[Chore] Remove Nemotron-Nano-VL config copy (#28126)

Signed-off-by: Isotr0py <mozf@mail2.sysu.edu.cn>

vllm/transformers_utils/config.py

@@ -81,7 +81,6 @@ _CONFIG_REGISTRY: dict[str, type[PretrainedConfig]] = LazyConfigDict(
     flex_olmo="FlexOlmoConfig",
     kimi_linear="KimiLinearConfig",
     kimi_vl="KimiVLConfig",
-    Llama_Nemotron_Nano_VL="Nemotron_Nano_VL_Config",
     RefinedWeb="RWConfig",  # For tiiuae/falcon-40b(-instruct)
     RefinedWebModel="RWConfig",  # For tiiuae/falcon-7b(-instruct)
     jais="JAISConfig",
@@ -106,6 +105,7 @@ _CONFIG_ATTRS_MAPPING: dict[str, str] = {
 
 _AUTO_CONFIG_KWARGS_OVERRIDES: dict[str, dict[str, Any]] = {
     "internvl_chat": {"has_no_defaults_at_init": True},
+    "Llama_Nemotron_Nano_VL": {"attn_implementation": "eager"},
     "NVLM_D": {"has_no_defaults_at_init": True},
 }
 

vllm/transformers_utils/configs/__init__.py

@@ -28,7 +28,6 @@ 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.olmo3 import Olmo3Config
 from vllm.transformers_utils.configs.ovis import OvisConfig
 from vllm.transformers_utils.configs.qwen3_next import Qwen3NextConfig
@@ -59,7 +58,6 @@ __all__ = [
     "KimiVLConfig",
     "NemotronConfig",
     "NemotronHConfig",
-    "Nemotron_Nano_VL_Config",
     "Olmo3Config",
     "OvisConfig",
     "RadioConfig",

vllm/transformers_utils/configs/nemotron_vl.py

-# SPDX-License-Identifier: Apache-2.0
-# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
-
-# ruff: noqa: E501
-# Adapted from
-# https://huggingface.co/nvidia/Llama-3.1-Nemotron-Nano-VL-8B-V1/blob/main/configuration.py
-# --------------------------------------------------------
-# Adapted from https://huggingface.co/OpenGVLab/InternVL2-Llama3-76B under MIT License
-#     LICENSE is in incl_licenses directory.
-# --------------------------------------------------------
-
-from transformers import LlamaConfig
-from transformers.configuration_utils import PretrainedConfig
-from transformers.dynamic_module_utils import get_class_from_dynamic_module
-
-
-class Nemotron_Nano_VL_Config(PretrainedConfig):
-    model_type = "Llama_Nemotron_Nano_VL"
-    is_composition = True
-
-    def __init__(
-        self,
-        vision_config=None,
-        llm_config=None,
-        force_image_size=None,
-        downsample_ratio=0.5,
-        template=None,
-        ps_version="v1",
-        image_tag_type="internvl",
-        projector_hidden_size=4096,
-        vit_hidden_size=1280,
-        **kwargs,
-    ):
-        super().__init__(**kwargs)
-
-        if vision_config is not None:
-            assert (
-                "auto_map" in vision_config
-                and "AutoConfig" in vision_config["auto_map"]
-            )
-            vision_auto_config = get_class_from_dynamic_module(
-                *vision_config["auto_map"]["AutoConfig"].split("--")[::-1]
-            )
-            self.vision_config = vision_auto_config(**vision_config)
-        else:
-            self.vision_config = PretrainedConfig()
-
-        if llm_config is None:
-            self.text_config = LlamaConfig()
-        else:
-            self.text_config = LlamaConfig(**llm_config)
-
-        # Assign configuration values
-        self.force_image_size = force_image_size
-        self.downsample_ratio = downsample_ratio
-        self.template = template  # TODO move out of here and into the tokenizer
-        self.ps_version = ps_version  # Pixel shuffle version
-        self.image_tag_type = image_tag_type  # TODO: into the tokenizer too?
-        self.projector_hidden_size = projector_hidden_size
-        self.vit_hidden_size = vit_hidden_size