refactor patcher

Former-commit-id: 263cfe1294f5c3188f5e8d65791f35ee0d87315a

src/llmtuner/model/utils/attention.py

@@ -0,0 +1,55 @@
+from typing import TYPE_CHECKING
+
+from ...extras.logging import get_logger
+from ...extras.packages import is_flash_attn2_available, is_sdpa_available
+
+
+if TYPE_CHECKING:
+    from transformers import PretrainedConfig
+
+    from ...hparams import ModelArguments
+
+
+logger = get_logger(__name__)
+
+
+def configure_attn_implementation(config: "PretrainedConfig", model_args: "ModelArguments") -> None:
+    if model_args.flash_attn == "auto":
+        return
+
+    elif model_args.flash_attn == "off":
+        requested_attn_implementation = "eager"
+
+    elif model_args.flash_attn == "sdpa":
+        if not is_sdpa_available():
+            logger.warning("Torch>=2.1.1 is required for SDPA attention.")
+            return
+
+        requested_attn_implementation = "sdpa"
+    elif model_args.flash_attn == "fa2":
+        if not is_flash_attn2_available():
+            logger.warning("FlashAttention-2 is not installed.")
+            return
+
+        requested_attn_implementation = "flash_attention_2"
+    else:
+        raise NotImplementedError("Unknown attention type: {}".format(model_args.flash_attn))
+
+    if getattr(config, "model_type", None) == "internlm2":  # special case for custom models
+        setattr(config, "attn_implementation", requested_attn_implementation)
+    else:
+        setattr(config, "_attn_implementation", requested_attn_implementation)
+
+
+def print_attn_implementation(config: "PretrainedConfig") -> None:
+    if getattr(config, "model_type", None) == "internlm2":  # special case for custom models
+        attn_implementation = getattr(config, "attn_implementation", None)
+    else:
+        attn_implementation = getattr(config, "_attn_implementation", None)
+
+    if attn_implementation == "flash_attention_2":
+        logger.info("Using FlashAttention-2 for faster training and inference.")
+    elif attn_implementation == "sdpa":
+        logger.info("Using torch SDPA for faster training and inference.")
+    else:
+        logger.info("Using vanilla Attention implementation.")