Fix CUDA Attention dispatch: skip MEA when head_size != v_head_size in GQA

[justinchuby]

Summary

Problem

The Memory-Efficient Attention (MEA) path crashes with cudaErrorMisalignedAddress when:

• GQA mode (q_num_heads != kv_num_heads)
• head_size != v_head_size (e.g., Q.head_dim=256, K.head_dim=512)
• seq_len >= 4 (Flash Attention not eligible due to attention mask)

This is because MEA's LaunchUngroup requires equal head sizes, but the dispatch logic only checked this constraint for the past_key case (line 1380), not the general GQA case.

Fix

Skip MEA for GQA when head sizes differ. The Unfused Attention fallback handles this correctly.

Affected Models

Gemma4 (google/gemma-4-e2b-it) with KV sharing:

• Layers 15-34 borrow K,V from source layers
• Q projection: 1536 → 2048 (8 heads × 256)
• K/V from source: [batch, 1, seq, 512]
• head_size = 256, v_head_size = 512

Testing

Minimal repro (from #28357):

# Attention(Q=[1,S,2048], K=[1,S,512], V=[1,S,512], q_num_heads=8, kv_num_heads=1)
# Before fix: seq=4+ crashes with misaligned address
# After fix: all seq lengths work

Full Gemma4 decoder (35 layers, 15 GQA + 20 standard Attention):

• Prefill seq=32: ✅
• Decode seq=1: ✅

Fixes #28357