feat: update linear deps 1/N (#1305)

python/sglang/srt/layers/activation.py

@@ -31,8 +31,9 @@ from vllm.distributed import (
     get_tensor_model_parallel_world_size,
 )
 from vllm.model_executor.custom_op import CustomOp
-from vllm.model_executor.layers.quantization import QuantizationConfig
-from vllm.model_executor.utils import set_weight_attrs
+
+from sglang.srt.layers.quantization.base_config import QuantizationConfig
+from sglang.srt.utils import set_weight_attrs
 
 logger = logging.getLogger(__name__)
 

python/sglang/srt/layers/quantization/__init__.py

+# Adapted from https://raw.githubusercontent.com/vllm-project/vllm/v0.5.5/vllm/model_executor/layers/quantization/__init__.py
+
+from typing import Dict, Type
+
+from vllm.model_executor.layers.quantization.aqlm import AQLMConfig
+from vllm.model_executor.layers.quantization.awq import AWQConfig
+from vllm.model_executor.layers.quantization.awq_marlin import AWQMarlinConfig
+from vllm.model_executor.layers.quantization.bitsandbytes import BitsAndBytesConfig
+from vllm.model_executor.layers.quantization.compressed_tensors.compressed_tensors import (  # noqa: E501
+    CompressedTensorsConfig,
+)
+from vllm.model_executor.layers.quantization.deepspeedfp import DeepSpeedFPConfig
+from vllm.model_executor.layers.quantization.experts_int8 import ExpertsInt8Config
+from vllm.model_executor.layers.quantization.fbgemm_fp8 import FBGEMMFp8Config
+from vllm.model_executor.layers.quantization.fp8 import Fp8Config
+from vllm.model_executor.layers.quantization.gguf import GGUFConfig
+from vllm.model_executor.layers.quantization.gptq import GPTQConfig
+from vllm.model_executor.layers.quantization.gptq_marlin import GPTQMarlinConfig
+from vllm.model_executor.layers.quantization.gptq_marlin_24 import GPTQMarlin24Config
+from vllm.model_executor.layers.quantization.marlin import MarlinConfig
+from vllm.model_executor.layers.quantization.qqq import QQQConfig
+from vllm.model_executor.layers.quantization.squeezellm import SqueezeLLMConfig
+from vllm.model_executor.layers.quantization.tpu_int8 import Int8TpuConfig
+
+from sglang.srt.layers.quantization.base_config import QuantizationConfig
+
+QUANTIZATION_METHODS: Dict[str, Type[QuantizationConfig]] = {
+    "aqlm": AQLMConfig,
+    "awq": AWQConfig,
+    "deepspeedfp": DeepSpeedFPConfig,
+    "tpu_int8": Int8TpuConfig,
+    "fp8": Fp8Config,
+    "fbgemm_fp8": FBGEMMFp8Config,
+    # The order of gptq methods is important for config.py iteration over
+    # override_quantization_method(..)
+    "marlin": MarlinConfig,
+    "gguf": GGUFConfig,
+    "gptq_marlin_24": GPTQMarlin24Config,
+    "gptq_marlin": GPTQMarlinConfig,
+    "awq_marlin": AWQMarlinConfig,
+    "gptq": GPTQConfig,
+    "squeezellm": SqueezeLLMConfig,
+    "compressed-tensors": CompressedTensorsConfig,
+    "bitsandbytes": BitsAndBytesConfig,
+    "qqq": QQQConfig,
+    "experts_int8": ExpertsInt8Config,
+}
+
+
+def get_quantization_config(quantization: str) -> Type[QuantizationConfig]:
+    if quantization not in QUANTIZATION_METHODS:
+        raise ValueError(f"Invalid quantization method: {quantization}")
+    return QUANTIZATION_METHODS[quantization]
+
+
+__all__ = [
+    "QuantizationConfig",
+    "get_quantization_config",
+    "QUANTIZATION_METHODS",
+]
+
+"""
+def fp8_get_quant_method(
+    self, layer: torch.nn.Module, prefix: str
+) -> Optional["QuantizeMethodBase"]:
+    if isinstance(layer, LinearBase):
+        if is_layer_skipped(prefix, self.ignored_layers):
+            return UnquantizedLinearMethod()
+        return Fp8LinearMethod(self)
+    elif isinstance(layer, FusedMoE):
+        return Fp8MoEMethod(self)
+    return None
+
+
+setattr(Fp8Config, "get_quant_method", fp8_get_quant_method)
+"""

