mirror of
https://git.datalinker.icu/vllm-project/vllm.git
synced 2026-03-26 00:11:27 +08:00
remove multimodal in model_arch_config
Signed-off-by: Xingyu Liu <charlotteliu12x@gmail.com>
This commit is contained in:
parent
a8cc81a695
commit
48eeb1ffba
@ -13,7 +13,7 @@
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"total_num_kv_heads": 0,
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"num_experts": 0,
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"is_deepseek_mla": false,
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"is_multimodal_model": false,
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"supports_multimodal": false,
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"dtype": "torch.float32"
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},
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"mistralai/Mamba-Codestral-7B-v0.1": {
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@ -30,7 +30,7 @@
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"total_num_kv_heads": 0,
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"num_experts": 0,
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"is_deepseek_mla": false,
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"is_multimodal_model": false,
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"supports_multimodal": false,
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"dtype": "torch.bfloat16"
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},
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"ibm-nasa-geospatial/Prithvi-EO-2.0-300M-TL-Sen1Floods11": {
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@ -47,7 +47,7 @@
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"total_num_kv_heads": 0,
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"num_experts": 0,
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"is_deepseek_mla": false,
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"is_multimodal_model": true,
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"supports_multimodal": true,
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"dtype": "torch.float32"
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},
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"Zyphra/Zamba2-7B-instruct": {
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@ -64,7 +64,7 @@
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"total_num_kv_heads": 32,
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"num_experts": 0,
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"is_deepseek_mla": false,
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"is_multimodal_model": false,
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"supports_multimodal": false,
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"dtype": "torch.bfloat16"
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},
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"mosaicml/mpt-7b": {
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@ -81,7 +81,7 @@
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"total_num_kv_heads": 32,
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"num_experts": 0,
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"is_deepseek_mla": false,
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"is_multimodal_model": false,
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"supports_multimodal": false,
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"dtype": "torch.bfloat16"
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},
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"databricks/dbrx-instruct": {
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@ -98,7 +98,7 @@
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"total_num_kv_heads": 8,
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"num_experts": 0,
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"is_deepseek_mla": false,
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"is_multimodal_model": false,
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"supports_multimodal": false,
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"dtype": "torch.bfloat16"
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},
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"tiiuae/falcon-7b": {
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@ -115,7 +115,7 @@
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"total_num_kv_heads": 1,
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"num_experts": 0,
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"is_deepseek_mla": false,
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"is_multimodal_model": false,
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"supports_multimodal": false,
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"dtype": "torch.bfloat16"
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},
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"tiiuae/falcon-40b": {
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@ -132,7 +132,7 @@
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"total_num_kv_heads": 8,
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"num_experts": 0,
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"is_deepseek_mla": false,
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"is_multimodal_model": false,
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"supports_multimodal": false,
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"dtype": "torch.bfloat16"
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},
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"luccafong/deepseek_mtp_main_random": {
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@ -149,7 +149,7 @@
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"total_num_kv_heads": 32,
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"num_experts": 72,
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"is_deepseek_mla": true,
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"is_multimodal_model": false,
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"supports_multimodal": false,
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"dtype": "torch.bfloat16"
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},
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"luccafong/deepseek_mtp_draft_random": {
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@ -166,7 +166,7 @@
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"total_num_kv_heads": 32,
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"num_experts": 72,
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"is_deepseek_mla": true,
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"is_multimodal_model": false,
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"supports_multimodal": false,
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"dtype": "torch.bfloat16"
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},
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"Qwen/Qwen3-Next-80B-A3B-Instruct": {
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@ -183,7 +183,7 @@
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"total_num_kv_heads": 2,
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"num_experts": 512,
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"is_deepseek_mla": false,
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"is_multimodal_model": false,
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"supports_multimodal": false,
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"dtype": "torch.bfloat16"
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},
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"tiny-random/qwen3-next-moe": {
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@ -200,7 +200,7 @@
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"total_num_kv_heads": 8,
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"num_experts": 32,
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"is_deepseek_mla": false,
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"is_multimodal_model": false,
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"supports_multimodal": false,
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"dtype": "torch.bfloat16"
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},
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"zai-org/GLM-4.5": {
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@ -217,7 +217,7 @@
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"total_num_kv_heads": 8,
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"num_experts": 160,
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"is_deepseek_mla": false,
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"is_multimodal_model": false,
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"supports_multimodal": false,
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"dtype": "torch.bfloat16"
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},
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"baidu/ERNIE-4.5-21B-A3B-PT": {
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@ -234,7 +234,7 @@
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"total_num_kv_heads": 4,
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"num_experts": 64,
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"is_deepseek_mla": false,
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"is_multimodal_model": false,
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"supports_multimodal": false,
