Sync from v0.13

vllm/lora/layers/base.py

@@ -0,0 +1,66 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+from typing import TYPE_CHECKING
+
+import torch
+import torch.nn as nn
+from transformers import PretrainedConfig
+
+from vllm.config.lora import LoRAConfig
+
+if TYPE_CHECKING:
+    from vllm.lora.punica_wrapper import PunicaWrapperBase
+
+
+class BaseLayerWithLoRA(nn.Module):
+    def slice_lora_a(
+        self, lora_a: torch.Tensor | list[torch.Tensor | None]
+    ) -> torch.Tensor | list[torch.Tensor | None]:
+        """Slice lora a if splitting for tensor parallelism."""
+        ...
+
+    def slice_lora_b(
+        self, lora_b: torch.Tensor | list[torch.Tensor | None]
+    ) -> torch.Tensor | list[torch.Tensor | None]:
+        """Slice lora b if splitting with tensor parallelism."""
+        ...
+
+    def create_lora_weights(
+        self,
+        max_loras: int,
+        lora_config: LoRAConfig,
+        model_config: PretrainedConfig | None = None,
+    ) -> None:
+        """Initializes lora matrices."""
+        ...
+
+    def reset_lora(self, index: int):
+        """Resets the lora weights at index back to 0."""
+        ...
+
+    def set_lora(
+        self,
+        index: int,
+        lora_a: torch.Tensor | list[torch.Tensor],
+        lora_b: torch.Tensor | list[torch.Tensor],
+    ):
+        """Overwrites lora tensors at index."""
+        ...
+
+    def set_mapping(
+        self,
+        punica_wrapper,
+    ):
+        self.punica_wrapper: PunicaWrapperBase = punica_wrapper
+
+    @classmethod
+    def can_replace_layer(
+        cls,
+        source_layer: nn.Module,
+        lora_config: LoRAConfig,
+        packed_modules_list: list,
+        model_config: PretrainedConfig | None = None,
+    ) -> bool:
+        """Returns True if the layer can be replaced by this LoRA layer."""
+        raise NotImplementedError