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"op": "ai.onnx.Scan",
"cases": [
{
"name": "lowered_prefix_sum_state",
"inputs": {
"initial_state": { "dtype": "float32", "shape": [2], "data": { "kind": "values", "values": [1.0, 10.0] } },
"scan_input": {
"dtype": "float32",
"shape": [3, 2],
"data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0] }
}
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [2], "tolerance": 0.000001 },
"scan_output": { "dtype": "float32", "shape": [3, 2], "tolerance": 0.000001 }
}
},
{
"name": "lowered_prefix_sum_reverse",
"attrs": { "reverse": 1 },
"inputs": {
"initial_state": { "dtype": "float32", "shape": [1], "data": { "kind": "values", "values": [0.0] } },
"scan_input": {
"dtype": "float32",
"shape": [4, 1],
"data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0] }
}
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [1], "tolerance": 0.000001 },
"scan_output": { "dtype": "float32", "shape": [4, 1], "tolerance": 0.000001 }
}
},
{
"name": "lowered_ort_projection_short_sequence_two_state_lanes",
"provenance": {
"source": "onnxruntime/test/providers/cpu/controlflow/scan_test.cc",
"test": "Scan8.ShortSequenceTwoInBatchOneLoopStateVar",
"notes": "Projection onto the framework's lowered prefix-sum variant using two state lanes from ORT's short sequence data."
},
"inputs": {
"initial_state": { "dtype": "float32", "shape": [2], "data": { "kind": "values", "values": [0.0, 10.0] } },
"scan_input": {
"dtype": "float32",
"shape": [2, 2],
"data": { "kind": "values", "values": [1.0, -1.0, 4.0, -4.0] }
}
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [2], "tolerance": 0.000001 },
"scan_output": { "dtype": "float32", "shape": [2, 2], "tolerance": 0.000001 }
}
},
{
"name": "lowered_ort_projection_reverse_two_state_lanes",
"attrs": { "reverse": 1 },
"provenance": {
"source": "onnxruntime/test/providers/cpu/controlflow/scan_test.cc",
"test": "Scan8.MixedSequenceLensReverse",
"notes": "Projection onto the framework's lowered reverse prefix-sum variant using reverse-direction values from ORT's Scan coverage."
},
"inputs": {
"initial_state": { "dtype": "float32", "shape": [2], "data": { "kind": "values", "values": [0.0, 10.0] } },
"scan_input": {
"dtype": "float32",
"shape": [2, 2],
"data": { "kind": "values", "values": [1.0, -1.0, 4.0, -4.0] }
}
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [2], "tolerance": 0.000001 },
"scan_output": { "dtype": "float32", "shape": [2, 2], "tolerance": 0.000001 }
}
},
{
"name": "lowered_ort_projection_scalar_loop_state",
"provenance": {
"source": "onnxruntime/test/providers/cpu/controlflow/scan_test.cc",
"test": "Scan8.OnnxScalarLoopState",
"notes": "Projection onto the framework's lowered prefix-sum variant using a scalar carried state."
