Update Dockerfile for vllm wheel version and enhance input processing in Omni models. Added decoding for byte messages in async requests, included new metrics in benchmarks, and improved pause state handling in the scheduler. Refined input and output processing methods for better multimodal support and error handling.
Signed-off-by: tzhouam <tzhouam@connect.ust.hk>
- Eliminated the _process_embeds method and related imports from preprocess.py, streamlining the input preprocessing workflow.
- Updated the main processing logic to focus solely on token inputs, enhancing clarity and maintainability.
Signed-off-by: tzhouam <tzhouam@connect.ust.hk>
- Updated OmniInputProcessor to streamline input processing, including enhanced handling of prompt embeddings and additional information.
- Introduced OmniTextPrompt and OmniEmbedsInputs to support new input structures with optional metadata.
- Modified input preprocessing methods to accommodate new prompt types and ensure compatibility with multimodal inputs.
- Improved error handling and type checking for data parallel configurations.
Signed-off-by: [Your Name] <your.email@example.com>
Signed-off-by: tzhouam <tzhouam@connect.ust.hk>
- Introduced `OmniModelRunnerOutput` and `OmniRequestOutput` classes for handling multimodal outputs.
- Implemented `OmniEngineCoreRequest` and `OmniInputPreprocessor` to manage prompt embeddings and additional information.
- Created `OmniTokensPrompt`, `OmniTokenInputs`, and `OmniEmbedsPrompt` for enhanced token handling.
- Added parsing and preprocessing functions to support new input structures.
- Removed the obsolete `diffusion_engine.py` file as part of the refactor.
tzhouam