python/sglang/srt/layers/quantization/base_config.py

+# Adapted from https://raw.githubusercontent.com/vllm-project/vllm/v0.5.5/vllm/model_executor/layers/quantization/base_config.py
+
+from abc import ABC, abstractmethod
+from typing import Any, Dict, List, Optional
+
+import torch
+from torch import nn
+
+
+class QuantizeMethodBase(ABC):
+    """Base class for different quantized methods."""
+
+    @abstractmethod
+    def create_weights(
+        self, layer: torch.nn.Module, *weight_args, **extra_weight_attrs
+    ):
+        """Create weights for a layer.
+
+        The weights will be set as attributes of the layer."""
+        raise NotImplementedError
+
+    @abstractmethod
+    def apply(self, layer: torch.nn.Module, *args, **kwargs) -> torch.Tensor:
+        """Apply the weights in layer to the input tensor.
+
+        Expects create_weights to have been called before on the layer."""
+        raise NotImplementedError
+
+    def process_weights_after_loading(self, layer: nn.Module) -> None:
+        """Process the weight after loading.
+
+        This can be used for example, to transpose weights for computation.
+        """
+        return
+
+
+class QuantizationConfig(ABC):
+    """Base class for quantization configs."""
+
+    @abstractmethod
+    def get_name(self) -> str:
+        """Name of the quantization method."""
+        raise NotImplementedError
+
+    @abstractmethod
+    def get_supported_act_dtypes(self) -> List[torch.dtype]:
+        """List of supported activation dtypes."""
+        raise NotImplementedError
+
+    @classmethod
+    @abstractmethod
+    def get_min_capability(cls) -> int:
+        """Minimum GPU capability to support the quantization method.
+
+        E.g., 70 for Volta, 75 for Turing, 80 for Ampere.
+        This requirement is due to the custom CUDA kernels used by the
+        quantization method.
+        """
+        raise NotImplementedError
+
+    @staticmethod
+    @abstractmethod
+    def get_config_filenames() -> List[str]:
+        """List of filenames to search for in the model directory."""
+        raise NotImplementedError
+
+    @classmethod
+    @abstractmethod
+    def from_config(cls, config: Dict[str, Any]) -> "QuantizationConfig":
+        """Create a config class from the model's quantization config."""
+        raise NotImplementedError
+
+    @classmethod
+    def override_quantization_method(cls, hf_quant_cfg, user_quant) -> Optional[str]:
+        """
+        Detects if this quantization method can support a given checkpoint
+        format by overriding the user specified quantization method --
+        this method should only be overwritten by subclasses in exceptional
+        circumstances
+        """
+        return None
+
+    @staticmethod
+    def get_from_keys(config: Dict[str, Any], keys: List[str]) -> Any:
+        """Get a value from the model's quantization config."""
+        for key in keys:
+            if key in config:
+                return config[key]
+        raise ValueError(
+            f"Cannot find any of {keys} in the model's " "quantization config."
+        )
+
+    @staticmethod
+    def get_from_keys_or(config: Dict[str, Any], keys: List[str], default: Any) -> Any:
+        """Get a optional value from the model's quantization config."""
+        try:
+            return QuantizationConfig.get_from_keys(config, keys)
+        except ValueError:
+            return default
+
+    @abstractmethod
+    def get_quant_method(
+        self, layer: torch.nn.Module, prefix: str
+    ) -> Optional[QuantizeMethodBase]:
+        """Get the quantize method to use for the quantized layer.
+
+        Args:
+            layer: The layer for the quant method.
+            prefix: The full name of the layer in the state dict
+        Returns:
+            The quantize method. None if the given layer doesn't support quant
+            method.
+        """
+        raise NotImplementedError
+
+    @abstractmethod
+    def get_scaled_act_names(self) -> List[str]:
+        """Returns the activation function names that should be post-scaled.
+
+        For now, this is only used by AWQ.
+        """
+        raise NotImplementedError