},
"inputs": {
"initial_state": { "dtype": "float32", "shape": [1], "data": { "kind": "values", "values": [0.0] } },
"scan_input": { "dtype": "float32", "shape": [3, 1], "data": { "kind": "values", "values": [1.0, 2.0, 3.0] } }
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [1], "tolerance": 0.000001 },
"scan_output": { "dtype": "float32", "shape": [3, 1], "tolerance": 0.000001 }
}
},
{
"name": "lowered_prefix_sum_zero_steps",
"inputs": {
"initial_state": { "dtype": "float32", "shape": [2], "data": { "kind": "values", "values": [2.0, -3.0] } },
"scan_input": { "dtype": "float32", "shape": [0, 2], "data": { "kind": "values", "values": [] } }
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [2], "tolerance": 0.000001 },
"scan_output": { "dtype": "float32", "shape": [0, 2], "tolerance": 0.000001 }
}
},
{
"name": "lowered_prefix_sum_reverse_rank2_signed",
"attrs": { "reverse": 1 },
"inputs": {
"initial_state": { "dtype": "float32", "shape": [2], "data": { "kind": "values", "values": [10.0, -10.0] } },
"scan_input": {
"dtype": "float32",
"shape": [3, 2],
"data": { "kind": "values", "values": [1.0, -1.0, 2.0, -2.0, 3.0, -3.0] }
}
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [2], "tolerance": 0.000001 },
"scan_output": { "dtype": "float32", "shape": [3, 2], "tolerance": 0.000001 }
}
},
{
"name": "lowered_prefix_sum_reverse_zero_steps",
"attrs": { "reverse": 1 },
"inputs": {
"initial_state": { "dtype": "float32", "shape": [2], "data": { "kind": "values", "values": [7.0, -8.0] } },
"scan_input": { "dtype": "float32", "shape": [0, 2], "data": { "kind": "values", "values": [] } }
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [2], "tolerance": 0.000001 },
"scan_output": { "dtype": "float32", "shape": [0, 2], "tolerance": 0.000001 }
}
},
{
"name": "lowered_prefix_sum_zero_delta_lane",
"inputs": {
"initial_state": { "dtype": "float32", "shape": [3], "data": { "kind": "values", "values": [1.0, 10.0, -5.0] } },
"scan_input": {
"dtype": "float32",
"shape": [3, 3],
"data": { "kind": "values", "values": [0.0, 2.0, -1.0, 0.0, -3.0, 4.0, 0.0, 1.0, -2.0] }
}
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [3], "tolerance": 0.000001 },
"scan_output": { "dtype": "float32", "shape": [3, 3], "tolerance": 0.000001 }
}
},
{
"name": "coop_channel_prefix_sum_128x64",
"provenance": {
"notes": "Cross-gate case for the coop_channel_prefix_sum variant (dim>=64 and steps>=64). dim=64 -> 64 channel workgroups; steps=128 spans multiple WG-sized chunks with a cross-chunk carry. Tolerance covers the within-chunk subgroup/Hillis-Steele reassociation vs the strict serial loop."
},
"inputs": {
"initial_state": { "dtype": "float32", "shape": [64] },
"scan_input": { "dtype": "float32", "shape": [128, 64] }
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [64], "tolerance": 0.0001 },
"scan_output": { "dtype": "float32", "shape": [128, 64], "tolerance": 0.0001 }
}
},
{
"name": "coop_channel_prefix_sum_reverse_300x96",
"attrs": { "reverse": 1 },
"provenance": {
"notes": "Reverse-direction cross-gate case for coop_channel_prefix_sum. steps=300 is NOT a multiple of the 256 workgroup size, exercising the partial-chunk identity padding; dim=96 channel workgroups."
},
"inputs": {
"initial_state": { "dtype": "float32", "shape": [96] },
"scan_input": { "dtype": "float32", "shape": [300, 96] }
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [96], "tolerance": 0.0001 },
"scan_output": { "dtype": "float32", "shape": [300, 96], "tolerance": 0.0001 }
}
},
{
"name": "coop_channel_prefix_sum_dim512_steps256_perf_compact",
"provenance": {
"notes": "Compact correctness sibling for the Scan no-MMA prefix-sum cliff: dim=512 and steps=256 select coop_channel_prefix_sum with one full workgroup-sized scan chunk."
},
"inputs": {
"initial_state": { "dtype": "float32", "shape": [512] },
"scan_input": { "dtype": "float32", "shape": [256, 512] }
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [512], "tolerance": 0.0001 },
"scan_output": { "dtype": "float32", "shape": [256, 512], "tolerance": 0.0001 }
}
},
{
"name": "coop_channel_prefix_sum_dim1024_steps256",
"provenance": {
"notes": "Exercises a wide cooperative dispatch (1024 channel workgroups) and one full workgroup-sized scan chunk. Tolerance covers within-chunk subgroup/Hillis-Steele reassociation."
},
"inputs": {
"initial_state": { "dtype": "float32", "shape": [1024] },
"scan_input": { "dtype": "float32", "shape": [256, 1024] }
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [1024], "tolerance": 0.0001 },
"scan_output": { "dtype": "float32", "shape": [256, 1024], "tolerance": 0.0001 }
}
},
{
"name": "coop_dim1025_above_old_fixed_gate",
"provenance": {
"notes": "Regression for the former hard-coded dim<=1024 ceiling. Device-limit-derived cooperative coverage keeps this realistic 1025-channel scan off the serial fallback."