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"dtype": "torch.bfloat16"
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},
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"lmsys/gpt-oss-20b-bf16": {
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@ -251,7 +251,7 @@
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"total_num_kv_heads": 8,
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"num_experts": 32,
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"is_deepseek_mla": false,
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"is_multimodal_model": false,
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"supports_multimodal": false,
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"dtype": "torch.bfloat16"
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},
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"deepseek-ai/DeepSeek-V3.2-Exp": {
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@ -268,7 +268,7 @@
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"total_num_kv_heads": 128,
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"num_experts": 256,
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"is_deepseek_mla": true,
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"is_multimodal_model": false,
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"supports_multimodal": false,
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"dtype": "torch.bfloat16"
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},
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"meta-llama/Llama-4-Scout-17B-16E-Instruct": {
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@ -285,7 +285,7 @@
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"total_num_kv_heads": 8,
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"num_experts": 16,
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"is_deepseek_mla": false,
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"is_multimodal_model": true,
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"supports_multimodal": true,
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"dtype": "torch.bfloat16"
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},
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"nvidia/Llama-3_3-Nemotron-Super-49B-v1": {
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@ -302,7 +302,7 @@
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"total_num_kv_heads": 8,
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"num_experts": 0,
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"is_deepseek_mla": false,
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"is_multimodal_model": false,
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"supports_multimodal": false,
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"dtype": "torch.bfloat16"
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},
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"XiaomiMiMo/MiMo-7B-RL": {
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@ -319,7 +319,7 @@
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"total_num_kv_heads": 8,
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"num_experts": 0,
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"is_deepseek_mla": false,
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"is_multimodal_model": false,
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"supports_multimodal": false,
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"dtype": "torch.bfloat16"
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},
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"meituan-longcat/LongCat-Flash-Chat": {
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@ -336,7 +336,7 @@
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"total_num_kv_heads": 64,
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"num_experts": 512,
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"is_deepseek_mla": true,
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"is_multimodal_model": false,
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"supports_multimodal": false,
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"dtype": "torch.float32"
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}
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}
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@ -64,8 +64,6 @@ def test_model_arch_config():
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assert model_arch_config.total_num_kv_heads == expected["total_num_kv_heads"]
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assert model_arch_config.num_experts == expected["num_experts"]
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assert model_arch_config.is_deepseek_mla == expected["is_deepseek_mla"]
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assert model_arch_config.is_multimodal_model == expected["is_multimodal_model"]
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dtype = model_arch_config.torch_dtype
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assert str(dtype) == expected["dtype"]
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@ -53,9 +53,6 @@ class ModelArchitectureConfig:
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torch_dtype: torch.dtype | str | None
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"""PyTorch data type for model weights (e.g., 'float16', 'bfloat16')."""
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is_multimodal_model: bool
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"""Whether the model is a multimodal model."""
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is_deepseek_mla: bool
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"""Whether the model is a DeepSeek MLA model."""
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@ -1,7 +1,7 @@
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# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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from typing import TYPE_CHECKING, final
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from typing import final
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import torch
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from safetensors.torch import _TYPES as _SAFETENSORS_TO_TORCH_DTYPE
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@ -17,17 +17,8 @@ from vllm.transformers_utils.config import (
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get_hf_text_config,
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try_get_safetensors_metadata,
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)
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from vllm.utils.import_utils import LazyLoader
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from vllm.utils.torch_utils import common_broadcastable_dtype
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if TYPE_CHECKING:
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import vllm.model_executor.models.registry as me_models_registry
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else:
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# Use lazy loading to avoid circular import
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me_models_registry = LazyLoader(
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"model_executor", globals(), "vllm.model_executor.models.registry"
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)
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logger = init_logger(__name__)
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@ -248,12 +239,6 @@ class ModelArchConfigConvertorBase:
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derived_max_model_len = tmp_max_len
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return derived_max_model_len, max_len_key
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def is_multimodal_model(self) -> bool:
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return any(
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multi_model_arch in self.hf_config.architectures
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for multi_model_arch in me_models_registry._MULTIMODAL_MODELS
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)
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def convert(self, model_id: str, revision: str | None) -> ModelArchitectureConfig:
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model_arch_config = ModelArchitectureConfig(
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architectures=getattr(self.hf_config, "architectures", []),
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@ -268,7 +253,6 @@ class ModelArchConfigConvertorBase:
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num_experts=self.get_num_experts(self.hf_text_config),
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quantization_config=self.get_quantization_config(self.hf_config),
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torch_dtype=self.get_torch_dtype(self.hf_config, model_id, revision),
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is_multimodal_model=self.is_multimodal_model(),
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is_deepseek_mla=self.is_deepseek_mla(),
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derived_max_model_len_and_key=self.derive_max_model_len_and_key(),
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)
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