Use max example seq_len when exporting Qwen3.5 MoE

The previous example used T=2, which caused AOTI to compile the
chunk_gated_delta_rule kernel for a single chunk (NT=1). At runtime,
prompts longer than 64 tokens (requiring NT>1 chunks) failed with
"Error resizing tensor at input 0". Using max_seq_len-1 as the
example ensures AOTI generalizes intermediate buffer sizes for the
full sequence length range.

Comparison against original export (tq4_sdpa fused kernel)
on H100 (Qwen3.5-35B-A3B, HQQ-INT4, max_seq_len=4096, 5 runs median):

                Original (tq4_sdpa)  Baseline (Triton SDPA)
  Decode tok/s       68.4               61.7
  Prefill tok/s     275.7              378.2

Baseline prefill is 1.37x faster; decode is 0.90x (tq4_sdpa's fused
decode kernel is faster than the tiled Triton SDPA at L_q=1). The
split-K commit addresses the decode gap.

Author: digantdesai

examples/models/qwen3_5_moe/export.py

@@ -398,9 +398,13 @@ def export_and_lower(model, config, args):
     # -O0 compiles ~8x faster than -O1 with no measurable runtime impact.
     inductor_config.aot_inductor.compile_wrapper_opt_level = "O0"
 
-    # Dynamic shapes
-    example_tokens = torch.tensor([[0, 1]], dtype=torch.long)
-    example_input_pos = torch.tensor([0, 1], dtype=torch.long)
+    # Dynamic shapes — example T must equal max_seq_len-1 so AOTI compiles
+    # kernels (especially chunk_gated_delta_rule with CHUNK_SIZE=64) for the
+    # full range of sequence lengths. Smaller examples cause AOTI to bake in
+    # intermediate buffer sizes that reject longer prompts at runtime.
+    example_seq_len = config.max_seq_len - 1
+    example_tokens = torch.zeros((1, example_seq_len), dtype=torch.long)
+    example_input_pos = torch.arange(example_seq_len, dtype=torch.long)
     seq_dim = Dim("seq_len", min=1, max=config.max_seq_len - 1)
     dynamic_shapes = ({1: seq_dim}, {0: seq_dim})