o ۷i#@szddlmZmZddlmZddlZddlmZddlm Z ddl m Z ddl m Z Gdd d e ZeGd d d ZdS) ) dataclassfield)AnyN)Image) RequestOutput)ModelRunnerOutput)OmniPromptTypec@s@eZdZUdZdZeeejfdBe d<dZ e edBe d<dS)OmniModelRunnerOutputaMModel runner output for omni models. Extends the base ModelRunnerOutput with support for multimodal outputs that may be produced by non-autoregressive stages. Attributes: multimodal_outputs: Optional dictionary mapping modality names to output tensors (e.g., {"image": tensor, "audio": tensor}) Nmultimodal_outputskv_extracted_req_ids) __name__ __module__ __qualname____doc__r dictstrtorchTensor__annotations__r listrrG/home/ubuntu/vllm_env/lib/python3.10/site-packages/vllm_omni/outputs.pyr s  r c@s<eZdZUdZdZeed<dZeed<dZ e dBed<dZ eed <dZ e dBed <eed Zeejed <dZedBed <dZejdBed<eed Zeeefed<eed Zeeefed<ede d ed e ddfddZe     d0ded eejd edBdeeefdBdejdBdeeefdBd eddfddZedeeeffddZede fddZ edee dBfddZ!edeefddZ"edee dBfd d!Z#edefd"d#Z$ede dBfd$d%Z%edefd&d'Z&edefd(d)Z'edefd*d+Z(deeeffd,d-Z)defd.d/Z*dS)1OmniRequestOutputaqUnified request output for both pipeline stages and diffusion models. This class handles outputs from: 1. Multi-stage LLM pipelines (with stage_id, final_output_type, request_output) 2. Diffusion models (with images, prompt, metrics) Attributes: request_id: Unique identifier for this request finished: Whether generation is complete stage_id: Identifier of the stage that produced this output (pipeline mode) final_output_type: Type of output ("text", "image", "audio", "latents") request_output: The underlying RequestOutput from the stage (pipeline mode) images: List of generated PIL images (diffusion mode) prompt: The prompt used for generation (diffusion mode) latents: Optional tensor of latent representations (diffusion mode) metrics: Optional dictionary of generation metrics request_idTfinishedNstage_idtextfinal_output_typerequest_output)default_factoryimagespromptlatentsmetrics_multimodal_outputreturncCs|t|dd|||ddS)a Create output from pipeline stage. Args: stage_id: Stage identifier final_output_type: Type of output request_output: The stage's output Returns: OmniRequestOutput configured for pipeline mode rrT)rrrrr)getattr)clsrrrrrr from_pipeline@s zOmniRequestOutput.from_pipelineimagemultimodal_outputc Cs |||||||p i|p iddS)aRCreate output from diffusion model. Args: request_id: Request identifier images: Generated images prompt: The prompt used metrics: Generation metrics latents: Optional latent tensors Returns: OmniRequestOutput configured for diffusion mode T)rrr!r"r#r$r%rr)r(rr!r"r$r#r+rrrrfrom_diffusionYsz OmniRequestOutput.from_diffusioncCs|jdur|jSt|jtr|jn|jg}|D]%}t|dgD]}t|dd}r/|Sqt|dd}r<|Sq|jS)zReturn multimodal output from the underlying request output or local field. For pipeline outputs, this checks completion outputs first, then request_output. For diffusion outputs, this returns the local _multimodal_output field. Noutputsr+)rr% isinstancerr')selfrequest_outputsreq_outoutputmmrrrr+{s  z#OmniRequestOutput.multimodal_outputcCs t|jS)z&Return the number of generated images.)lenr!r/rrr num_imagess zOmniRequestOutput.num_imagescC|jdur t|jddSdS)zReturn prompt token IDs from the underlying request output. This property is required for compatibility with vLLM's streaming chat completion generator which checks res.prompt_token_ids. Nprompt_token_idsrr'r5rrrr8 z"OmniRequestOutput.prompt_token_idscCs|jdur t|jdgSgS)zReturn outputs from the underlying request output. This property is required for compatibility with vLLM's streaming and non-streaming chat completion generators. Nr-r9r5rrrr-r:zOmniRequestOutput.outputscCr7)zCReturn encoder prompt token IDs from the underlying request output.Nencoder_prompt_token_idsr9r5rrrr; z*OmniRequestOutput.encoder_prompt_token_idscCr7)z:Return prompt logprobs from the underlying request output.Nprompt_logprobsr9r5rrrr=r<z!OmniRequestOutput.prompt_logprobscCr7)zBReturn number of cached tokens from the underlying request output.Nnum_cached_tokensr9r5rrrr>r<z#OmniRequestOutput.num_cached_tokenscCr7)z=Return KV transfer params from the underlying request output.Nkv_transfer_paramsr9r5rrrr?r<z$OmniRequestOutput.kv_transfer_paramscCst|jdkp |jdkS)z*Check if this is a diffusion model output.rr*)r4r!rr5rrris_diffusion_outputsz%OmniRequestOutput.is_diffusion_outputcCs|jduo |jduS)z)Check if this is a pipeline stage output.N)rrr5rrris_pipeline_outputsz$OmniRequestOutput.is_pipeline_outputcCsJ|j|j|jd}|jr||j|j|jd|jr#|d|j i|S)z-Convert to dictionary for JSON serialization.)rrr)r6r"r$r) rrrr@updater6r"r$rAr)r/resultrrrto_dicts"zOmniRequestOutput.to_dictc Cs|jr dt|jdnd}d|jd|jd|jd|jd|jd |d |jd |jd |j d |j g }dd |dS)zBCustom repr to properly show image count instead of image objects.[z PIL Images]z[]z request_id=z finished=z stage_id=zfinal_output_type=zrequest_output=zimages=zprompt=zlatents=zmetrics=zmultimodal_output=zOmniRequestOutput(z, )) r!r4rrrrrr"r#r$r%join)r/ images_reprpartsrrr__repr__s          zOmniRequestOutput.__repr__)NNNNr*)+r r rrrrrrboolrintrrrrrr!rr"rr#rrrr$rr% classmethodr)r,propertyr+r6r8r-r;r=r>r?r@rArDrJrrrrrs      !  r) dataclassesrrtypingrrPILr vllm.outputsrvllm.v1.outputsrvllm_omni.inputs.datarr rrrrrs