| { |
| "fixtureArrays": { |
| "ort_3d_axis1_reverse_input_x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24] |
| }, |
| "cases": [ |
| { |
| "name": "f16_splitk_vec4_rows_axis0", |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [8192, 4], |
| "data": { |
| "kind": "cycle", |
| "values": [0.125, -0.0625, 0.03125, -0.015625, -0.125, 0.0625, -0.03125, 0.015625] |
| } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float16", "shape": [8192, 4], "tolerance": 0 } } |
| }, |
| { |
| "name": "dispatch_cliff_thread_row_scan_f32", |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [1, 16777216], "data": { "kind": "constant", "value": 1.0 } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [1, 16777216], "tolerance": 0 } } |
| }, |
| { |
| "name": "axis1_f32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._2DTestAxis1" |
| }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 4], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 10.0, 20.0, 30.0, 40.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 4] } } |
| }, |
| { |
| "name": "ort_2d_axis0_f32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._2DTestAxis0" |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_2d_axis1_f32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._2DTestAxis1" |
| }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "f32_ordered_prefix_cancellation_workgroup_scan_no_subgroups", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._1DTest", |
| "notes": "CumSum is an ordered prefix operation. The no-subgroups workgroup tree scan may regroup 1e20 + -1e20 + 1 and lose the finite residual." |
| }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [1, 33], |
| "data": { |
| "kind": "values", |
| "values": [100000000000000000000.0, -100000000000000000000.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] |
| } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [1, 33], "tolerance": 0 } } |
| }, |
| { |
| "name": "f32_ordered_reverse_exclusive_cancellation_workgroup_scan_no_subgroups", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._1DTestReverseExclusive", |
| "notes": "Reverse+exclusive CumSum is still an ordered prefix operation. The no-subgroups workgroup tree scan may regroup 1 + -1e20 + 1e20 and lose the finite residual." |
| }, |
| "attrs": { "exclusive": 1, "reverse": 1 }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [1, 33], |
| "data": { |
| "kind": "values", |
| "values": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, -100000000000000000000.0, 100000000000000000000.0] |
| } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [1, 33], "tolerance": 0 } } |
| }, |
| { |
| "name": "f32_subnormal_axis1_accumulation_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: WebGPU/Metal flushes subnormals to zero in f32; bit-exact subnormal preservation is unattainable on GPU." |
| }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._2DTestAxis1", |
| "notes": "Cumulative sums of finite subnormal values remain valid float32 outputs; flushing any step loses the entire running total." |
| }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3], |
| "data": { "kind": "values", "values": [1e-40, 1e-40, 1e-40, -1e-40, -1e-40, -1e-40] } |
| } |
| }, |
| "outputs": { |
| "y": { |
| "dtype": "float32", |
| "shape": [2, 3], |
| "tolerance": 0, |
| "data": { "kind": "values", "values": [1e-40, 2e-40, 3e-40, -1e-40, -2e-40, -3e-40] } |
| } |
| } |
| }, |
| { |
| "name": "f32_subnormal_axis0_forward_accumulation_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: WebGPU/Metal flushes subnormals to zero in f32; bit-exact subnormal preservation is unattainable on GPU." |
| }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._2DTestAxis0", |
| "notes": "Finite subnormal cumulative sums along axis 0 exercise the non-contiguous scan path." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 2], |
| "data": { "kind": "values", "values": [1e-40, -1e-40, 2e-40, -2e-40, 3e-40, -3e-40] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 2], "tolerance": 0 } } |
| }, |
| { |
| "name": "f32_subnormal_axis1_reverse_exclusive_accumulation_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: WebGPU/Metal flushes subnormals to zero in f32; bit-exact subnormal preservation is unattainable on GPU." |
| }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._1DTestReverseExclusive", |
| "notes": "Reverse+exclusive CumSum accumulates from the far end of the axis; valid subnormal residuals should survive each shifted prefix." |
| }, |
| "attrs": { "exclusive": 1, "reverse": 1 }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [1, 4], |
| "data": { "kind": "values", "values": [1e-40, 2e-40, 3e-40, 4e-40] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [1, 4], "tolerance": 0 } } |
| }, |
| { |
| "name": "f32_subnormal_axis0_reverse_accumulation_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: WebGPU/Metal flushes subnormals to zero in f32; bit-exact subnormal preservation is unattainable on GPU." |
| }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._2DTestAxis0", |
| "notes": "Reverse CumSum along axis 0 exercises subnormal residual propagation through the non-last-axis scan path." |
