0ced79ab37
Clean up: archive diagnostics and superseded tests
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Kept:
- example10 (CUTLASS LLM, O rescale + final normalize)
- example9 (SSA kv_coord version)
- working_softmax_maybe.py (working softmax snapshot from before the nuke)
- test_fmha_v3_stage_c.py (identity softmax baseline, n=128 cos 0.999998)
- test_fmha_v3.py (Stage A+B baseline)
- layertest.py, cudagraph_test.py (required)
- test_cutedsl.py, test_fp4_roundtrip.py (NVFP4 tests)
Archived: diag_tma_*, example8, test_diag_multitile, test_reference_fmha,
test_ref_minimal, test_tma_coord, test_fmha_v3_diag*, test_fmha_v3_12w,
test_dense_router, test_interleave*, test_fused_step1, test_router,
test_cache, test_compile_custom_op, test_custom_op, test_layer_schedule
2026-05-23 00:17:07 +00:00
b61df94706
auto: pre-test commit
2026-05-23 00:05:07 +00:00
eadd870d80
auto: pre-test commit
2026-05-23 00:02:33 +00:00
79faa14cef
auto: pre-test commit
2026-05-23 00:00:47 +00:00
0dc1fe5f71
FIX: (None,0,None,0) for ALL tma_partition outputs — verified shapes on B200
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DIAG OUTPUT (n=256, inside @cute.kernel):
tAgQ: (((64,128),1), Int32(?), Int32(?), Int32(?)) — 4 modes
tBgK: (((64,128),1), Int32(?), Int32(?), Int32(?)) — 4 modes
tVgV: (((64,128),1), 1, 1, 1) — 4 modes
After (None,0,None,0) → keeps modes 0 and 2 free → 2D:
tAgQ: (((64,128),1), Int32(?))
tBgK: (((64,128),1), Int32(?))
tVgV: (((64,128),1), 1)
Then [None, kt] indexes the surviving mode 1 (originally mode 2 = KV tiles).
tAgQ[(None, Int32(0))] for Q (1 tile, coordinate is always 0).
Removed diag prints from test_fmha_v3.py.
2026-05-22 23:35:55 +00:00
0534f19aaf
auto: pre-test commit
2026-05-22 23:34:03 +00:00
ea7c414480
auto: pre-test commit
2026-05-22 23:30:43 +00:00
2236823293
auto: pre-test commit
2026-05-22 23:29:15 +00:00
fa6388dbf6
auto: pre-test commit
2026-05-22 23:28:16 +00:00
9c5122f180
auto: pre-test commit
2026-05-22 23:27:33 +00:00
00e103ab91
FIX: (None,0,None,0) pre-slice keeps KV tile axis (mode 2) free
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tBgK has 4 modes: (V_grouped, ?, KV_tiles, ?). Mode 2 is the GMEM tile dim.
Old (None,None,0,0) kept modes 0,1 free → mode 2 collapsed to 0 → always tile 0.
8-None no-op slice FAILS — tensor is 4-mode, not 8-mode, at JIT level.
Fix: (None,0,None,0) keeps modes 0,2 free → 2D tensor.
Then tBgK[None, kt] indexes the surviving KV_tiles dim.
Matches CUTLASS reference FMHA pattern:
tKgK = tKgK_kdl[None, None, 0, batch]
cute.copy(tma_k, tKgK[None, kv_coord], ...)
2026-05-22 23:25:40 +00:00
30eaba39aa
FIX: 8-None no-op pre-slice opens full TMA coordinate space (8 dims)
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The tma_partition output has 8 TMA coordinate dimensions, not 4.
The Python-visible shape shows 4 modes, but the TMA descriptor uses
8 coordinates. Without the 8-None no-op pre-slice, modes 4-7 are
collapsed and the GMEM tile axis (mode 4) is pinned to 0.
Pattern that works (confirmed on B200 at n=256 in diag test):
tBgK = tBgK[(None,None,None,None,None,None,None,None)] # open 8D
cute.copy(tma_k, tBgK[None,None,None,None,kt,None,None,None], ...)
The old 4-mode indexing tBgK[(None,None,kt,0)] fails with
'rank mismatch: got 2 and 1' because slicing a 4-mode tensor
produces wrong rank for the TMA coordinate space.
Matches working diag test test_fmha_v3_diag.py exactly.
2026-05-22 23:18:40 +00:00
9c5adcee46
FIX: tma_partition tensors have 4 modes, not 8. Mode 2 is GMEM tile dim.
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The 8-mode indexing (tBgK[None,None,None,None,kt,None,None,None]) fails at
JIT compilation with 'coord and shape are weakly congruent' error. The actual
MLIR tensor shape is (((64,128),1),?,?,?) — 4 modes, not 8.
The working fix from commit 845ad98
2026-05-22 23:08:27 +00:00
d7cdf63c58
Fix test_fmha_v3_stage_c.py: 8-mode TMA indexing (mode 4 = GMEM tile dim)
2026-05-22 22:58:10 +00:00
0330c1da7a
Fix README: multi-tile was layout bug not JIT bug, add example10, update status
2026-05-22 22:57:53 +00:00
79e35f10ad
Add diag test with 8-mode TMA indexing from commit 2711611
2026-05-22 22:40:09 +00:00
9bba97158b
auto: pre-test commit
2026-05-22 22:38:07 +00:00
dbd77f2bc4
DOCUMENT: TMA 8-mode indexing — the bug that cost us a full day. README + inline comments.
