[Auto Sync] Update load_config.py, model_config.py, configu... (20250923) (#10825)

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

python/sglang/srt/configs/load_config.py

@@ -24,6 +24,8 @@ class LoadFormat(str, enum.Enum):
     JAX = "jax"
     REMOTE = "remote"
     REMOTE_INSTANCE = "remote_instance"
+    RDMA = "rdma"
+    LOCAL_CACHED = "local_cached"
 
 
 @dataclass
@@ -47,6 +49,7 @@ class LoadConfig:
         checkpoints.
     decryption_key_file: If set, decrypts the output files with a password read
         from this file (after PBKDF2).
+    decrypt_max_concurrency: The maximum number of concurrent processes to decrypt the safetensor files. -1 means no limit.
     """
 
     load_format: Union[str, LoadFormat] = LoadFormat.AUTO
@@ -54,6 +57,7 @@ class LoadConfig:
     model_loader_extra_config: Optional[Union[str, dict]] = field(default_factory=dict)
     ignore_patterns: Optional[Union[List[str], str]] = None
     decryption_key_file: Optional[str] = None
+    decrypt_max_concurrency: int = -1
 
     def __post_init__(self):
         model_loader_extra_config = self.model_loader_extra_config or {}

python/sglang/srt/configs/model_config.py

@@ -75,7 +75,10 @@ class ModelConfig:
         self.model_path = model_path
         self.revision = revision
         self.quantization = quantization
+        self.is_draft_model = is_draft_model
         self.model_impl = model_impl
+
+        # TODO: remove these fields
         self.tp_rank = tp_rank
         self.remote_instance_weight_loader_seed_instance_ip = (
             remote_instance_weight_loader_seed_instance_ip
@@ -87,12 +90,12 @@ class ModelConfig:
             remote_instance_weight_loader_send_weights_group_ports
         )
 
-        self.maybe_pull_model_tokenizer_from_remote()
+        # Get hf config
+        self._maybe_pull_model_tokenizer_from_remote()
         self.model_override_args = json.loads(model_override_args)
         kwargs = {}
         if override_config_file and override_config_file.strip():
             kwargs["_configuration_file"] = override_config_file.strip()
-
         self.hf_config = get_config(
             self.model_path,
             trust_remote_code=trust_remote_code,
@@ -100,7 +103,7 @@ class ModelConfig:
             model_override_args=self.model_override_args,
             **kwargs,
         )
-
+        self.hf_text_config = get_hf_text_config(self.hf_config)
         self.hf_generation_config = get_generation_config(
             self.model_path,
             trust_remote_code=trust_remote_code,
@@ -108,7 +111,25 @@ class ModelConfig:
             **kwargs,
         )
 
-        self.hf_text_config = get_hf_text_config(self.hf_config)
+        # Set enable_multimodal
+        if enable_multimodal is None:
+            mm_disabled_models = [
+                "Gemma3ForConditionalGeneration",
+                "Llama4ForConditionalGeneration",
+                "Step3VLForConditionalGeneration",
+            ]
+            if self.hf_config.architectures[0] in mm_disabled_models:
+                enable_multimodal = False
+                logger.info(
+                    f"Multimodal is disabled for {self.hf_config.model_type}. To enable it, set --enable-multimodal."
+                )
+            else:
+                enable_multimodal = True
+
+        # Config draft model
+        self._config_draft_model()
+
+        # Check model type
         self.attention_chunk_size = getattr(
             self.hf_text_config, "attention_chunk_size", None
         )
@@ -124,20 +145,73 @@ class ModelConfig:
                     self.hf_config.architectures, self.hf_text_config.num_hidden_layers
                 )
             )
+        self.is_generation = is_generation_model(
+            self.hf_config.architectures, is_embedding
+        )
+        self.is_multimodal = enable_multimodal and is_multimodal_model(
+            self.hf_config.architectures
+        )
+        self.is_multimodal_gen = enable_multimodal and is_multimodal_gen_model(
+            self.hf_config.architectures
+        )
+        self.is_image_gen = enable_multimodal and is_image_gen_model(
+            self.hf_config.architectures
+        )
+        self.is_audio_model = enable_multimodal and is_audio_model(
+            self.hf_config.architectures
+        )
+        self.is_multimodal_chunked_prefill_supported = (
+            enable_multimodal
+            and is_multimodal_chunked_prefill_supported(self.hf_config.architectures)
+        )
+        self.is_encoder_decoder = is_encoder_decoder_model(self.hf_config.architectures)
+        self.dtype = _get_and_verify_dtype(self.hf_text_config, dtype)
 
