Deprecate tflite, ort-training and bettertransformer (#2316)

* deprecate tflite

* bt and ort training

Author: IlyasMoutawwakil

optimum/bettertransformer/transformation.py

@@ -212,9 +212,7 @@ def transform(
             The converted model if the conversion has been successful.
         """
 
-        logger.warning(
-            "The class `optimum.bettertransformers.transformation.BetterTransformer` is deprecated and will be removed in optimum v2.0."
-        )
+        logger.warning("BetterTransformer is deprecated and will be removed in Optimum v2.0.")
 
         hf_config = model.config
         if hf_config.model_type in ["falcon", "gpt_bigcode", "llama", "whisper"]:

optimum/exporters/tflite/convert.py

@@ -67,7 +67,7 @@ def validate_model_outputs(
     """
     if not is_tf_available():
         raise ImportError(
-            "Cannot validate conversion because TensorFlow is not installed. " "Please install TensorFlow first."
+            "Cannot validate conversion because TensorFlow is not installed. Please install TensorFlow first."
         )
     import tensorflow as tf
 
@@ -128,7 +128,7 @@ def validate_model_outputs(
 
     if shape_failures:
         msg = "\n".join(f"- {t[0]}: got {t[1]} (reference) and {t[2]} (TFLite)" for t in shape_failures)
-        raise ShapeError("Output shapes do not match between reference model and the TFLite exported model:\n" "{msg}")
+        raise ShapeError("Output shapes do not match between reference model and the TFLite exported model:\n{msg}")
 
     if value_failures:
         msg = "\n".join(f"- {t[0]}: max diff = {t[1]}" for t in value_failures)
@@ -341,8 +341,11 @@ def export(
         `Tuple[List[str], List[str]]`: A tuple with an ordered list of the model's inputs, and the named inputs from
         the TFLite configuration.
     """
+
+    logger.warning("The TFLite exporter is deprecated and will be removed in Optimum v2.0.")
+
     if not is_tf_available():
-        raise ImportError("Cannot convert because TensorFlow is not installed. " "Please install TensorFlow first.")
+        raise ImportError("Cannot convert because TensorFlow is not installed. Please install TensorFlow first.")
     import tensorflow as tf
 
     output.parent.mkdir(parents=True, exist_ok=True)

optimum/onnxruntime/trainer.py

@@ -244,6 +244,8 @@ def __init__(
         optimizers: Tuple[torch.optim.Optimizer, torch.optim.lr_scheduler.LambdaLR] = (None, None),
         preprocess_logits_for_metrics: Optional[Callable[[torch.Tensor, torch.Tensor], torch.Tensor]] = None,
     ):
+        logger.warning("The ORTTrainer is deprecated and will be removed in Optimum v2.0.")
+
         super().__init__(
             model=model,
             args=args,
@@ -1048,10 +1050,10 @@ def create_optimizer(self):
                 for module in opt_model.modules():
                     if isinstance(module, nn.Embedding):
                         skipped += sum({p.data_ptr(): p.numel() for p in module.parameters()}.values())
-                        logger.info(f"skipped {module}: {skipped/2**20}M params")
+                        logger.info(f"skipped {module}: {skipped / 2**20}M params")
                         manager.register_module_override(module, "weight", {"optim_bits": 32})
                         logger.debug(f"bitsandbytes: will optimize {module} in fp32")
-                logger.info(f"skipped: {skipped/2**20}M params")
+                logger.info(f"skipped: {skipped / 2**20}M params")
 
         if is_sagemaker_mp_enabled():
             raise NotImplementedError(