self.add_model_signature()
         self.copy_finetune_config(self.ft_pytorch_model_path, self.mlflow_model_save_path)
 
-        # Temp fix for t5 text-classification
-        if self.is_t5_text_classification_finetune(model.config.model_type):
+        # Temp fix for t5 text-classification, translation, summarization
+        if self.is_t5_finetune(model.config.model_type):
             self.remove_unwanted_packages(self.mlflow_model_save_path)
 
         logger.info("Saved MLFlow model using OSS flavour.")