python/sglang/srt/models/baichuan.py

@@ -34,7 +34,6 @@ from vllm.model_executor.layers.linear import (
     QKVParallelLinear,
     RowParallelLinear,
 )
-from vllm.model_executor.layers.quantization.base_config import QuantizationConfig
 from vllm.model_executor.layers.rotary_embedding import get_rope
 from vllm.model_executor.layers.vocab_parallel_embedding import (
     ParallelLMHead,
@@ -45,6 +44,7 @@ from vllm.model_executor.model_loader.weight_utils import default_weight_loader
 from sglang.srt.layers.activation import SiluAndMul
 from sglang.srt.layers.layernorm import RMSNorm
 from sglang.srt.layers.logits_processor import LogitsProcessor
+from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.layers.radix_attention import RadixAttention
 from sglang.srt.model_executor.forward_batch_info import InputMetadata
 

python/sglang/srt/models/chatglm.py

@@ -24,12 +24,6 @@ from torch import nn
 from torch.nn import LayerNorm
 from vllm.config import CacheConfig
 from vllm.distributed import get_tensor_model_parallel_world_size
-from vllm.model_executor.layers.linear import (
-    MergedColumnParallelLinear,
-    QKVParallelLinear,
-    RowParallelLinear,
-)
-from vllm.model_executor.layers.quantization.base_config import QuantizationConfig
 from vllm.model_executor.layers.rotary_embedding import get_rope
 from vllm.model_executor.layers.vocab_parallel_embedding import (
     ParallelLMHead,
@@ -40,7 +34,13 @@ from vllm.transformers_utils.configs import ChatGLMConfig
 
 from sglang.srt.layers.activation import SiluAndMul
 from sglang.srt.layers.layernorm import RMSNorm
+from sglang.srt.layers.linear import (
+    MergedColumnParallelLinear,
+    QKVParallelLinear,
+    RowParallelLinear,
+)
 from sglang.srt.layers.logits_processor import LogitsProcessor
+from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.layers.radix_attention import RadixAttention
 from sglang.srt.model_executor.forward_batch_info import InputMetadata
 

python/sglang/srt/models/commandr.py

@@ -50,21 +50,21 @@ from vllm.distributed import (
     get_tensor_model_parallel_rank,
     get_tensor_model_parallel_world_size,
 )
-from vllm.model_executor.layers.linear import (
-    MergedColumnParallelLinear,
-    QKVParallelLinear,
-    RowParallelLinear,
-)
-from vllm.model_executor.layers.quantization.base_config import QuantizationConfig
 from vllm.model_executor.layers.rotary_embedding import get_rope
 from vllm.model_executor.layers.vocab_parallel_embedding import VocabParallelEmbedding
 from vllm.model_executor.model_loader.weight_utils import default_weight_loader
-from vllm.model_executor.utils import set_weight_attrs
 
 from sglang.srt.layers.activation import SiluAndMul
+from sglang.srt.layers.linear import (
+    MergedColumnParallelLinear,
+    QKVParallelLinear,
+    RowParallelLinear,
+)
 from sglang.srt.layers.logits_processor import LogitsProcessor
+from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.layers.radix_attention import RadixAttention
 from sglang.srt.model_executor.forward_batch_info import InputMetadata
+from sglang.srt.utils import set_weight_attrs
 
 
 @torch.compile

python/sglang/srt/models/dbrx.py

@@ -27,12 +27,6 @@ from vllm.distributed import (
     tensor_model_parallel_all_reduce,
 )
 from vllm.model_executor.layers.fused_moe import fused_moe
-from vllm.model_executor.layers.linear import (
-    QKVParallelLinear,
-    ReplicatedLinear,
-    RowParallelLinear,
-)
-from vllm.model_executor.layers.quantization.base_config import QuantizationConfig
 from vllm.model_executor.layers.rotary_embedding import get_rope
 from vllm.model_executor.layers.vocab_parallel_embedding import (
     DEFAULT_VOCAB_PADDING_SIZE,
@@ -40,12 +34,18 @@ from vllm.model_executor.layers.vocab_parallel_embedding import (
     VocabParallelEmbedding,
 )
 from vllm.model_executor.model_loader.weight_utils import default_weight_loader
-from vllm.model_executor.utils import set_weight_attrs
 from vllm.transformers_utils.configs.dbrx import DbrxConfig
 
