[Misc] Further clean up some redundant config definitions (#22649)

Signed-off-by: Isotr0py <2037008807@qq.com>

vllm/transformers_utils/config.py

@@ -32,11 +32,10 @@ from vllm.logger import init_logger
 from vllm.transformers_utils.configs import (ChatGLMConfig, DeepseekVLV2Config,
                                              EAGLEConfig, JAISConfig,
                                              KimiVLConfig, MedusaConfig,
-                                             MllamaConfig, MLPSpeculatorConfig,
+                                             MLPSpeculatorConfig,
                                              Nemotron_Nano_VL_Config,
-                                             NemotronConfig, NVLM_D_Config,
+                                             NemotronConfig, OvisConfig,
-                                             OvisConfig, RWConfig,
+                                             RWConfig, SpeculatorsConfig,
-                                             SpeculatorsConfig,
                                              Step3TextConfig, Step3VLConfig,
                                              UltravoxConfig)
 # yapf: enable
@@ -68,10 +67,6 @@ def _get_hf_token() -> Optional[str]:
     return None
 
 
-_CONFIG_REGISTRY_OVERRIDE_HF: dict[str, type[PretrainedConfig]] = {
-    "mllama": MllamaConfig
-}
-
 _CONFIG_REGISTRY: dict[str, type[PretrainedConfig]] = {
     "chatglm": ChatGLMConfig,
     "deepseek_vl_v2": DeepseekVLV2Config,
@@ -85,18 +80,30 @@ _CONFIG_REGISTRY: dict[str, type[PretrainedConfig]] = {
     "eagle": EAGLEConfig,
     "speculators": SpeculatorsConfig,
     "nemotron": NemotronConfig,
-    "NVLM_D": NVLM_D_Config,
     "ovis": OvisConfig,
     "ultravox": UltravoxConfig,
     "step3_vl": Step3VLConfig,
     "step3_text": Step3TextConfig,
-    **_CONFIG_REGISTRY_OVERRIDE_HF
 }
 
 _CONFIG_ATTRS_MAPPING: dict[str, str] = {
     "llm_config": "text_config",
 }
 
+_AUTO_CONFIG_KWARGS_OVERRIDES: dict[str, dict[str, Any]] = {
+    "internvl_chat": {
+        "has_no_defaults_at_init": True
+    },
+    # transformers regards mllama as is_encoder_decoder=False
+    # vllm needs is_encoder_decoder=True to enable cross-attention
+    "mllama": {
+        "is_encoder_decoder": True
+    },
+    "NVLM_D": {
+        "has_no_defaults_at_init": True
+    },
+}
+
 
 class ConfigFormat(str, enum.Enum):
     AUTO = "auto"
@@ -273,12 +280,13 @@ def thinker_uses_mrope(config: PretrainedConfig) -> bool:
 
 def is_encoder_decoder(config: PretrainedConfig) -> bool:
     """Detect if the model with this config is used as an encoder/decoder."""
-    text_config = getattr(config, "text_config", None)
-    if text_config is not None:
-        return is_encoder_decoder(text_config)
 
+    def _is_encoder_decoder(config: PretrainedConfig) -> bool:
         return getattr(config, "is_encoder_decoder", False)
 
+    return (_is_encoder_decoder(config)
+            or _is_encoder_decoder(config.get_text_config()))
+
 
 def is_interleaved(config: PretrainedConfig) -> bool:
     """
@@ -291,13 +299,21 @@ def is_interleaved(config: PretrainedConfig) -> bool:
     return False
 
 
+def _maybe_update_auto_config_kwargs(kwargs: dict[str, Any], model_type: str):
+    """
+    Update kwargs for AutoConfig initialization based on model_type
+    """
+    if model_type in _AUTO_CONFIG_KWARGS_OVERRIDES:
+        kwargs.update(_AUTO_CONFIG_KWARGS_OVERRIDES[model_type])
+    return kwargs
+
+
 def _maybe_remap_hf_config_attrs(config: PretrainedConfig) -> PretrainedConfig:
     """Remap config attributes to match the expected names."""
     for old_attr, new_attr in _CONFIG_ATTRS_MAPPING.items():
         if hasattr(config, old_attr):
             if not hasattr(config, new_attr):
                 config.update({new_attr: getattr(config, old_attr)})
-            delattr(config, old_attr)
             logger.debug("Remapped config attribute '%s' to '%s'", old_attr,
                          new_attr)
     return config
@@ -408,15 +424,14 @@ def get_config(
             )
         else:
             try:
+                kwargs = _maybe_update_auto_config_kwargs(
+                    kwargs, model_type=model_type)
                 config = AutoConfig.from_pretrained(
                     model,
                     trust_remote_code=trust_remote_code,
                     revision=revision,
                     code_revision=code_revision,
                     token=_get_hf_token(),
-                    # some old custom model's config needs
-                    # `has_no_defaults_at_init=True` to work.
-                    has_no_defaults_at_init=trust_remote_code,
                     **kwargs,
                 )
             except ValueError as e:

