TensorRT-LLMs/cpp/include/tensorrt_llm
Robin Kobus 7b2818a47b
refactor: CreateNewDecoderRequests (#4452)
* refactor: CreateNewDecoderRequests

Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>

* refactor: Consolidate request generation in CreateNewDecoderRequests

- Removed the GenerateRequestOptions class and integrated its functionality into CreateNewDecoderRequests.
- Updated the constructor of CreateNewDecoderRequests to accept parameters for speculative decoding and normalization options.
- Modified the operator() method to handle request generation directly, improving code organization and reducing redundancy.
- Cleaned up associated includes and references throughout the codebase.

Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>

* refactor: Simplify request handling in CreateNewDecoderRequests

- Removed the generateRequestOptions method and integrated its logic directly into the operator() method.
- Updated the request generation process to improve clarity and reduce redundancy.
- Adjusted the return type to streamline the handling of batch slots, decoder requests, and sampling configurations.

Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>

* refactor: Enhance createDecoderRequests method in CreateNewDecoderRequests

- Updated the createDecoderRequests method to include additional parameters for decoder state and CUDA streams, improving flexibility in request handling.
- Removed redundant request generation logic from the operator() method, streamlining the process.
- Adjusted the newRequest method to utilize the updated decoder request structure, enhancing clarity and maintainability.

Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>

* refactor: Use MedusaBuffers instead of RuntimeBuffers in CreateNewDecoderRequests

- Updated references from RuntimeBuffers to MedusaBuffers across the CreateNewDecoderRequests class and its methods, enhancing clarity in buffer management.
- Adjusted method signatures and internal logic to accommodate the new MedusaBuffers type, ensuring compatibility with existing functionality.
- Cleaned up unnecessary includes and improved code organization for better maintainability.

Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>

* refactor: Update CreateNewDecoderRequests to use DecoderState and CudaStream parameters

- Modified method signatures in CreateNewDecoderRequests to replace GptDecoderBatched with runtime::decoder::DecoderState and added a separate CudaStream for the decoder.
- Adjusted the implementation of the operator() method to accommodate the new parameters, enhancing flexibility in request handling.
- Updated associated bindings in the pybind11 interface to reflect the changes in method signatures, ensuring consistency across the codebase.

Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>

* refactor: Update TRTLLMSampler to use refactored create_new_decoder_requests

- Updated the sampler.py to reflect changes in the request handling logic, replacing generate_request_options with create_new_decoder_requests for improved clarity and consistency.
- Updated bindings and method signatures for decoder stream handling.

Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>

* refactor: Update gptDecoderBatchedTest to use CreateNewDecoderRequests::newRequest

Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>

---------

Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
2025-05-23 22:54:37 +08:00
..
batch_manager refactor: CreateNewDecoderRequests (#4452) 2025-05-23 22:54:37 +08:00
common feat: NIXL interface integration (#3934) 2025-05-19 18:18:22 +08:00
deep_gemm Feat: add deep_gemm swapab Kernel (#4430) 2025-05-21 10:48:43 +08:00
executor Agent interface impl for NIXL (#4125) 2025-05-22 09:09:41 +08:00
kernels Update TensorRT-LLM (#2873) 2025-03-11 21:13:42 +08:00
layers v1.2 (#3082) 2025-03-26 23:31:29 +08:00
plugins/api Update TensorRT-LLM (#2532) 2024-12-04 21:16:56 +08:00
runtime fix: [nvbugs/5287097] Align PP layer distribution between pytorch and TRT flow. (#4399) 2025-05-19 14:25:36 -07:00