},
"inputs": {
"initial_state": { "dtype": "float32", "shape": [1025] },
"scan_input": { "dtype": "float32", "shape": [256, 1025] }
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [1025], "tolerance": 0.0001 },
"scan_output": { "dtype": "float32", "shape": [256, 1025], "tolerance": 0.0001 }
}
},
{
"name": "coop_channel_prefix_sum_dim64_steps64_min_gate",
"provenance": {
"notes": "Both lower coop gates at their exact inclusive thresholds: dim=64 (dim>=64) and steps=64 (steps>=64). This is the smallest shape that still selects coop_channel_prefix_sum. An off-by-one tightening of either >=64 gate (to >64) would demote this corner to the lowered fallback. Verifies coop at the minimum supported width and exactly one partial-free chunk boundary (steps==WG/4)."
},
"inputs": {
"initial_state": { "dtype": "float32", "shape": [64] },
"scan_input": { "dtype": "float32", "shape": [64, 64] }
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [64], "tolerance": 0.0001 },
"scan_output": { "dtype": "float32", "shape": [64, 64], "tolerance": 0.0001 }
}
},
{
"name": "lowered_dim64_steps63_below_steps_gate",
"provenance": {
"notes": "Just below the coop steps gate: dim=64 passes dim>=64 but steps=63 fails steps>=64, so this MUST fall to lowered_prefix_sum. Pins the steps off-by-one: an erroneous steps>=63 (or >63 vs >=64) gate would mis-route this short sequence. Both variants are spec-correct; this checks the lowered path at the exact step below the coop threshold."
},
"inputs": {
"initial_state": { "dtype": "float32", "shape": [64] },
"scan_input": { "dtype": "float32", "shape": [63, 64] }
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [64], "tolerance": 0.000001 },
"scan_output": { "dtype": "float32", "shape": [63, 64], "tolerance": 0.000001 }
}
},
{
"name": "lowered_prefix_sum_subnormal_residuals_gpu_gap",
"skipGpu": {
"category": "permanent",
"reason": "Portable WGSL floating-point semantics do not guarantee preservation of the subnormal values required by this fixture. Backend evidence: Metal flushes denormals to zero in the ALU; this lowered prefix-sum accumulates subnormal residuals that flush on GPU. Permanent FTZ limitation."
},
"provenance": {
"source": "onnxruntime/test/providers/cpu/controlflow/scan_test.cc",
"test": "Scan8.ShortSequenceTwoInBatchOneLoopStateVar",
"notes": "Projection onto the lowered prefix-sum variant: finite subnormal loop-state increments are valid residuals and must not flush to zero."
},
"inputs": {
"initial_state": { "dtype": "float32", "shape": [2], "data": { "kind": "values", "values": [0.0, 0.0] } },
"scan_input": {
"dtype": "float32",
"shape": [4, 2],
"data": { "kind": "values", "values": [1e-40, -1e-40, 1e-40, -1e-40, -1e-40, 1e-40, 2e-40, -2e-40] }
}
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [2], "tolerance": 0 },
"scan_output": { "dtype": "float32", "shape": [4, 2], "tolerance": 0 }
}
},
{
"name": "lowered_prefix_sum_reverse_subnormal_residuals_gpu_gap",
"skipGpu": {
"category": "permanent",
"reason": "Portable WGSL floating-point semantics do not guarantee preservation of the subnormal values required by this fixture. Backend evidence: Metal flushes denormals to zero in the ALU; this lowered prefix-sum accumulates subnormal residuals that flush on GPU. Permanent FTZ limitation."
},
"attrs": { "reverse": 1 },
"provenance": {
"source": "onnxruntime/test/providers/cpu/controlflow/scan_test.cc",
"test": "Scan8.MixedSequenceLensReverse",
"notes": "Reverse companion for subnormal prefix residuals; the scan-output slots are written in reverse traversal order but still contain finite float32 subnormal sums."
