feat(moe): NSP-blocked expert dispatch for Qwen3MOE and GPT-OSS prefill

[vbaddi]

Adds NSP-parallel expert-blocked dispatch to the chunked prefill MoE path for Qwen3MOE and GPT-OSS, replacing the sequential per-expert loop with a batched packed-prefix approach.

Configuration:
  export EXPERT_BLOCKING_NUM_NSP=16   # default: 1 NSP per expert (best perf at T=256)
  export EXPERT_BLOCKING_NUM_NSP=8    # 2 NSPs per expert
  export EXPERT_BLOCKING_NUM_NSP=2    # for testing

Falls back to the original per-expert loop if num_experts % EXPERT_BLOCKING_NUM_NSP !=0.
EXPERT_BLOCKING_NUM_NSP=2 pytest tests/transformers/models/test_moe_prefill_blocked.py -v

Update (0429):
export EXPERT_BLOCKING_PACKED_CHUNK_SIZE=256 for chunk PL of 512

Update (0525):
Configuration is now compile-API driven:

1. num_cores controls NSP parallelism.
2. moe_prefill_packed_chunk_size controls packed chunk size.
3. No EXPERT_BLOCKING_NUM_NSP / EXPERT_BLOCKING_PACKED_CHUNK_SIZE env vars are required.

Example:

  qeff_model.compile(
      prefill_seq_len=512,
      ctx_len=...,
      num_cores=16,
      prefill_only=True,
      enable_chunking=True,
      moe_prefill_packed_chunk_size=256,
      ...
  )

Notes:

• Qwen3-MoE and GPT-OSS disaggregated serving examples are updated to use PL=512 and packed chunk size=256.
• The optimized path requires num_experts % num_cores == 0.
• Qwen3-MoE and GPT-OSS now use the same packed-chunk flow as the standalone benchmark.
• torch.clamp is retained for bench alignment, with tensor bounds to avoid QAIC Clip dtype issues.
• Subfunction-specific ReduceSum/Einsum cleanup is deferred and will be handled separately.

Validation:

pytest -q \
  tests/transformers/models/test_moe_prefill_blocked.py::test_qwen3moe_blocked_forward_parity \
  tests/transformers/models/test_moe_prefill_blocked.py::test_qwen3moe_prefill_chunked_subfunction_export_contains_cumsum_custom_ops \
  tests/transformers/models/test_moe_prefill_blocked.py::test_gptoss_blocked_forward_parity \
  tests/transformers/models/test_moe_prefill_blocked.py::test_gptoss_prefill_chunked_export_traces_packed_chunks

Also verified tiny non-subfunction QAIC compile for Qwen3-MoE and GPT-OSS with:

• prefill_seq_len=512
• moe_prefill_packed_chunk_size=256
• num_cores=2