[autotune] Add observed heuristic seeds#2378
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Extends observed-heuristics with:
1. Three quantized-matmul kernel classes: matmul_int4, matmul_int16,
matmul_fp4. classify_runtime_kernel now takes an optional kernel
arg to fingerprint int4 vs fp4 from kernel source (their tensor
shapes and dtypes are identical). Quantized kernels lack the
"matmul" workload trait (manual outer-product + sum instead of
hl.dot), so a secondary classification branch triggers on
{"reduction","sum_reduction"} + packed-int8 signature.
2. Top-level `fallbacks` block in observed_heuristics_b200.json used
when exact-bucket rule lookup misses. Shape-groups per family
are returned by _fallback_group_for_class:
- matmul: small_m / small_n / small_k / balanced / rect
- row_*: short / narrow / wide / square
- elementwise: tiny / mid / huge
- attention: short_seq / long_seq / small_head / mid_seq
3. JSON now has 30 rules (9 existing attention/matmul/row_softmax
+ 21 new quantized-GEMM) and 15 fallback entries (5 groups * 3
quantized kernels). Quantized rules are keyed on the matmul
bucketing scheme already used for regular matmul, with the
dtype slot separating the kernels (int4/fp4/int16 weight
operand all produce arg0_dtype=bf16 -> dtype_family=fp16_bf16).
Pre-existing attention/matmul/row_softmax rules resolve identically.
test_observed_heuristics.py: all 4 tests pass.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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