chore: import upstream snapshot with attribution

swift/loss/base.py

@@ -0,0 +1,53 @@
+# Copyright (c) ModelScope Contributors. All rights reserved.
+import torch
+from abc import ABC, abstractmethod
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from swift.trainers import Trainer, TrainingArguments
+
+
+class BaseLoss(ABC):
+    """Abstract base class for custom loss functions.
+
+    This class provides a common interface for implementing custom loss functions
+    that can be integrated with the ms-swift training framework. All custom loss
+    implementations should inherit from this class and implement the __call__ method.
+
+    Attributes:
+        args (TrainingArguments): Training configuration and hyperparameters.
+        trainer (Trainer): Reference to the trainer instance for accessing model
+            and training state.
+    """
+
+    def __init__(self, args: 'TrainingArguments', trainer: 'Trainer'):
+        """Initialize the loss function with training arguments and trainer.
+
+        Args:
+            args (TrainingArguments): Training configuration and hyperparameters.
+            trainer (Trainer): Reference to the trainer instance.
+        """
+        self.args = args
+        self.trainer = trainer
+        mro_class_names = [cls.__name__ for cls in trainer.__class__.__mro__]
+        self.is_megatron = 'BaseMegatronTrainer' in mro_class_names
+
+    @abstractmethod
+    def __call__(self, outputs, labels, *, num_items_in_batch=None, loss_scale=None, **kwargs) -> torch.Tensor:
+        """Calculate the loss value.
+
+        This method must be implemented by all subclasses to define the specific
+        loss calculation logic.
+
+        Args:
+            outputs: Model outputs.
+            labels: Ground truth labels or targets.
+            num_items_in_batch (int, optional): Number of items (tokens) in the current batch,
+                Defaults to None.
+            loss_scale (float, optional): Scaling factor to apply to the loss value.
+                Defaults to None.
+
+        Returns:
+            torch.Tensor: A scalar tensor representing the computed loss value.
+        """
+        pass