docs: class migration from sphinx to mkdocs (vllm)

Signed-off-by: Zerohertz <ohg3417@gmail.com>

Author: Zerohertz

vllm/config.py

@@ -2980,7 +2980,7 @@ class PoolerConfig:
     pooling_type: Optional[str] = None
     """
     The pooling method of the pooling model. This should be a key in
-    {class}`vllm.model_executor.layers.pooler.PoolingType`.
+    [`vllm.model_executor.layers.pooler.PoolingType`][].
     """
 
     normalize: Optional[bool] = None
@@ -3691,23 +3691,27 @@ class CompilationConfig:
     """Configuration for compilation. It has three parts:
 
     - Top-level Compilation control:
-        - {attr}`level`
-        - {attr}`debug_dump_path`
-        - {attr}`cache_dir`
-        - {attr}`backend`
-        - {attr}`custom_ops`
-        - {attr}`splitting_ops`
+        - [`level`][vllm.config.CompilationConfig.level]
+        - [`debug_dump_path`][vllm.config.CompilationConfig.debug_dump_path]
+        - [`cache_dir`][vllm.config.CompilationConfig.cache_dir]
+        - [`backend`][vllm.config.CompilationConfig.backend]
+        - [`custom_ops`][vllm.config.CompilationConfig.custom_ops]
+        - [`splitting_ops`][vllm.config.CompilationConfig.splitting_ops]
     - CudaGraph capture:
-        - {attr}`use_cudagraph`
-        - {attr}`cudagraph_capture_sizes`
-        - {attr}`cudagraph_num_of_warmups`
-        - {attr}`cudagraph_copy_inputs`
-        - {attr}`full_cuda_graph`
+        - [`use_cudagraph`][vllm.config.CompilationConfig.use_cudagraph]
+        - [`cudagraph_capture_sizes`]
+        [vllm.config.CompilationConfig.cudagraph_capture_sizes]
+        - [`cudagraph_num_of_warmups`]
+        [vllm.config.CompilationConfig.cudagraph_num_of_warmups]
+        - [`cudagraph_copy_inputs`]
+        [vllm.config.CompilationConfig.cudagraph_copy_inputs]
+        - [`full_cuda_graph`][vllm.config.CompilationConfig.full_cuda_graph]
     - Inductor compilation:
-        - {attr}`use_inductor`
-        - {attr}`compile_sizes`
-        - {attr}`inductor_compile_config`
-        - {attr}`inductor_passes`
+        - [`use_inductor`][vllm.config.CompilationConfig.use_inductor]
+        - [`compile_sizes`][vllm.config.CompilationConfig.compile_sizes]
+        - [`inductor_compile_config`]
+        [vllm.config.CompilationConfig.inductor_compile_config]
+        - [`inductor_passes`][vllm.config.CompilationConfig.inductor_passes]
         - custom inductor passes
 
     Why we have different sizes for cudagraph and inductor:

vllm/connections.py

@@ -167,4 +167,7 @@ async def async_download_file(
 
 
 global_http_connection = HTTPConnection()
-"""The global {class}`HTTPConnection` instance used by vLLM."""
+"""
+The global [`HTTPConnection`][vllm.connections.HTTPConnection] instance used
+by vLLM.
+"""

vllm/logger.py

@@ -68,22 +68,22 @@ class _VllmLogger(Logger):
     """
     Note:
         This class is just to provide type information.
-        We actually patch the methods directly on the {class}`logging.Logger`
+        We actually patch the methods directly on the [`logging.Logger`][]
         instance to avoid conflicting with other libraries such as
         `intel_extension_for_pytorch.utils._logger`.
     """
 
     def info_once(self, msg: str, *args: Hashable) -> None:
         """
-        As {meth}`info`, but subsequent calls with the same message
-        are silently dropped.
+        As [`info`][logging.Logger.info], but subsequent calls with
+        the same message are silently dropped.
         """
         _print_info_once(self, msg, *args)
 
     def warning_once(self, msg: str, *args: Hashable) -> None:
         """
-        As {meth}`warning`, but subsequent calls with the same message
-        are silently dropped.
+        As [`warning`][logging.Logger.warning], but subsequent calls with
+        the same message are silently dropped.
         """
         _print_warning_once(self, msg, *args)
 

vllm/sequence.py

@@ -27,7 +27,7 @@
 
 
 def array_full(token_id: int, count: int):
-    """{class}`array` equivalent of [numpy.full][]."""
+    """[`array`][] equivalent of [numpy.full][]."""
     return array(VLLM_TOKEN_ID_ARRAY_TYPE, [token_id]) * count
 
 
@@ -192,8 +192,8 @@ class SequenceData(msgspec.Struct,
     def from_prompt_token_counts(
             *token_counts: tuple[int, int]) -> "SequenceData":
         """
-        Construct a {class}`SequenceData` instance by concatenating
-        prompt token sequences.
+        Construct a [`SequenceData`][vllm.sequence.SequenceData] instance
+        by concatenating prompt token sequences.
 
         Each tuple represents one token sequence, expressed in the form
         `(token_id, count)`.
@@ -216,8 +216,8 @@ def from_seqs(
         prompt_embeds: Optional[torch.Tensor] = None,
     ) -> "SequenceData":
         """
-        Construct a {class}`SequenceData` instance from prompt and output
-        token sequences.
+        Construct a [`SequenceData`][vllm.sequence.SequenceData] instance
+        from prompt and output token sequences.
         """
         prompt_token_ids_arr = array(VLLM_TOKEN_ID_ARRAY_TYPE,
                                      prompt_token_ids)
@@ -452,9 +452,11 @@ def __repr__(self) -> str:
 class Sequence:
     """Stores the data, status, and block information of a sequence.
 
-    The sequence is constructed from the {data}`DecoderOnlyInputs`
-    (for decoder-only) or {data}`EncoderDecoderInputs` (for encoder-decoder)
-    instance passed in through the `inputs` constructor argument.
+    The sequence is constructed from the
+    [`DecoderOnlyInputs`][vllm.inputs.data.DecoderOnlyInputs] (for decoder-only)
+    or [`EncoderDecoderInputs`][vllm.inputs.data.EncoderDecoderInputs]
+    (for encoder-decoder) instance passed in through the `inputs`
+    constructor argument.
 
     Args:
         seq_id: The ID of the sequence.

vllm/utils.py

@@ -1004,7 +1004,7 @@ def flatten_2d_lists(lists: Iterable[Iterable[T]]) -> list[T]:
 
 def full_groupby(values: Iterable[_V], *, key: Callable[[_V], _K]):
     """
-    Unlike {class}`itertools.groupby`, groups are not broken by
+    Unlike [`itertools.groupby`][], groups are not broken by
     non-contiguous data.
     """
     groups = defaultdict[_K, list[_V]](list)
@@ -1924,7 +1924,8 @@ class _PlaceholderBase:
     Disallows downstream usage of placeholder modules.
 
     We need to explicitly override each dunder method because
-    {meth}`__getattr__` is not called when they are accessed.
+    [`__getattr__`][vllm.utils._PlaceholderBase.__getattr__]
+    is not called when they are accessed.
 
     Info:
         [Special method lookup](https://docs.python.org/3/reference/datamodel.html#special-lookup)