+from sglang.srt.layers.linear import (
+    QKVParallelLinear,
+    ReplicatedLinear,
+    RowParallelLinear,
+)
 from sglang.srt.layers.logits_processor import LogitsProcessor
+from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.layers.radix_attention import RadixAttention
 from sglang.srt.model_executor.forward_batch_info import InputMetadata
+from sglang.srt.utils import set_weight_attrs
 
 
 class DbrxRouter(nn.Module):

python/sglang/srt/models/deepseek.py

@@ -28,13 +28,6 @@ from vllm.distributed import (
     tensor_model_parallel_all_reduce,
 )
 from vllm.model_executor.layers.fused_moe import fused_moe
-from vllm.model_executor.layers.linear import (
-    MergedColumnParallelLinear,
-    QKVParallelLinear,
-    ReplicatedLinear,
-    RowParallelLinear,
-)
-from vllm.model_executor.layers.quantization.base_config import QuantizationConfig
 from vllm.model_executor.layers.rotary_embedding import get_rope
 from vllm.model_executor.layers.vocab_parallel_embedding import (
     ParallelLMHead,
@@ -44,7 +37,14 @@ from vllm.model_executor.model_loader.weight_utils import default_weight_loader
 
 from sglang.srt.layers.activation import SiluAndMul
 from sglang.srt.layers.layernorm import RMSNorm
+from sglang.srt.layers.linear import (
+    MergedColumnParallelLinear,
+    QKVParallelLinear,
+    ReplicatedLinear,
+    RowParallelLinear,
+)
 from sglang.srt.layers.logits_processor import LogitsProcessor
+from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.layers.radix_attention import RadixAttention
 from sglang.srt.model_executor.forward_batch_info import InputMetadata
 

python/sglang/srt/models/deepseek_v2.py

@@ -27,13 +27,6 @@ from vllm.distributed import (
     tensor_model_parallel_all_reduce,
 )
 from vllm.model_executor.layers.fused_moe import FusedMoE
-from vllm.model_executor.layers.linear import (
-    ColumnParallelLinear,
-    MergedColumnParallelLinear,
-    ReplicatedLinear,
-    RowParallelLinear,
-)
-from vllm.model_executor.layers.quantization.base_config import QuantizationConfig
 from vllm.model_executor.layers.rotary_embedding import get_rope
 from vllm.model_executor.layers.vocab_parallel_embedding import (
     ParallelLMHead,
@@ -43,7 +36,14 @@ from vllm.model_executor.model_loader.weight_utils import default_weight_loader
 
 from sglang.srt.layers.activation import SiluAndMul
 from sglang.srt.layers.layernorm import RMSNorm
+from sglang.srt.layers.linear import (
+    ColumnParallelLinear,
+    MergedColumnParallelLinear,
+    ReplicatedLinear,
+    RowParallelLinear,
+)
 from sglang.srt.layers.logits_processor import LogitsProcessor
+from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.layers.radix_attention import RadixAttention
 from sglang.srt.managers.schedule_batch import global_server_args_dict
 from sglang.srt.model_executor.forward_batch_info import InputMetadata

python/sglang/srt/models/exaone.py

@@ -23,12 +23,6 @@ import torch
 from torch import nn
 from vllm.config import CacheConfig
 from vllm.distributed import get_tensor_model_parallel_world_size
-from vllm.model_executor.layers.linear import (
-    MergedColumnParallelLinear,
-    QKVParallelLinear,
-    RowParallelLinear,
-)
-from vllm.model_executor.layers.quantization.base_config import QuantizationConfig
 from vllm.model_executor.layers.rotary_embedding import get_rope
 from vllm.model_executor.layers.vocab_parallel_embedding import (
     ParallelLMHead,
@@ -38,7 +32,13 @@ from vllm.model_executor.model_loader.weight_utils import default_weight_loader
 
 from sglang.srt.layers.activation import SiluAndMul
 from sglang.srt.layers.layernorm import RMSNorm
+from sglang.srt.layers.linear import (
+    MergedColumnParallelLinear,
+    QKVParallelLinear,
+    RowParallelLinear,
+)
 from sglang.srt.layers.logits_processor import LogitsProcessor, LogitsProcessorOutput
+from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.layers.radix_attention import RadixAttention
 from sglang.srt.model_executor.forward_batch_info import InputMetadata
 

