clean code

src/llamafactory/chat/vllm_engine.py

@@ -1,12 +1,10 @@
 import uuid
 from typing import TYPE_CHECKING, AsyncGenerator, AsyncIterator, Dict, List, Optional, Sequence, Union
 
-from packaging import version
-
 from ..data import get_template_and_fix_tokenizer
 from ..extras.logging import get_logger
 from ..extras.misc import get_device_count
-from ..extras.packages import is_vllm_available, _get_package_version
+from ..extras.packages import is_vllm_available, is_vllm_version_greater_than_0_5
 from ..model import load_config, load_tokenizer
 from ..model.model_utils.visual import LlavaMultiModalProjectorForYiVLForVLLM
 from .base_engine import BaseEngine, Response
@@ -16,7 +14,7 @@ if is_vllm_available():
     from vllm import AsyncEngineArgs, AsyncLLMEngine, RequestOutput, SamplingParams
     from vllm.lora.request import LoRARequest
 
-    if _get_package_version("vllm") >= version.parse("0.5.0"):
+    if is_vllm_version_greater_than_0_5():
         from vllm.multimodal.image import ImagePixelData
     else:
         from vllm.sequence import MultiModalData
@@ -112,9 +110,9 @@ class VllmEngine(BaseEngine):
         if self.processor is not None and image is not None:  # add image features
             image_processor: "BaseImageProcessor" = getattr(self.processor, "image_processor")
             pixel_values = image_processor(image, return_tensors="pt")["pixel_values"]
-            if _get_package_version("vllm") >= version.parse("0.5.0"):
-                multi_modal_data = ImagePixelData(pixel_values)
-            else:
+            if is_vllm_version_greater_than_0_5():
+                multi_modal_data = ImagePixelData(image=pixel_values)
+            else:  # TODO: remove vllm 0.4.3 support
                 multi_modal_data = MultiModalData(type=MultiModalData.Type.IMAGE, data=pixel_values)
         else:
             multi_modal_data = None

src/llamafactory/extras/packages.py

@@ -1,5 +1,6 @@
 import importlib.metadata
 import importlib.util
+from functools import lru_cache
 from typing import TYPE_CHECKING
 
 from packaging import version
@@ -24,10 +25,6 @@ def is_fastapi_available():
     return _is_package_available("fastapi")
 
 
-def is_flash_attn2_available():
-    return _is_package_available("flash_attn") and _get_package_version("flash_attn") > version.parse("2.0.0")
-
-
 def is_galore_available():
     return _is_package_available("galore_torch")
 
@@ -36,18 +33,10 @@ def is_gradio_available():
     return _is_package_available("gradio")
 
 
-def is_jieba_available():
-    return _is_package_available("jieba")
-
-
 def is_matplotlib_available():
     return _is_package_available("matplotlib")
 
 
-def is_nltk_available():
-    return _is_package_available("nltk")
-
-
 def is_pillow_available():
     return _is_package_available("PIL")
 
@@ -60,10 +49,6 @@ def is_rouge_available():
     return _is_package_available("rouge_chinese")
 
 
-def is_sdpa_available():
-    return _get_package_version("torch") > version.parse("2.1.1")
-
-
 def is_starlette_available():
     return _is_package_available("sse_starlette")
 
@@ -74,3 +59,8 @@ def is_uvicorn_available():
 
 def is_vllm_available():
     return _is_package_available("vllm")
+
+
+@lru_cache
+def is_vllm_version_greater_than_0_5():
+    return _get_package_version("vllm") >= version.parse("0.5.0")

src/llamafactory/model/model_utils/attention.py

@@ -1,7 +1,8 @@
 from typing import TYPE_CHECKING
 
+from transformers.utils import is_flash_attn_2_available, is_torch_sdpa_available
+
 from ...extras.logging import get_logger
-from ...extras.packages import is_flash_attn2_available, is_sdpa_available
 
 
 if TYPE_CHECKING:
@@ -21,13 +22,13 @@ def configure_attn_implementation(config: "PretrainedConfig", model_args: "Model
         requested_attn_implementation = "eager"
 
     elif model_args.flash_attn == "sdpa":
-        if not is_sdpa_available():
+        if not is_torch_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():
+        if not is_flash_attn_2_available():
             logger.warning("FlashAttention-2 is not installed.")
             return
 

src/llamafactory/train/sft/metric.py

@@ -2,9 +2,10 @@ from dataclasses import dataclass
 from typing import TYPE_CHECKING, Dict, Sequence, Tuple, Union
 
 import numpy as np
+from transformers.utils import is_jieba_available, is_nltk_available
 
 from ...extras.constants import IGNORE_INDEX
-from ...extras.packages import is_jieba_available, is_nltk_available, is_rouge_available
+from ...extras.packages import is_rouge_available
 
 
 if TYPE_CHECKING: