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chore: import upstream snapshot with attribution
2026-07-13 12:38:16 +08:00

60 lines
1.8 KiB
Python

from sglang.multimodal_gen.runtime.pipelines_core import LoRAPipeline
from sglang.multimodal_gen.runtime.pipelines_core.composed_pipeline_base import (
ComposedPipelineBase,
)
from sglang.multimodal_gen.runtime.pipelines_core.stages import DenoisingStage
from sglang.multimodal_gen.runtime.pipelines_core.stages.model_specific_stages.glm_image import (
GlmImageAR,
GlmImageBeforeDenoisingStage,
)
from sglang.multimodal_gen.runtime.server_args import ServerArgs
from sglang.multimodal_gen.runtime.utils.logging_utils import init_logger
logger = init_logger(__name__)
class GlmImagePipeline(LoRAPipeline, ComposedPipelineBase):
pipeline_name = "GlmImagePipeline"
_required_config_modules = [
"text_encoder",
"tokenizer",
"vae",
"vision_language_encoder",
"processor",
"transformer",
"scheduler",
]
def create_pipeline_stages(self, server_args: ServerArgs):
self.add_stage(
GlmImageAR(
processor=self.get_module("processor"),
vision_language_encoder=self.get_module("vision_language_encoder"),
),
"glm_image_ar",
)
self.add_stage(
GlmImageBeforeDenoisingStage(
vae=self.get_module("vae"),
text_encoder=self.get_module("text_encoder"),
tokenizer=self.get_module("tokenizer"),
transformer=self.get_module("transformer"),
scheduler=self.get_module("scheduler"),
),
"glm_image_before_denoising_stage",
)
self.add_stage(
DenoisingStage(
transformer=self.get_module("transformer"),
scheduler=self.get_module("scheduler"),
),
)
self.add_standard_decoding_stage()
EntryClass = [GlmImagePipeline]