python/sglang/srt/models/gemma.py

@@ -23,19 +23,19 @@ from torch import nn
 from transformers import PretrainedConfig
 from vllm.config import CacheConfig, LoRAConfig
 from vllm.distributed import get_tensor_model_parallel_world_size
-from vllm.model_executor.layers.linear import (
-    MergedColumnParallelLinear,
-    QKVParallelLinear,
-    RowParallelLinear,
-)
-from vllm.model_executor.layers.quantization.base_config import QuantizationConfig
 from vllm.model_executor.layers.rotary_embedding import get_rope
 from vllm.model_executor.layers.vocab_parallel_embedding import VocabParallelEmbedding
 from vllm.model_executor.model_loader.weight_utils import default_weight_loader
 
 from sglang.srt.layers.activation import GeluAndMul
 from sglang.srt.layers.layernorm import RMSNorm
+from sglang.srt.layers.linear import (
+    MergedColumnParallelLinear,
+    QKVParallelLinear,
+    RowParallelLinear,
+)
 from sglang.srt.layers.logits_processor import LogitsProcessor
+from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.layers.radix_attention import RadixAttention
 from sglang.srt.model_executor.forward_batch_info import InputMetadata
 

python/sglang/srt/models/gemma2.py

@@ -22,12 +22,6 @@ from torch import nn
 from transformers import PretrainedConfig
 from vllm.config import CacheConfig, LoRAConfig
 from vllm.distributed import get_tensor_model_parallel_world_size
-from vllm.model_executor.layers.linear import (
-    MergedColumnParallelLinear,
-    QKVParallelLinear,
-    RowParallelLinear,
-)
-from vllm.model_executor.layers.quantization.base_config import QuantizationConfig
 
 # from vllm.model_executor.layers.rotary_embedding import GemmaRotaryEmbedding
 from vllm.model_executor.layers.vocab_parallel_embedding import VocabParallelEmbedding
@@ -35,7 +29,13 @@ from vllm.model_executor.model_loader.weight_utils import default_weight_loader
 
 from sglang.srt.layers.activation import GeluAndMul
 from sglang.srt.layers.layernorm import GemmaRMSNorm
+from sglang.srt.layers.linear import (
+    MergedColumnParallelLinear,
+    QKVParallelLinear,
+    RowParallelLinear,
+)
 from sglang.srt.layers.logits_processor import LogitsProcessor
+from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.layers.radix_attention import RadixAttention
 from sglang.srt.model_executor.forward_batch_info import InputMetadata
 

python/sglang/srt/models/gpt_bigcode.py

@@ -23,17 +23,17 @@ from torch import nn
 from transformers import GPTBigCodeConfig
 from vllm.config import CacheConfig, LoRAConfig
 from vllm.distributed import get_tensor_model_parallel_world_size
-from vllm.model_executor.layers.linear import (
-    ColumnParallelLinear,
-    QKVParallelLinear,
-    RowParallelLinear,
-)
-from vllm.model_executor.layers.quantization.base_config import QuantizationConfig
 from vllm.model_executor.layers.vocab_parallel_embedding import VocabParallelEmbedding
 from vllm.model_executor.model_loader.weight_utils import default_weight_loader
 
 from sglang.srt.layers.activation import get_act_fn
+from sglang.srt.layers.linear import (
+    ColumnParallelLinear,
+    QKVParallelLinear,
+    RowParallelLinear,
+)
 from sglang.srt.layers.logits_processor import LogitsProcessor
+from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.layers.radix_attention import RadixAttention
 from sglang.srt.model_executor.forward_batch_info import InputMetadata
 

python/sglang/srt/models/grok.py

@@ -28,12 +28,6 @@ from vllm.distributed import (
     get_tensor_model_parallel_rank,
     get_tensor_model_parallel_world_size,
 )
-from vllm.model_executor.layers.linear import (
-    QKVParallelLinear,
-    ReplicatedLinear,
-    RowParallelLinear,
-)
-from vllm.model_executor.layers.quantization.base_config import QuantizationConfig
 from vllm.model_executor.layers.rotary_embedding import get_rope
 from vllm.model_executor.layers.vocab_parallel_embedding import (
     ParallelLMHead,
@@ -44,7 +38,13 @@ from vllm.model_executor.model_loader.weight_utils import default_weight_loader
 
 from sglang.srt.layers.fused_moe import FusedMoE
 from sglang.srt.layers.layernorm import RMSNorm
+from sglang.srt.layers.linear import (
+    QKVParallelLinear,
+    ReplicatedLinear,
+    RowParallelLinear,
+)
 from sglang.srt.layers.logits_processor import LogitsProcessor
+from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.layers.radix_attention import RadixAttention
 from sglang.srt.model_executor.forward_batch_info import InputMetadata
 

