Replace {func} with mkdocs style links (#18610)

Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>

vllm/model_executor/models/llava_next.py

@@ -540,7 +540,7 @@ class LlavaNextForConditionalGeneration(nn.Module, SupportsMultiModal,
         Unlike in LLaVA-1.5, the number of image tokens inputted to the language
         model depends on the original size of the input image. Including the
         original image token in the input, the required number of image tokens
-        is given by {func}`get_llava_next_image_feature_size`.
+        is given by [get_llava_next_image_feature_size][].
 
         This way, the `positions` and `attn_metadata` are consistent
         with the `input_ids`.

vllm/multimodal/processing.py

@@ -387,7 +387,7 @@ _M = TypeVar("_M", bound=Union[_HasModalityAttr, _HasModalityProp])
 
 
 def full_groupby_modality(values: Iterable[_M]) -> ItemsView[str, list[_M]]:
-    """Convenience function to apply {func}`full_groupby` based on modality."""
+    """Convenience function to apply [full_groupby][] based on modality."""
     return full_groupby(values, key=lambda x: x.modality)
 
 

vllm/platforms/interface.py

@@ -157,7 +157,7 @@ class Platform:
         return self._enum == PlatformEnum.OOT
 
     def is_cuda_alike(self) -> bool:
-        """Stateless version of {func}`torch.cuda.is_available`."""
+        """Stateless version of [torch.cuda.is_available][]."""
         return self._enum in (PlatformEnum.CUDA, PlatformEnum.ROCM)
 
     def is_sleep_mode_available(self) -> bool:
@@ -194,7 +194,7 @@ class Platform:
         cls,
         device_id: int = 0,
     ) -> Optional[DeviceCapability]:
-        """Stateless version of {func}`torch.cuda.get_device_capability`."""
+        """Stateless version of [torch.cuda.get_device_capability][]."""
         return None
 
     @classmethod

vllm/sequence.py

@@ -27,7 +27,7 @@ VLLM_INVALID_TOKEN_ID = -1
 
 
 def array_full(token_id: int, count: int):
-    """{class}`array` equivalent of {func}`numpy.full`."""
+    """{class}`array` equivalent of [numpy.full][]."""
     return array(VLLM_TOKEN_ID_ARRAY_TYPE, [token_id]) * count
 
 

vllm/v1/worker/utils.py

@@ -66,7 +66,7 @@ def gather_mm_placeholders(
     """
     Reconstructs the embeddings from the placeholder tokens.
 
-    This is the operation of {func}`scatter_mm_placeholders`.
+    This is the operation of [scatter_mm_placeholders][].
     """
     if is_embed is None:
         return placeholders