[Docs] Fix warnings in mkdocs build (continued) (#24740)

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

vllm/model_executor/models/aria.py

@@ -143,16 +143,8 @@ class AriaProjector(nn.Module):
     projects ViT's outputs into MoE's inputs.
 
     Args:
-        patch_to_query_dict (dict): Maps patch numbers to their corresponding
-        query numbers,
-            e.g., {1225: 128, 4900: 256}. This allows for different query sizes
-            based on image resolution.
-        embed_dim (int): Embedding dimension.
-        num_heads (int): Number of attention heads.
-        kv_dim (int): Dimension of key and value.
-        ff_dim (int): Hidden dimension of the feed-forward network.
-        output_dim (int): Output dimension.
-        norm_layer (nn.Module): Normalization layer. Default is nn.LayerNorm.
+        config: [AriaConfig](https://huggingface.co/docs/transformers/main/model_doc/aria#transformers.AriaConfig)
+            containing projector configuration parameters.
 
     Outputs:
         A tensor with the shape of (batch_size, query_number, output_dim)
@@ -282,8 +274,8 @@ class AriaTextMoELayer(nn.Module):
         Forward pass of the MoE Layer.
 
         Args:
-            hidden_states (torch.Tensor): Input tensor of shape (batch_size,
-            sequence_length, hidden_size).
+            hidden_states: Input tensor of shape
+                (batch_size, sequence_length, hidden_size).
 
         Returns:
             torch.Tensor: Output tensor after passing through the MoE layer.