-        if enable_multimodal is None:
-            mm_disabled_models = [
-                "Gemma3ForConditionalGeneration",
-                "Llama4ForConditionalGeneration",
-                "Step3VLForConditionalGeneration",
-            ]
-            if self.hf_config.architectures[0] in mm_disabled_models:
-                enable_multimodal = False
-                logger.info(
-                    f"Multimodal is disabled for {self.hf_config.model_type}. To enable it, set --enable-multimodal."
+        # Derive context length and model shapes
+        self._derive_context_length(context_length)
+        self._derive_model_shapes()
+
+        # Verify quantization
+        self._verify_quantization()
+
+        # Verify dual-chunk attention config
+        self._verify_dual_chunk_attention_config()
+
+        # Cache attributes
+        self.hf_eos_token_id = self._get_hf_eos_token_id()
+
+        # multimodal
+        self.image_token_id = getattr(
+            self.hf_config, "image_token_id", None
+        ) or getattr(self.hf_config, "image_token_index", None)
+
+    @staticmethod
+    def from_server_args(
+        server_args: ServerArgs,
+        model_path: str = None,
+        model_revision: str = None,
+        **kwargs,
+    ):
+        return ModelConfig(
+            model_path=model_path or server_args.model_path,
+            trust_remote_code=server_args.trust_remote_code,
+            revision=model_revision or server_args.revision,
+            context_length=server_args.context_length,
+            model_override_args=server_args.json_model_override_args,
+            is_embedding=server_args.is_embedding,
+            enable_multimodal=server_args.enable_multimodal,
+            dtype=server_args.dtype,
+            quantization=server_args.quantization,
+            hybrid_kvcache_ratio=server_args.hybrid_kvcache_ratio,
+            model_impl=server_args.model_impl,
+            remote_instance_weight_loader_seed_instance_ip=server_args.remote_instance_weight_loader_seed_instance_ip,
+            remote_instance_weight_loader_seed_instance_service_port=server_args.remote_instance_weight_loader_seed_instance_service_port,
+            remote_instance_weight_loader_send_weights_group_ports=server_args.remote_instance_weight_loader_send_weights_group_ports,
+            **kwargs,
         )
-            else:
-                enable_multimodal = True
+
+    def _config_draft_model(self):
+        is_draft_model = self.is_draft_model
 
         if (
             is_draft_model
@@ -172,31 +246,10 @@ class ModelConfig:
             self.hf_config.architectures[0] = "Qwen3NextForCausalLMMTP"
             self.hf_config.num_nextn_predict_layers = 1
 
