[CI/Build] Fix registry tests (#21934)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>

tests/models/registry.py

@@ -170,8 +170,10 @@ _TEXT_GENERATION_EXAMPLE_MODELS = {
                                             min_transformers_version="4.54"),
     "Ernie4_5_MoeForCausalLM": _HfExamplesInfo("baidu/ERNIE-4.5-21B-A3B-PT",
                                                min_transformers_version="4.54"),
-    "ExaoneForCausalLM": _HfExamplesInfo("LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct"),  # noqa: E501
-    "Exaone4ForCausalLM": _HfExamplesInfo("LGAI-EXAONE/EXAONE-4.0-32B"),  # noqa: E501
+    "ExaoneForCausalLM": _HfExamplesInfo("LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct",
+                                         trust_remote_code=True),
+    "Exaone4ForCausalLM": _HfExamplesInfo("LGAI-EXAONE/EXAONE-4.0-32B",
+                                          min_transformers_version="4.54"),
     "Fairseq2LlamaForCausalLM": _HfExamplesInfo("mgleize/fairseq2-dummy-Llama-3.2-1B"),  # noqa: E501
     "FalconForCausalLM": _HfExamplesInfo("tiiuae/falcon-7b"),
     "FalconH1ForCausalLM":_HfExamplesInfo("tiiuae/Falcon-H1-0.5B-Base",
@@ -199,8 +201,10 @@ _TEXT_GENERATION_EXAMPLE_MODELS = {
                                              trust_remote_code=True),
     "HunYuanMoEV1ForCausalLM": _HfExamplesInfo("tencent/Hunyuan-A13B-Instruct",
                                                trust_remote_code=True),
+    # TODO: Remove is_available_online once their config.json is fixed
     "HunYuanDenseV1ForCausalLM":_HfExamplesInfo("tencent/Hunyuan-7B-Instruct-0124",
-                                               trust_remote_code=True),
+                                                trust_remote_code=True,
+                                                is_available_online=False),
     "HCXVisionForCausalLM": _HfExamplesInfo(
         "naver-hyperclovax/HyperCLOVAX-SEED-Vision-Instruct-3B",
         trust_remote_code=True),
@@ -275,7 +279,8 @@ _TEXT_GENERATION_EXAMPLE_MODELS = {
     "StableLMEpochForCausalLM": _HfExamplesInfo("stabilityai/stablelm-zephyr-3b"),  # noqa: E501
     "StableLmForCausalLM": _HfExamplesInfo("stabilityai/stablelm-3b-4e1t"),
     "Starcoder2ForCausalLM": _HfExamplesInfo("bigcode/starcoder2-3b"),
-    "SolarForCausalLM": _HfExamplesInfo("upstage/solar-pro-preview-instruct"),
+    "SolarForCausalLM": _HfExamplesInfo("upstage/solar-pro-preview-instruct",
+                                        trust_remote_code=True),
     "TeleChat2ForCausalLM": _HfExamplesInfo("Tele-AI/TeleChat2-3B",
                                             trust_remote_code=True),
     "TeleFLMForCausalLM": _HfExamplesInfo("CofeAI/FLM-2-52B-Instruct-2407",
@@ -449,7 +454,8 @@ _MULTIMODAL_EXAMPLE_MODELS = {
                                                           max_model_len=4096),
     "Qwen2_5OmniModel": _HfExamplesInfo("Qwen/Qwen2.5-Omni-3B"),
     "Qwen2_5OmniForConditionalGeneration": _HfExamplesInfo("Qwen/Qwen2.5-Omni-7B-AWQ"),  # noqa: E501
-    "SkyworkR1VChatModel": _HfExamplesInfo("Skywork/Skywork-R1V-38B"),
+    "SkyworkR1VChatModel": _HfExamplesInfo("Skywork/Skywork-R1V-38B",
+                                           trust_remote_code=True),
     "SmolVLMForConditionalGeneration": _HfExamplesInfo("HuggingFaceTB/SmolVLM2-2.2B-Instruct"),  # noqa: E501
     "UltravoxModel": _HfExamplesInfo("fixie-ai/ultravox-v0_5-llama-3_2-1b",  # noqa: E501
                                      trust_remote_code=True),

vllm/model_executor/models/mpt.py

@@ -8,7 +8,7 @@ from typing import Optional, Union
 
 import torch
 import torch.nn as nn
-from transformers import PretrainedConfig
+from transformers import MptConfig
 
 from vllm.attention import Attention
 from vllm.compilation.decorators import support_torch_compile
@@ -50,7 +50,7 @@ class MPTAttention(nn.Module):
 