python/sglang/srt/models/internlm2.py

@@ -23,12 +23,6 @@ from torch import nn
 from transformers import PretrainedConfig
 from vllm.config import CacheConfig
 from vllm.distributed import get_tensor_model_parallel_world_size
-from vllm.model_executor.layers.linear import (
-    MergedColumnParallelLinear,
-    QKVParallelLinear,
-    RowParallelLinear,
-)
-from vllm.model_executor.layers.quantization.base_config import QuantizationConfig
 from vllm.model_executor.layers.rotary_embedding import get_rope
 from vllm.model_executor.layers.vocab_parallel_embedding import (
     ParallelLMHead,
@@ -38,7 +32,13 @@ from vllm.model_executor.model_loader.weight_utils import default_weight_loader
 
 from sglang.srt.layers.activation import SiluAndMul
 from sglang.srt.layers.layernorm import RMSNorm
+from sglang.srt.layers.linear import (
+    MergedColumnParallelLinear,
+    QKVParallelLinear,
+    RowParallelLinear,
+)
 from sglang.srt.layers.logits_processor import LogitsProcessor
+from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.layers.radix_attention import RadixAttention
 from sglang.srt.model_executor.forward_batch_info import InputMetadata
 

python/sglang/srt/models/llama.py

@@ -24,12 +24,6 @@ from torch import nn
 from transformers import LlamaConfig
 from vllm.config import CacheConfig
 from vllm.distributed import get_tensor_model_parallel_world_size
-from vllm.model_executor.layers.linear import (
-    MergedColumnParallelLinear,
-    QKVParallelLinear,
-    RowParallelLinear,
-)
-from vllm.model_executor.layers.quantization.base_config import QuantizationConfig
 from vllm.model_executor.layers.rotary_embedding import get_rope
 from vllm.model_executor.layers.vocab_parallel_embedding import (
     ParallelLMHead,
@@ -39,7 +33,13 @@ from vllm.model_executor.model_loader.weight_utils import default_weight_loader
 
 from sglang.srt.layers.activation import SiluAndMul
 from sglang.srt.layers.layernorm import RMSNorm
+from sglang.srt.layers.linear import (
+    MergedColumnParallelLinear,
+    QKVParallelLinear,
+    RowParallelLinear,
+)
 from sglang.srt.layers.logits_processor import LogitsProcessor, LogitsProcessorOutput
+from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.layers.radix_attention import RadixAttention
 from sglang.srt.layers.torchao_utils import apply_torchao_config_
 from sglang.srt.managers.schedule_batch import global_server_args_dict

python/sglang/srt/models/llama_classification.py

@@ -19,10 +19,10 @@ import torch
 from torch import nn
 from transformers import LlamaConfig
 from vllm.config import CacheConfig
-from vllm.model_executor.layers.quantization.base_config import QuantizationConfig
 from vllm.model_executor.model_loader.weight_utils import default_weight_loader
 
 from sglang.srt.layers.logits_processor import LogitsProcessorOutput
+from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.model_executor.forward_batch_info import InputMetadata
 from sglang.srt.models.llama import LlamaForCausalLM, LlamaModel
 

python/sglang/srt/models/llava.py

@@ -32,9 +32,9 @@ from transformers import (
 )
 from transformers.models.llava.modeling_llava import LlavaMultiModalProjector
 from vllm.config import CacheConfig
-from vllm.model_executor.layers.quantization.base_config import QuantizationConfig
 from vllm.model_executor.model_loader.weight_utils import default_weight_loader
 
+from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.mm_utils import (
     get_anyres_image_grid_shape,
     unpad_image,

python/sglang/srt/models/llavavid.py

@@ -23,9 +23,9 @@ from torch import nn
 from transformers import CLIPVisionModel, LlavaConfig
 from transformers.models.llava.modeling_llava import LlavaMultiModalProjector
 from vllm.config import CacheConfig
-from vllm.model_executor.layers.quantization.base_config import QuantizationConfig
 from vllm.model_executor.model_loader.weight_utils import default_weight_loader
 
+from sglang.srt.layers.quantization.base_config import QuantizationConfig
 from sglang.srt.model_executor.forward_batch_info import ForwardMode, InputMetadata
 from sglang.srt.models.llama import LlamaForCausalLM