[Bugfix][Kernel] Pass the correct expert count to WNA16 MoE block config

[morluto]

Purpose

The CUDA and Triton WNA16 MoE dispatchers passed B.size(1) as both
size_n and num_experts when selecting a block configuration. For the
expert weight tensor, B.size(0) is the expert count and B.size(1) is
the output dimension.

The incorrect expert count feeds the CUDA num_m_blocks heuristic and
can select different BLOCK_SIZE_N and BLOCK_SIZE_K values. The
Triton selector currently returns before using num_experts, but this
PR fixes both call sites to preserve the argument contract.

A regression test invokes the CUDA dispatcher with E=8 and N=1024
while mocking only the native kernel launch. It verifies that the
dispatcher selects:

BLOCK_SIZE_N=128
BLOCK_SIZE_K=512

Passing N=1024 as the expert count instead would select
BLOCK_SIZE_N=1024 and BLOCK_SIZE_K=256.

This PR does not change the block-selection heuristic itself.

Duplicate search found no open issue or PR for this expert-dimension
error. Related PRs #44563 and #40547 address different WNA16 block
configuration problems.

Test Plan

Run the focused WNA16 dispatcher regression test:

.venv/bin/python -m pytest tests/kernels/moe/test_moe.py \
  -k wna16_cuda_block_config -v

Test Result

1 passed, 972 deselected, 14 warnings in 2.53s

The warnings are unrelated TorchScript deprecation warnings.

No model evaluation was run because this change affects kernel
configuration selection, not model output semantics.

No performance benchmark was run, and this PR does not claim a measured
speedup.

AI assistance was used in preparing this change.

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