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Rename Spark3 to Spark2.5 (#36416)

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This commit is contained in:
KnightYao
2026-08-26 00:04:46 -07:00
committed by GitHub
parent 3ce4f957eb
commit 7ef49e8f7d
7 changed files with 43 additions and 43 deletions
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python/sglang/srt/configs/__init__.py
+2 -2
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@@ -57,7 +57,7 @@ from sglang.srt.configs.qwen3_5 import (
)
from sglang.srt.configs.qwen3_asr import Qwen3ASRConfig
from sglang.srt.configs.qwen3_next import Qwen3NextConfig
from sglang.srt.configs.spark3 import Spark3Config
from sglang.srt.configs.spark2_5 import Spark2_5Config
from sglang.srt.configs.step3_vl import (
Step3TextConfig,
Step3VisionEncoderConfig,
@@ -118,7 +118,7 @@ __all__ = [
"MiniCPMHybridConfig",
"Step3p5Config",
"MiniMaxM3VLConfig",
"Spark3Config",
"Spark2_5Config",
"Step3p7Config",
"Qwen3ASRConfig",
"InklingAudioConfig",
python/sglang/srt/configs/spark3.py → python/sglang/srt/configs/spark2_5.py
+3 -3
View File
@@ -3,9 +3,9 @@ from typing import Any, Optional
from transformers.configuration_utils import PretrainedConfig
class Spark3Config(PretrainedConfig):
model_type = "spark3"
architectures = ["Spark3ForCausalLM"]
class Spark2_5Config(PretrainedConfig):
model_type = "spark2_5"
architectures = ["Spark2_5ForCausalLM"]
def __init__(
self,
python/sglang/srt/function_call/function_call_parser.py
+2 -2
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@@ -43,7 +43,7 @@ from sglang.srt.function_call.poolside_v1_detector import PoolsideV1Detector
from sglang.srt.function_call.pythonic_detector import PythonicDetector
from sglang.srt.function_call.qwen3_coder_detector import Qwen3CoderDetector
from sglang.srt.function_call.qwen25_detector import Qwen25Detector
from sglang.srt.function_call.spark3_detector import Spark3Detector
from sglang.srt.function_call.spark25_detector import Spark25Detector
from sglang.srt.function_call.step3_detector import Step3Detector
from sglang.srt.function_call.trinity_detector import TrinityDetector
from sglang.srt.function_call.utils import (
@@ -88,7 +88,7 @@ class FunctionCallParser:
"qwen": Qwen25Detector,
"qwen25": Qwen25Detector,
"qwen3_coder": Qwen3CoderDetector,
"spark": Spark3Detector,
"spark25": Spark25Detector,
"step3": Step3Detector,
"step3p5": Qwen3CoderDetector,
"minimax-m2": MinimaxM2Detector,
python/sglang/srt/function_call/spark3_detector.py → python/sglang/srt/function_call/spark25_detector.py
+9 -9
View File
@@ -26,7 +26,7 @@ ARG_PAIR_PATTERN = re.compile(
@dataclass(frozen=True)
class _Spark3ToolCall:
class _Spark2_5ToolCall:
name: str
arguments: dict[str, Any]
@@ -57,7 +57,7 @@ def _get_param_type(tools: list[Tool], function_name: str, param_name: str) -> s
def _convert_value(value: str, param_type: str) -> Any:
"""Convert Spark3 XML text according to the model's tool protocol."""
"""Convert Spark2_5 XML text according to the model's tool protocol."""
if value.lower() == "null":
return None
@@ -83,7 +83,7 @@ def _convert_value(value: str, param_type: str) -> Any:
return value
def _parse_tool_call_xml(tool_xml: str, tools: list[Tool]) -> _Spark3ToolCall | None:
def _parse_tool_call_xml(tool_xml: str, tools: list[Tool]) -> _Spark2_5ToolCall | None:
if not tool_xml.startswith(TOOL_CALL_BEGIN) or not tool_xml.endswith(TOOL_CALL_END):
return None
@@ -102,7 +102,7 @@ def _parse_tool_call_xml(tool_xml: str, tools: list[Tool]) -> _Spark3ToolCall |
raw_value,
_get_param_type(tools, function_name, key),
)
return _Spark3ToolCall(name=function_name, arguments=arguments)
return _Spark2_5ToolCall(name=function_name, arguments=arguments)
def _partial_marker_suffix_length(text: str, marker: str) -> int:
@@ -113,8 +113,8 @@ def _partial_marker_suffix_length(text: str, marker: str) -> int:
return 0
class Spark3Detector(BaseFormatDetector):
"""Detector for Spark3's XML-KV tool-call format.
class Spark25Detector(BaseFormatDetector):
"""Detector for Spark2_5's XML-KV tool-call format.