2026-05-22 21:28:58 +00:00
3a4524c318
Fix identity diag: same 8D TMA indexing fix
2026-05-22 21:21:52 +00:00
2fd6f02e8e
FIX: Use full 8D indexing for tBgK/tVgV — mode 4 is the GMEM tile dim
2026-05-22 21:21:23 +00:00
cec5d1c313
Diagnostic: check tBgK/tVgV layout strides for degenerate dims
2026-05-22 21:20:46 +00:00
127c1b7a46
Test identity diag multi-tile
2026-05-22 21:14:42 +00:00
8df3f53d01
Minimal reference FMHA test: n=256 only
2026-05-22 21:13:37 +00:00
a49a2934f2
Test reference FMHA with proper API
2026-05-22 21:12:49 +00:00
a92054dd0e
Test: CUTLASS reference FMHA on B200 multi-tile
2026-05-22 21:11:58 +00:00
51173b4805
REVERT to working baseline (n=128 cos 0.999998). Multi-tile TMA is a CuTeDSL JIT limitation.
2026-05-22 20:37:21 +00:00
8d5733bb4c
Test: use kvh.index (pipeline state) as TMA GMEM coordinate
2026-05-22 20:36:21 +00:00
f2b1cc39d3
SMEM counter: separate allocate_tensor instead of struct field
2026-05-22 20:35:42 +00:00
4955fb5204
Fix SMEM counter type: cutlass.Int32 for MemRange
2026-05-22 20:35:17 +00:00
5f6e33c054
SMEM-backed kv_coord counter — JIT can't constant-fold SMEM reads
2026-05-22 20:34:52 +00:00
18a5c60e26
DEBUG: hardcoded Int32(1) to test if TMA can read tile 1
2026-05-22 20:34:21 +00:00
b7a1deed52
DEBUG: use Int32(kt) directly to test if coordinate matters
2026-05-22 20:34:03 +00:00
c01291f16a
Test: kv_coord = warp_idx() * 0 — force SSA from runtime value
2026-05-22 20:33:40 +00:00
da4eebc9a4
DEBUG: add cute.printf for kv_coord runtime value
2026-05-22 20:33:03 +00:00
b8d4ac0ecb
Test: Python range() instead of cutlass.range() for TMA loop
2026-05-22 20:32:44 +00:00
ae6197fc78
Test example9: drop try_acquire/pk, single loop-carried kv_coord
2026-05-22 20:32:25 +00:00
20290d7439
REVERT to working example7 (n=128 cos 0.999998). Example8 TMA fix didn't work.
2026-05-22 20:28:15 +00:00
72ad0eca9e
Update stage_c test to example8: SSA kv_coord + per-tile O rescale
2026-05-22 20:27:58 +00:00
b1ee693998
Clean up tests: archive superseded files, keep only essential unit tests
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Kept in tests/unit/:
- test_fmha_v3.py (stages A+B)
- test_fmha_v3_diag.py (identity softmax, n=128+256)
- test_fmha_v3_stage_c.py (real softmax, n=128 cos 0.999998)
- layertest.py + cudagraph_test.py (required for every change)
- infrastructure: cache, custom_op, cutedsl, router, fp4, fused, interleave
Archived: 19 superseded unit tests + 10 root-level scratch files
Root level: only fmha_v3_stage_c_example7.py remains (now in unit/)
2026-05-22 20:25:27 +00:00
578c7e58be
Revert TMA to kt pattern (n=128 works), multi-tile TMA is separate bug
2026-05-22 20:10:35 +00:00
6a82036ebd
TMA: use self.n_kv_tiles + kv_coord pattern from working diag test
2026-05-22 20:08:07 +00:00
74380ffc21
REVERT to 0bdcdc0 — the version that passed n=128 cos 0.999998
2026-05-22 20:07:18 +00:00
a3f0e73c82
DEBUG: disable O rescale + normalize, test if corr setup alone causes regression
2026-05-22 19:57:53 +00:00
aa43a902e1
Shared corr tensors for O rescale + final normalize, fix softmax loop
2026-05-22 19:55:06 +00:00
bd52e88ce1
Add O rescale with correction_rescale pattern + fix TMA to working diag pattern
2026-05-22 19:51:53 +00:00
93acac7e43
O normalize: exact CUTLASS correction_rescale pattern with 2D reg tensor
2026-05-22 19:50:37 +00:00
70349de6dc
O normalize: TMEM round-trip with paired Ld/St atoms + standard epilogue_tma_store
2026-05-22 19:49:51 +00:00
02543b3d8d
Fix: use NamedBarrier instead of mbarrier_arrive/wait
2026-05-22 19:49:07 +00:00
5f98eaec3a
Fix: barrier_wait → mbarrier_wait, barrier_arrive → mbarrier_arrive
2026-05-22 19:48:31 +00:00
afe5d1ae21
Fix epilogue: corr_tile_size=16, proper epi_subtile tuple, match CUTLASS reference
2026-05-22 19:47:57 +00:00
