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vllm-omni/vllm_omni/deploy/glm_image.yaml
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2026-04-22 15:09:28 +08:00

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# GLM-Image deploy: AR (stage 0) + Diffusion (stage 1).
# Topology declared in vllm_omni/model_executor/models/glm_image/pipeline.py.
#
# Fields omitted from a stage fall back to StageDeployConfig dataclass
# defaults (see vllm_omni/config/stage_config.py). Pipeline-wide settings
# (trust_remote_code, distributed_executor_backend, etc.) use DeployConfig
# defaults unless overridden here.
async_chunk: false
stages:
# Stage 0: AR Model (GlmImageForConditionalGeneration)
# Generates prior_token_ids for conditioning the diffusion process.
- stage_id: 0
max_num_seqs: 1
gpu_memory_utilization: 0.6
enforce_eager: false
max_num_batched_tokens: 32768
devices: "0"
default_sampling_params:
temperature: 0.9
top_p: 0.75
top_k: 16512
stop_token_ids: [16385]
seed: 42
detokenize: false
# Stage 1: Diffusion (DiT + VAE)
# Receives prior_token_ids from AR, performs denoising + VAE decode.
- stage_id: 1
max_num_seqs: 1
enforce_eager: true
devices: "1"
default_sampling_params:
seed: 42
num_inference_steps: 50
guidance_scale: 1.5
height: 1024
width: 1024