| }, |
| "attrs": { "reverse": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [4, 1], |
| "data": { "kind": "values", "values": [1e-40, 2e-40, 3e-40, 4e-40] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [4, 1], "tolerance": 0 } } |
| }, |
| { |
| "name": "f32_subnormal_workgroup_scan_accumulation_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: WebGPU/Metal flushes subnormals to zero in f32; bit-exact subnormal preservation is unattainable on GPU." |
| }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._2DTestAxis1", |
| "notes": "A cumulative sum over more than 32 values must retain finite subnormal running totals." |
| }, |
| "args": { "axis": 1 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [1, 33], "data": { "kind": "constant", "value": 1e-40 } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [1, 33], "tolerance": 0 } } |
| }, |
| { |
| "name": "axis0_exclusive_reverse_f32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._3DTestAxis0ReverseExclusive" |
| }, |
| "attrs": { "exclusive": 1, "reverse": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 2], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 2] } } |
| }, |
| { |
| "name": "negative_axis_uint32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._1DTestNegAxis" |
| }, |
| "args": { "axis": -1 }, |
| "inputs": { |
| "x": { "dtype": "uint32", "shape": [2, 3], "data": { "kind": "values", "values": [1, 2, 3, 4, 5, 6] } } |
| }, |
| "outputs": { "y": { "dtype": "uint32", "shape": [2, 3] } } |
| }, |
| { |
| "name": "axis1_f16", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._1DTestFloat16" |
| }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [2, 3], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, -1.0, -2.0, -3.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float16", "shape": [2, 3] } }, |
| "tolerance": 0.001 |
| }, |
| { |
| "name": "onnx_1d_exclusive", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._1DTestExclusive" |
| }, |
| "attrs": { "exclusive": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [5], "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0] } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [5], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "onnx_1d_reverse", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._1DTestReverse" |
| }, |
| "attrs": { "reverse": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [5], "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0] } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [5], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "onnx_1d_reverse_exclusive", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._1DTestReverseExclusive" |
| }, |
| "attrs": { "exclusive": 1, "reverse": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [5], "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0] } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [5], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "exclusive_singleton_axis_forward", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._1DTestExclusiveAxisHasSingleValue" |
| }, |
| "attrs": { "exclusive": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [1, 2], "data": { "kind": "values", "values": [1.0, 2.0] } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [1, 2], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_exclusive_singleton_axis_reverse", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._1DTestExclusiveAxisHasSingleValue" |
| }, |
| "attrs": { "exclusive": 1, "reverse": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [1, 2], "data": { "kind": "values", "values": [1.0, 2.0] } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [1, 2], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_3d_axis1_reverse", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._3DTestAxis1Reverse" |
| }, |
| "attrs": { "reverse": 1 }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3, 4], |
| "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/ort_3d_axis1_reverse_input_x" } } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3, 4], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_3d_axis2_reverse_exclusive", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._3DTestAxis2ReverseExclusive" |
| }, |
| "attrs": { "exclusive": 1, "reverse": 1 }, |
| "args": { "axis": 2 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3, 4], |
| "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/ort_3d_axis1_reverse_input_x" } } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3, 4], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_exclusive_axis_dim_one_forward", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._1DTestExclusiveAxisHasSingleValue" |
| }, |
| "attrs": { "exclusive": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [1, 2], "data": { "kind": "values", "values": [1.0, 2.0] } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [1, 2], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_exclusive_axis_dim_one_reverse", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._1DTestExclusiveAxisHasSingleValue" |
| }, |