},
"inputs": {
"initial_state": { "dtype": "float32", "shape": [1], "data": { "kind": "values", "values": [0.0] } },
"scan_input": {
"dtype": "float32",
"shape": [3, 1],
"data": { "kind": "values", "values": [1e-40, 2e-40, 3e-40] }
}
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [1], "tolerance": 0 },
"scan_output": { "dtype": "float32", "shape": [3, 1], "tolerance": 0 }
}
},
{
"name": "coop_channel_prefix_sum_dim64_steps257_chunk_carry",
"provenance": {
"notes": "Routes to coop_channel_prefix_sum (dim=64>=64, dim<=1024, steps=257>=64). chunks=ceil(257/256)=2: chunk 0 = steps 0..255, chunk 1 = ONLY step 256 (one valid lane, 255 identity-padded). Isolates cross-chunk carry propagation into a near-empty second chunk and the final_state = carry-after-both-chunks path. An off-by-one chunk bound, stale carry, or padded-lane double-count would corrupt scan_output[256*64+i] and final_state. Verifies BOTH outputs against the TS reference; tolerance 1e-4 covers within-chunk subgroup/Hillis-Steele reassociation."
},
"inputs": {
"initial_state": { "dtype": "float32", "shape": [64] },
"scan_input": { "dtype": "float32", "shape": [257, 64] }
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [64], "tolerance": 0.0001 },
"scan_output": { "dtype": "float32", "shape": [257, 64], "tolerance": 0.0001 }
}
},
{
"name": "coop_channel_prefix_sum_reverse_dim64_steps257_chunk_carry",
"attrs": { "reverse": 1 },
"provenance": {
"notes": "Reverse coop_channel_prefix_sum (dim=64>=64, dim<=1024, steps=257>=64, reverse=1). chunks=2: chunk 0 (j=0..255) -> original steps 256..1, chunk 1 (j=256) -> original step 0. Pins the minimal 1-step residual chunk under reverse: verifies the reversed read/write addresses at the chunk boundary and the scan-order cross-chunk carry land at the correct reversed scan_output slots and final_state. Both outputs checked vs the TS reference; tolerance 1e-4 covers within-chunk reassociation."
},
"inputs": {
"initial_state": { "dtype": "float32", "shape": [64] },
"scan_input": { "dtype": "float32", "shape": [257, 64] }
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [64], "tolerance": 0.0001 },
"scan_output": { "dtype": "float32", "shape": [257, 64], "tolerance": 0.0001 }
}
},
{
"name": "lowered_dim1_steps2000_singlechannel_serial",
"provenance": {
"notes": "dim=1 fails coop 'dim>=64' -> lowered_prefix_sum, one active lane (i=0) running the serial 2000-step recurrence with addressing t*1+0=t. Covers the single-channel serial scan over a long sequence (existing dim=1 cases stop at steps<=4). Serial per-channel accumulation is bit-identical to the reference, so tolerance stays at 1e-6; both outputs verified vs the TS reference."
},
"inputs": {
"initial_state": { "dtype": "float32", "shape": [1], "data": { "kind": "values", "values": [3.5] } },
"scan_input": {
"dtype": "float32",
"shape": [2000, 1],
"data": { "kind": "fillFloat32", "sinStep": 0.017, "scale": 0.25, "offset": 0.01 }
}
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [1], "tolerance": 0.000001 },
"scan_output": { "dtype": "float32", "shape": [2000, 1], "tolerance": 0.000001 }
}
},
{
"name": "multichunk_small_state_dim2_steps4096",
"provenance": {
"notes": "Compact correctness lock for a realistic long-stream recurrence with only two independent state lanes. The optimized path partitions the sequential axis into workgroup-sized chunks, scans chunk totals, then applies carries."
},
"inputs": {
"initial_state": { "dtype": "float32", "shape": [2], "data": { "kind": "values", "values": [1.5, -2.0] } },
"scan_input": {
"dtype": "float32",
"shape": [4096, 2],
"data": { "kind": "fillFloat32", "sinStep": 0.017, "cosStep": 0.013, "scale": 0.01, "offset": 0.0001 }
}
},
"outputs": {
"final_state": { "dtype": "float32", "shape": [2], "tolerance": 0.001, "relTolerance": 0.0001 },
"scan_output": { "dtype": "float32", "shape": [4096, 2], "tolerance": 0.001, "relTolerance": 0.0001 }
}
}
]
}
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