-        # Check model type
-        self.is_generation = is_generation_model(
-            self.hf_config.architectures, is_embedding
-        )
-        self.is_multimodal = enable_multimodal and is_multimodal_model(
-            self.hf_config.architectures
-        )
-        self.is_multimodal_gen = enable_multimodal and is_multimodal_gen_model(
-            self.hf_config.architectures
-        )
-        self.is_image_gen = enable_multimodal and is_image_gen_model(
-            self.hf_config.architectures
-        )
-        self.is_audio_model = enable_multimodal and is_audio_model(
-            self.hf_config.architectures
-        )
-        self.is_multimodal_chunked_prefill_supported = (
-            enable_multimodal
-            and is_multimodal_chunked_prefill_supported(self.hf_config.architectures)
-        )
-        self.is_encoder_decoder = is_encoder_decoder_model(self.hf_config.architectures)
-        self.dtype = _get_and_verify_dtype(self.hf_text_config, dtype)
-
-        # Derive context length
+    def _derive_context_length(self, context_length: int):
+        is_draft_model = self.is_draft_model
         derived_context_len = get_context_length(self.hf_text_config)
+
         if context_length is not None:
             if context_length > derived_context_len:
                 reason = "Target model's" if is_draft_model else "User-specified"
@@ -224,6 +277,10 @@ class ModelConfig:
         else:
             self.context_len = derived_context_len
 
+        # Transfer context_len to HuggingFace config so models can access it
+        self.hf_config.context_len = self.context_len
+
+    def _derive_model_shapes(self):
         # Unify the config keys for hf_text_config
         self.head_dim = getattr(
             self.hf_text_config,
@@ -318,45 +375,6 @@ class ModelConfig:
         )
         self.vocab_size = self.hf_text_config.vocab_size
 
-        # Verify quantization
-        self._verify_quantization()
-
-        # Verify dual-chunk attention config
-        self._verify_dual_chunk_attention_config()
-
-        # Cache attributes
-        self.hf_eos_token_id = self.get_hf_eos_token_id()
-
-        # multimodal
-        self.image_token_id = getattr(
-            self.hf_config, "image_token_id", None
-        ) or getattr(self.hf_config, "image_token_index", None)
-
-    @staticmethod
-    def from_server_args(
-        server_args: ServerArgs,
-        model_path: str = None,
-        model_revision: str = None,
-        **kwargs,
-    ):
-        return ModelConfig(
-            model_path=model_path or server_args.model_path,
-            trust_remote_code=server_args.trust_remote_code,
-            revision=model_revision or server_args.revision,
-            context_length=server_args.context_length,
-            model_override_args=server_args.json_model_override_args,
-            is_embedding=server_args.is_embedding,
-            enable_multimodal=server_args.enable_multimodal,
-            dtype=server_args.dtype,
-            quantization=server_args.quantization,
-            hybrid_kvcache_ratio=server_args.hybrid_kvcache_ratio,
-            model_impl=server_args.model_impl,
-            remote_instance_weight_loader_seed_instance_ip=server_args.remote_instance_weight_loader_seed_instance_ip,
-            remote_instance_weight_loader_seed_instance_service_port=server_args.remote_instance_weight_loader_seed_instance_service_port,
-            remote_instance_weight_loader_send_weights_group_ports=server_args.remote_instance_weight_loader_send_weights_group_ports,
-            **kwargs,
-        )
-
     def get_total_num_attention_heads(self) -> int:
         return self.num_attention_heads
 
@@ -591,7 +609,7 @@ class ModelConfig:
                     "sparse_attention_enabled"
                 ] = True
 
-    def get_hf_eos_token_id(self) -> Optional[Set[int]]:
+    def _get_hf_eos_token_id(self) -> Optional[Set[int]]:
         eos_ids = getattr(self.hf_config, "eos_token_id", None)
         if eos_ids is not None:
             # it can be either int or list of int
@@ -611,7 +629,7 @@ class ModelConfig:
                 eos_ids = eos_ids | generation_eos_ids
         return eos_ids
 
-    def maybe_pull_model_tokenizer_from_remote(self) -> None:
+    def _maybe_pull_model_tokenizer_from_remote(self) -> None:
         """
         Pull the model config files to a temporary
         directory in case of remote.

python/sglang/srt/layers/quantization/deep_gemm_wrapper/configurer.py

 import logging
 
-import torch
-
 from sglang.srt.utils import get_bool_env_var, get_device_sm, is_blackwell
 
 logger = logging.getLogger(__name__)