| "attrs": { "exclusive": 1, "reverse": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [1, 2], "data": { "kind": "values", "values": [1.0, 2.0] } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [1, 2], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_1d_int32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._1DTestInt32" |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "int32", "shape": [5], "data": { "kind": "values", "values": [1, 2, 3, 4, 5] } } }, |
| "outputs": { "y": { "dtype": "int32", "shape": [5], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_1d_f32_default", |
| "provenance": { "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", "test": "CumSumTest._1DTest" }, |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [5], "data": { "kind": "linspace", "start": 1.0, "end": 5.0 } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [5], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_1d_negative_axis_f32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._1DTestNegAxis" |
| }, |
| "args": { "axis": -1 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [5], "data": { "kind": "linspace", "start": 1.0, "end": 5.0 } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [5], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_2d_exclusive_axis0_f32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._2DTestExclusiveAxis0" |
| }, |
| "attrs": { "exclusive": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [2, 3], "data": { "kind": "linspace", "start": 1.0, "end": 6.0 } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_2d_exclusive_axis1_f32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._2DTestExclusiveAxis1" |
| }, |
| "attrs": { "exclusive": 1 }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [2, 3], "data": { "kind": "linspace", "start": 1.0, "end": 6.0 } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_3d_axis0_f32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._3DTestAxis0" |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [2, 3, 4], "data": { "kind": "linspace", "start": 1.0, "end": 24.0 } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3, 4], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_3d_axis2_f32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._3DTestAxis2" |
| }, |
| "args": { "axis": 2 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [2, 3, 4], "data": { "kind": "linspace", "start": 1.0, "end": 24.0 } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3, 4], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_3d_axis0_reverse_exclusive_f32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._3DTestAxis0ReverseExclusive" |
| }, |
| "attrs": { "exclusive": 1, "reverse": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [2, 3, 4], "data": { "kind": "linspace", "start": 1.0, "end": 24.0 } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3, 4], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_3d_axis1_reverse_exclusive_f32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._3DTestAxis1ReverseExclusive" |
| }, |
| "attrs": { "exclusive": 1, "reverse": 1 }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [2, 3, 4], "data": { "kind": "linspace", "start": 1.0, "end": 24.0 } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3, 4], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "onnx_backend_cumsum_1d_f32_projection", |
| "provenance": { |
| "source": "cmake/external/onnx/onnx/backend/test/data/node/test_cumsum_1d", |
| "notes": "The official ONNX backend fixture uses float64; this case preserves its values in supported float32 storage." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [5], "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0] } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [5], "tolerance": 0.00001 } } |
| }, |
| { |
| "name": "onnx_backend_cumsum_1d_exclusive_f32_projection", |
| "provenance": { |
| "source": "cmake/external/onnx/onnx/backend/test/data/node/test_cumsum_1d_exclusive", |
| "notes": "The official ONNX backend fixture uses float64; this case preserves its values in supported float32 storage." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [5], "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0] } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [5], "tolerance": 0.00001 } }, |
| "attrs": { "exclusive": 1 } |
| }, |
| { |
| "name": "onnx_backend_cumsum_1d_int32_exclusive", |
| "provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_cumsum_1d_int32_exclusive" }, |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "int32", "shape": [5], "data": { "kind": "values", "values": [1, 2, 3, 4, 5] } } }, |
| "outputs": { "y": { "dtype": "int32", "shape": [5], "tolerance": 0 } }, |
| "attrs": { "exclusive": 1 } |
| }, |
| { |
| "name": "onnx_backend_cumsum_1d_reverse_f32_projection", |
| "provenance": { |
| "source": "cmake/external/onnx/onnx/backend/test/data/node/test_cumsum_1d_reverse", |
| "notes": "The official ONNX backend fixture uses float64; this case preserves its values in supported float32 storage." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [5], "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0] } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [5], "tolerance": 0.00001 } }, |