     def __init__(
         self,
-        config: PretrainedConfig,
+        config: MptConfig,
         cache_config: Optional[CacheConfig] = None,
         quant_config: Optional[QuantizationConfig] = None,
         prefix: str = "",
@@ -59,15 +59,15 @@ class MPTAttention(nn.Module):
         self.d_model = config.d_model
         self.total_num_heads = config.n_heads
         self.head_dim = self.d_model // self.total_num_heads
-        self.clip_qkv = config.attn_config["clip_qkv"]
-        self.qk_ln = config.attn_config["qk_ln"]
-        self.alibi_bias_max = config.attn_config["alibi_bias_max"]
+        self.clip_qkv = config.attn_config.clip_qkv
+        self.qk_ln = config.attn_config.qk_ln
+        self.alibi_bias_max = config.attn_config.alibi_bias_max
         if "kv_n_heads" in config.attn_config:
-            self.total_num_kv_heads = config.attn_config['kv_n_heads']
+            self.total_num_kv_heads = config.attn_config.kv_n_heads
         else:
             self.total_num_kv_heads = self.total_num_heads
-        assert not config.attn_config["prefix_lm"]
-        assert config.attn_config["alibi"]
+        assert not config.attn_config.prefix_lm
+        assert config.attn_config.alibi
 
         # pylint: disable=invalid-name
         self.Wqkv = QKVParallelLinear(
@@ -144,7 +144,7 @@ class MPTMLP(nn.Module):
 
     def __init__(
         self,
-        config: PretrainedConfig,
+        config: MptConfig,
         quant_config: Optional[QuantizationConfig] = None,
     ):
         super().__init__()
@@ -176,7 +176,7 @@ class MPTBlock(nn.Module):
 
     def __init__(
         self,
-        config: PretrainedConfig,
+        config: MptConfig,
         cache_config: Optional[CacheConfig] = None,
         quant_config: Optional[QuantizationConfig] = None,
         prefix: str = "",

vllm/model_executor/models/telechat2.py

@@ -37,9 +37,20 @@ from .utils import (AutoWeightsLoader, PPMissingLayer, WeightsMapper,
 class TeleChat2Model(LlamaModel):
 
     def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
+        hf_config = vllm_config.model_config.hf_config
+
+        vllm_config.model_config.hf_config.attribute_map = {
+            "num_hidden_layers": "n_layer",
+            "num_attention_heads": "n_head",
+            "intermediate_size": "ffn_hidden_size",
+            "rms_norm_eps": "layer_norm_epsilon"
+        }
+        vllm_config.model_config.hf_config.hidden_act = "silu"
+
         # 1. Initialize the LlamaModel with bias
-        vllm_config.model_config.hf_config.bias = True
-        vllm_config.model_config.hf_config.mlp_bias = True
+        hf_config.bias = True
+        hf_config.mlp_bias = True
+
         super().__init__(vllm_config=vllm_config, prefix=prefix)
         # 2. Remove the bias from the qkv_proj and gate_up_proj based on config
         # Telechat2's gate_up_proj and qkv_proj don't have bias

vllm/transformers_utils/config.py

@@ -34,8 +34,8 @@ from vllm.transformers_utils.configs import (ChatGLMConfig, DeepseekVLV2Config,
                                              KimiVLConfig, MedusaConfig,
                                              MllamaConfig, MLPSpeculatorConfig,
                                              Nemotron_Nano_VL_Config,
-                                             NemotronConfig, RWConfig,
-                                             UltravoxConfig)
+                                             NemotronConfig, NVLM_D_Config,
+                                             RWConfig, UltravoxConfig)
 # yapf: enable
 from vllm.transformers_utils.configs.mistral import adapt_config_dict
 from vllm.transformers_utils.utils import check_gguf_file
@@ -81,6 +81,7 @@ _CONFIG_REGISTRY: dict[str, type[PretrainedConfig]] = {
     "medusa": MedusaConfig,
     "eagle": EAGLEConfig,
     "nemotron": NemotronConfig,
+    "NVLM_D": NVLM_D_Config,
     "ultravox": UltravoxConfig,
     **_CONFIG_REGISTRY_OVERRIDE_HF
 }

vllm/transformers_utils/configs/__init__.py

@@ -23,6 +23,7 @@ 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.ultravox import UltravoxConfig
 
 __all__ = [
@@ -39,5 +40,6 @@ __all__ = [
     "NemotronConfig",
     "NemotronHConfig",
     "Nemotron_Nano_VL_Config",
+    "NVLM_D_Config",
     "UltravoxConfig",
 ]

vllm/transformers_utils/configs/nvlm_d.py

+# 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)