Eliminate weight copies: pass stacked checkpoint tensors directly
Memory optimization for MoE weight processing:
Before (3-4 copies of weights in memory):
1. Original checkpoint weights in layer.w13_weight (copy 1)
2. Per-expert permuted copies (copy 2)
3. torch.stack() in runner._ensure_stacked (copy 3)
4. make_b_k_major re-stride (copy 4)
5. Scales: permute then assemble_scales_3d_side un-permutes (wasted)
After (1-2 copies):
1. View checkpoint as fp4 (NO copy — byte-preserving view)
2. Pass (E, N, K) stacked tensor directly to runner
3. Runner permutes to (E, K, N) contiguous (copy 1), frees stacked ref
4. make_b_k_major re-strides (copy 2), frees (E, K, N) ref
5. Scales: already (N, K_sf) from checkpoint, call assembly directly
6. Free layer.w13_weight etc. immediately after extracting views
Also: assemble_scales_3d_side transposes (K_sf, N)→(N, K_sf) internally,
but checkpoint scales are ALREADY (N, K_sf). Skip the double-transpose
by calling assemble_raw_scales_2d3d_3d_side directly.
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