| "attrs": { "reverse": 1 } |
| }, |
| { |
| "name": "onnx_backend_cumsum_1d_reverse_exclusive_f32_projection", |
| "provenance": { |
| "source": "cmake/external/onnx/onnx/backend/test/data/node/test_cumsum_1d_reverse_exclusive", |
| "notes": "The official ONNX backend fixture uses float64; this case preserves its values in supported float32 storage." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [5], "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0] } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [5], "tolerance": 0.00001 } }, |
| "attrs": { "exclusive": 1, "reverse": 1 } |
| }, |
| { |
| "name": "onnx_backend_cumsum_2d_axis_0_f32_projection", |
| "provenance": { |
| "source": "cmake/external/onnx/onnx/backend/test/data/node/test_cumsum_2d_axis_0", |
| "notes": "The official ONNX backend fixture uses float64; this case preserves its values in supported float32 storage." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3], "tolerance": 0.00001 } } |
| }, |
| { |
| "name": "onnx_backend_cumsum_2d_axis_1_f32_projection", |
| "provenance": { |
| "source": "cmake/external/onnx/onnx/backend/test/data/node/test_cumsum_2d_axis_1", |
| "notes": "The official ONNX backend fixture uses float64; this case preserves its values in supported float32 storage." |
| }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3], "tolerance": 0.00001 } } |
| }, |
| { |
| "name": "onnx_backend_cumsum_2d_int32", |
| "provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_cumsum_2d_int32" }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { "dtype": "int32", "shape": [2, 3], "data": { "kind": "values", "values": [1, 2, 3, 4, 5, 6] } } |
| }, |
| "outputs": { "y": { "dtype": "int32", "shape": [2, 3], "tolerance": 0 } } |
| }, |
| { |
| "name": "onnx_backend_cumsum_2d_negative_axis_f32_projection", |
| "provenance": { |
| "source": "cmake/external/onnx/onnx/backend/test/data/node/test_cumsum_2d_negative_axis", |
| "notes": "The official ONNX backend fixture uses float64; this case preserves its values in supported float32 storage." |
| }, |
| "args": { "axis": -1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3], "tolerance": 0.00001 } } |
| }, |
| { |
| "name": "ort_3d_axis1_f32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._3DTestAxis1" |
| }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3, 4], |
| "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/ort_3d_axis1_reverse_input_x" } } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3, 4], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_3d_axis0_exclusive_f32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._3DTestAxis0Exclusive" |
| }, |
| "attrs": { "exclusive": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3, 4], |
| "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/ort_3d_axis1_reverse_input_x" } } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3, 4], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_3d_axis1_exclusive_f32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._3DTestAxis1Exclusive" |
| }, |
| "attrs": { "exclusive": 1 }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3, 4], |
| "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/ort_3d_axis1_reverse_input_x" } } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3, 4], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_3d_axis2_exclusive_f32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._3DTestAxis2Exclusive" |
| }, |
| "attrs": { "exclusive": 1 }, |
| "args": { "axis": 2 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3, 4], |
| "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/ort_3d_axis1_reverse_input_x" } } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3, 4], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_3d_axis0_reverse_f32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._3DTestAxis0Reverse" |
| }, |
| "attrs": { "reverse": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3, 4], |
| "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/ort_3d_axis1_reverse_input_x" } } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3, 4], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_3d_axis2_reverse_f32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._3DTestAxis2Reverse" |
| }, |
| "attrs": { "reverse": 1 }, |
| "args": { "axis": 2 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3, 4], |
| "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/ort_3d_axis1_reverse_input_x" } } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3, 4], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_long_int32_axis0_compact", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._1DTestLong", |
| "notes": "Compact projection of ORT's 100000-element all-ones int32 scan; keeps runtime practical while exercising long-axis indexing." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "int32", "shape": [1024], "data": { "kind": "constant", "value": 1 } } }, |
| "outputs": { "y": { "dtype": "int32", "shape": [1024], "tolerance": 0 } } |
| }, |
| { |
| "name": "wg_scan_axis1_f32_len200", |
| "provenance": { |