Wire format::
@@ -137,7 +137,7 @@ class Spark3Detector(BaseFormatDetector):
def _build_item(
self,
parsed: _Spark3ToolCall,
parsed: _Spark2_5ToolCall,
tools: list[Tool],
tool_index: int,
) -> ToolCallItem | None:
@@ -153,7 +153,7 @@ class Spark3Detector(BaseFormatDetector):
)
def _record_streamed_item(
self, parsed: _Spark3ToolCall, item: ToolCallItem
self, parsed: _Spark2_5ToolCall, item: ToolCallItem
) -> None:
self.prev_tool_call_arr.append(
{"name": parsed.name, "arguments": parsed.arguments}
@@ -259,5 +259,5 @@ class Spark3Detector(BaseFormatDetector):
def structure_info(self) -> _GetInfoFunc:
raise NotImplementedError(
"Spark3 XML arguments cannot be represented by legacy structural tags"
"Spark2_5 XML arguments cannot be represented by legacy structural tags"
)
python/sglang/srt/models/spark3.py → python/sglang/srt/models/spark2_5.py
+15 -15
View File
@@ -31,7 +31,7 @@ from sglang.srt.platforms import current_platform
from sglang.srt.runtime_context import get_parallel
from sglang.srt.utils import add_prefix, make_layers
Spark3Config = None
Spark2_5Config = None
logger = logging.getLogger(__name__)
@@ -42,7 +42,7 @@ def _get_attention_sliding_window_size(config):
return config.sliding_window - 1
class Spark3MLP(nn.Module):
class Spark2_5MLP(nn.Module):
def __init__(
self,
hidden_size: int,
@@ -80,7 +80,7 @@ class Spark3MLP(nn.Module):
return x
class Spark3Attention(nn.Module):
class Spark2_5Attention(nn.Module):
def __init__(
self,
hidden_size: int,
@@ -169,7 +169,7 @@ class Spark3Attention(nn.Module):
is_neox_style=True,
)
if layer_type not in ("sliding_attention", "full_attention"):
raise ValueError(f"Unsupported Spark3 layer_type: {layer_type}")
raise ValueError(f"Unsupported Spark2_5 layer_type: {layer_type}")
sliding_window_size = (
sliding_window if layer_type == "sliding_attention" else -1
)
@@ -209,7 +209,7 @@ class Spark3Attention(nn.Module):
return output
class Spark3DecoderLayer(nn.Module):
class Spark2_5DecoderLayer(nn.Module):
"""A single transformer layer.
Transformer layer takes input with size [s, b, h] and returns an
@@ -218,7 +218,7 @@ class Spark3DecoderLayer(nn.Module):
def __init__(
self,
config: Spark3Config,
config: Spark2_5Config,
layer_id: int = 0,
quant_config: Optional[QuantizationConfig] = None,
prefix: str = "",
@@ -234,7 +234,7 @@ class Spark3DecoderLayer(nn.Module):
if partial_rotary_factor is None:
partial_rotary_factor = 1.0
self.self_attn = Spark3Attention(
self.self_attn = Spark2_5Attention(
hidden_size=config.hidden_size,
num_heads=config.num_attention_heads,
num_kv_heads=config.num_key_value_heads,
@@ -253,7 +253,7 @@ class Spark3DecoderLayer(nn.Module):
)
# MLP
self.mlp = Spark3MLP(
self.mlp = Spark2_5MLP(
config.hidden_size,
intermediate_size=config.intermediate_size,
quant_config=quant_config,
@@ -290,10 +290,10 @@ class Spark3DecoderLayer(nn.Module):
return hidden_states, residual
class Spark3Model(nn.Module):
class Spark2_5Model(nn.Module):
def __init__(
self,
config: Spark3Config,
config: Spark2_5Config,
quant_config: Optional[QuantizationConfig] = None,
prefix: str = "",
) -> None:
@@ -315,7 +315,7 @@ class Spark3Model(nn.Module):
self.layers, self.start_layer, self.end_layer = make_layers(
config.num_hidden_layers,
lambda idx, prefix: Spark3DecoderLayer(
lambda idx, prefix: Spark2_5DecoderLayer(
layer_id=idx,
config=config,
quant_config=quant_config,
@@ -377,10 +377,10 @@ class Spark3Model(nn.Module):
return hidden_states
class Spark3ForCausalLM(nn.Module):
class Spark2_5ForCausalLM(nn.Module):
def __init__(
self,
config: Spark3Config,
config: Spark2_5Config,
quant_config: Optional[QuantizationConfig] = None,
prefix: str = "",
) -> None:
@@ -388,7 +388,7 @@ class Spark3ForCausalLM(nn.Module):
self.pp_group = get_pp_group()
self.config = config
self.quant_config = quant_config
self.model = Spark3Model(
self.model = Spark2_5Model(
config, quant_config=quant_config, prefix=add_prefix("model", prefix)
)
@@ -561,4 +561,4 @@ class Spark3ForCausalLM(nn.Module):
return _get_attention_sliding_window_size(self.config)
EntryClass = [Spark3ForCausalLM]
EntryClass = [Spark2_5ForCausalLM]
python/sglang/srt/utils/hf_transformers/common.py
+2 -2
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@@ -66,7 +66,7 @@ from sglang.srt.configs import (
Qwen3_5MoeTextConfig,
Qwen3_5TextConfig,
Qwen3NextConfig,
Spark3Config,
Spark2_5Config,
Step3p5Config,
Step3p7Config,
Step3VLConfig,
@@ -103,7 +103,7 @@ _CONFIG_REGISTRY: Dict[str, Type[PretrainedConfig]] = {
LocateAnythingConfig,
InternVLChatConfig,
LagunaConfig,
Spark3Config,
Spark2_5Config,
Step3VLConfig,
LongcatFlashConfig,
Olmo3Config,