Fuse gdr preprocess#4656
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Pull request overview
This PR introduces a fused “preprocess” path for Gated Delta Rule inputs (q/k replication + optional q/k L2-norm + beta/g computation + init-token masking), and wires models/backends to pass raw (b, a, dt_bias, a_log_exp) instead of precomputed (beta, g).
Changes:
- Added a Triton kernel (
gated_delta_preprocess) and CUDA-backend hook to fuse q/k/b/a preprocessing whenuse_qk_l2norm_in_kernelis enabled. - Updated
GatedDeltacall path + Qwen3 models to pass raw(b, a, dt_bias, a_log_exp)and rely on backend preprocessing. - Added new kernel tests covering both 3D/4D
(b, a)layouts and decoding/prefill behavior.
Reviewed changes
Copilot reviewed 7 out of 7 changed files in this pull request and generated 5 comments.
Show a summary per file
| File | Description |
|---|---|
| tests/pytorch/kernel/test_gated_delta_preprocess.py | Adds tests validating fused preprocess outputs vs references/default prepare logic. |
| lmdeploy/pytorch/nn/gated_delta.py | Routes preprocessing through backend prepare_inputs; updates GatedDelta signature to accept raw (b, a, dt_bias, a_log_exp). |
| lmdeploy/pytorch/models/qwen3_next.py | Stops precomputing beta/g in-model; delegates to GatedDelta/backend. |
| lmdeploy/pytorch/models/qwen3_5.py | Stops precomputing beta/g in-model; delegates to GatedDelta/backend. |
| lmdeploy/pytorch/kernels/cuda/gated_delta_preprocess.py | New Triton-based fused preprocess kernel + Python wrapper. |
| lmdeploy/pytorch/backends/gated_delta_rule.py | Adds default prepare_inputs implementation to standardize preprocessing. |
| lmdeploy/pytorch/backends/cuda/gated_delta_rule.py | Overrides prepare_inputs to invoke fused preprocess kernel when enabled. |
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This PR fuse the preprocess of gated delta rule
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