[dev] perf(moe): Refine gated delta net implementation#3040
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…NVIDIA#3040, NVIDIA#3220) - Add context parallel (CP) support to GatedDeltaNet via all-to-all communication (tensor_a2a_cp2hp / tensor_a2a_hp2cp) - Refine GDN implementation: replace causal_conv1d_fn with fla.modules.convolution, extract _prepare_qkv_for_gated_delta_rule and _compute_g_and_beta as @jit_fuser methods - Update TransformerConfig to remove CP==1 assertion for gated_delta_net and add linear_attention_type deprecation alias - Enable CP test cases in test_gated_delta_net.py and refactor correctness test to use shared _test_parallel_attention_correctness helper Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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What does this PR do ?
PR for main #3042
Changes
[b, s, h]shaped input, which helps us eliminate 1 transpose op.cu_seqlensarg, which is necessary for one of our future works, sequence packing.E2E correctness is checked as follows. (baseline is in pink, the new impl is in blue)

Perf gain
Model: Qwen3-Next-80B-A3B
E2E perf gain: ~1.04x
Timelines:
Baseline GDN forward (1.79 ms, redundant ops are in red boxes)

Optimized GDN forward (1.49 ms)

Baseline GDN backward (3.24 ms, the redundant op is in the red box)

Optimized GDN backward (3.01 ms)

Contribution process
flowchart LR A[Pre-checks] --> B[PR Tests] subgraph Code Review/Approval C1[Expert Review] --> C2[Final Review] end B --> C1 C2 --> D[Merge]Pre-checks
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