- Removed AsyncOmniLLM from the main entry points as it is not supported yet.
- Updated the constructor of MultimodalOutputProcessor to set a default value for engine_core_output_type.
- Adjusted output type handling in various methods to utilize the new default engine_core_output_type for consistency.
- Translated comments from Chinese to English for better accessibility.
- Improved clarity of comments related to request handling and scheduling logic.
- Ensured comments align with the code functionality and maintain a uniform style.
- Introduced a static method `_dtype_to_name` to map PyTorch data types to their string representations.
- Updated the `dtype_str` assignments in the `OmniProcessor` class to utilize the new mapping method for improved readability and maintainability.
- Removed redundant imports of `torch` and `numpy` in `OmniProcessor` class.
- Improved comments in `parse_singleton_prompt_omni` function for clarity on token handling.
- Ensured `current_platform` is imported only once for better code organization.
- Eliminated redundant numpy import statements to streamline the code.
- Changed the return type of extract_multimodal_outputs from dict to tuple for better clarity on output structure.
- Added logging for exceptions during tensor movement to CPU in OmniRequestState and MultimodalOutputProcessor.
- Improved robustness by ensuring the output pipeline continues without crashing on errors.
- Updated comments for clarity on error handling behavior.
- Deleted the `has_kv_transfer_group` import as it was not utilized.
- Cleaned up commented-out code related to model methods, focusing on the forward method.
- Added a TODO comment to implement the diffuse method for additional model support.
Squashed commits:\n- 4e2d812 Add Qwen2.5-Omni model components\n- 351f833 load the thinker embedding from the weights, not rely on local .pt files\n- 2c32533 Refactor Qwen2.5-Omni model files\n- 9163a60 remove unused codes\n- 192bdf8 remove
- Renamed `DiffusionModelRunner` to `GPUDiffusionModelRunner` for better clarity in class purpose.
- Updated `DiffusionGPUWorker` to utilize the renamed `GPUDiffusionModelRunner`.
- Simplified output handling in `GPUDiffusionModelRunner` by removing unnecessary checks, enhancing code readability.
- Simplified the assignment of sampled_token_ids by removing the conditional check for "model_stage".
- Ensured consistent handling of sampled_token_ids for improved clarity and maintainability.
- Updated assertions and tensor management to correctly handle multimodal outputs in the `DiffusionModelRunner` class.
- Ensured that the output tensors are processed based on the type of multimodal outputs received, improving robustness and clarity in the code.
tzhouam