vllm/transformers_utils/configs/__init__.py

@@ -17,13 +17,11 @@ from vllm.transformers_utils.configs.falcon import RWConfig
 from vllm.transformers_utils.configs.jais import JAISConfig
 from vllm.transformers_utils.configs.kimi_vl import KimiVLConfig
 from vllm.transformers_utils.configs.medusa import MedusaConfig
-from vllm.transformers_utils.configs.mllama import MllamaConfig
 from vllm.transformers_utils.configs.mlp_speculator import MLPSpeculatorConfig
 from vllm.transformers_utils.configs.moonvit import MoonViTConfig
 from vllm.transformers_utils.configs.nemotron import NemotronConfig
 from vllm.transformers_utils.configs.nemotron_h import NemotronHConfig
 from vllm.transformers_utils.configs.nemotron_vl import Nemotron_Nano_VL_Config
-from vllm.transformers_utils.configs.nvlm_d import NVLM_D_Config
 from vllm.transformers_utils.configs.ovis import OvisConfig
 from vllm.transformers_utils.configs.speculators.base import SpeculatorsConfig
 from vllm.transformers_utils.configs.step3_vl import (Step3TextConfig,
@@ -34,18 +32,16 @@ from vllm.transformers_utils.configs.ultravox import UltravoxConfig
 __all__ = [
     "ChatGLMConfig",
     "DeepseekVLV2Config",
+    "EAGLEConfig",
     "RWConfig",
     "JAISConfig",
     "MedusaConfig",
-    "EAGLEConfig",
-    "MllamaConfig",
     "MLPSpeculatorConfig",
     "MoonViTConfig",
     "KimiVLConfig",
     "NemotronConfig",
     "NemotronHConfig",
     "Nemotron_Nano_VL_Config",
-    "NVLM_D_Config",
     "OvisConfig",
     "SpeculatorsConfig",
     "UltravoxConfig",

vllm/transformers_utils/configs/mllama.py

@@ -1,31 +0,0 @@
-# SPDX-License-Identifier: Apache-2.0
-# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
-
-from transformers.models.mllama import configuration_mllama as mllama_hf_config
-
-
-class MllamaTextConfig(mllama_hf_config.MllamaTextConfig):
-    '''
-    Use this class to override is_encoder_decoder:
-    - transformers regards mllama as is_encoder_decoder=False
-    - vllm needs is_encoder_decoder=True to enable cross-attention
-    '''
-
-    def __init__(
-        self,
-        **kwargs,
-    ):
-        super().__init__(**kwargs)
-        self.is_encoder_decoder = True
-
-
-class MllamaConfig(mllama_hf_config.MllamaConfig):
-
-    def __init__(
-        self,
-        text_config=None,
-        **kwargs,
-    ):
-        if isinstance(text_config, dict):
-            text_config = MllamaTextConfig(**text_config)
-        super().__init__(text_config=text_config, **kwargs)

vllm/transformers_utils/configs/nvlm_d.py

@@ -1,31 +0,0 @@
-# SPDX-License-Identifier: Apache-2.0
-# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
-
-# Adapted from
-# https://huggingface.co/nvidia/NVLM-D-72B/blob/main/configuration_nvlm_d.py
-# --------------------------------------------------------
-# NVLM-D
-# Copyright (c) 2024 NVIDIA
-# Licensed under Apache 2.0 License [see LICENSE for details]
-# --------------------------------------------------------
-from transformers import Qwen2Config
-from transformers.configuration_utils import PretrainedConfig
-
-
-class NVLM_D_Config(PretrainedConfig):
-    model_type = 'NVLM_D'
-    is_composition = True
-
-    def __init__(self, vision_config=None, llm_config=None, **kwargs):
-        super().__init__(**kwargs)
-
-        # Handle vision_config initialization
-        if vision_config is None:
-            vision_config = {}
-
-        # Handle llm_config initialization
-        if llm_config is None:
-            llm_config = {}
-
-        self.vision_config = PretrainedConfig(**vision_config)
-        self.text_config = Qwen2Config(**llm_config)