| "notes": "Integer-valued f32 (exact under any summation order) exercising the workgroup row-scan variant with a partial chunk." |
| }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [16, 200], "data": { "kind": "linspace", "start": 1.0, "end": 3200.0 } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [16, 200], "tolerance": 0 } } |
| }, |
| { |
| "name": "wg_scan_axis1_exclusive_f32", |
| "provenance": { |
| "notes": "An exclusive workgroup row scan over integer-valued float32 data has exact cumulative sums." |
| }, |
| "attrs": { "exclusive": 1 }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [8, 64], "data": { "kind": "linspace", "start": 1.0, "end": 512.0 } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [8, 64], "tolerance": 0 } } |
| }, |
| { |
| "name": "wg_scan_axis1_reverse_f32", |
| "provenance": { |
| "notes": "A reverse workgroup row scan over integer-valued float32 data has exact cumulative sums." |
| }, |
| "attrs": { "reverse": 1 }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [8, 64], "data": { "kind": "linspace", "start": 1.0, "end": 512.0 } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [8, 64], "tolerance": 0 } } |
| }, |
| { |
| "name": "wg_scan_reverse_exclusive_partial_chunk_f32", |
| "provenance": { "notes": "Reverse+exclusive workgroup row-scan with a non-multiple-of-256 axis length." }, |
| "attrs": { "exclusive": 1, "reverse": 1 }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [4, 100], "data": { "kind": "linspace", "start": 1.0, "end": 400.0 } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [4, 100], "tolerance": 0 } } |
| }, |
| { |
| "name": "wg_scan_multichunk_f32", |
| "provenance": { |
| "notes": "Axis length 1000 (last axis) spans four 256-element chunks (three full, one of 232), requiring the running sum to carry across chunk boundaries. Integer-valued data (1 to 4000) keeps the cumulative sum exact in float32." |
| }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [4, 1000], "data": { "kind": "linspace", "start": 1.0, "end": 4000.0 } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [4, 1000], "tolerance": 0 } } |
| }, |
| { |
| "name": "wg_scan_axis1_f16_ones", |
| "provenance": { "notes": "f16 workgroup row-scan; all-ones cumsum (1..64) is exact in f16." }, |
| "args": { "axis": 1 }, |
| "inputs": { "x": { "dtype": "float16", "shape": [2, 64], "data": { "kind": "constant", "value": 1.0 } } }, |
| "outputs": { "y": { "dtype": "float16", "shape": [2, 64], "tolerance": 0 } } |
| }, |
| { |
| "name": "wg_scan_axis1_u32_cycle", |
| "provenance": { |
| "notes": "A uint32 workgroup row scan remains exact because modulo-2^32 addition is associative." |
| }, |
| "args": { "axis": 1 }, |
| "inputs": { "x": { "dtype": "uint32", "shape": [3, 48], "data": { "kind": "cycle", "values": [1, 2, 3] } } }, |
| "outputs": { "y": { "dtype": "uint32", "shape": [3, 48], "tolerance": 0 } } |
| }, |
| { |
| "name": "thread_rows_axis0_f32", |
| "provenance": { |
| "notes": "Wide-inner axis-0 scan exercising the thread-per-row serial variant (bit-identical accumulation order to the fallback)." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [8, 4096], "data": { "kind": "linspace", "start": 1.0, "end": 32768.0 } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [8, 4096], "tolerance": 0 } } |
| }, |
| { |
| "name": "thread_rows_axis1_3d_reverse_exclusive_f32", |
| "provenance": { |
| "notes": "A three-dimensional middle-axis scan exercises reverse and exclusive handling in the thread-per-row path." |
| }, |
| "attrs": { "exclusive": 1, "reverse": 1 }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [4, 16, 512], "data": { "kind": "linspace", "start": 1.0, "end": 32768.0 } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [4, 16, 512], "tolerance": 0 } } |
| }, |
| { |
| "name": "thread_rows_axis0_int32_ones", |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "int32", "shape": [4, 2048], "data": { "kind": "constant", "value": 1 } } }, |
| "outputs": { "y": { "dtype": "int32", "shape": [4, 2048], "tolerance": 0 } } |
| }, |
| { |
| "name": "empty_input_zero_dim", |
| "args": { "axis": 1 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [0, 4], "data": { "kind": "values", "values": [] } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [0, 4], "tolerance": 0 } } |
| }, |
| { |
| "name": "wg_strided_axis0_f32_multichunk", |
| "provenance": { |
| "notes": "Workgroup strided row-scan (inner>1, dim>256): few rows + long non-innermost axis. constant-1 input keeps f32 exact across the cross-chunk carry." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [512, 32], "data": { "kind": "constant", "value": 1.0 } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [512, 32], "tolerance": 0 } } |
| }, |
| { |
| "name": "wg_strided_axis0_exclusive_f32", |
| "provenance": { "notes": "An exclusive workgroup strided scan over constant-one data has exact cumulative sums." }, |
| "attrs": { "exclusive": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [512, 8], "data": { "kind": "constant", "value": 1.0 } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [512, 8], "tolerance": 0 } } |
| }, |
| { |
| "name": "wg_strided_axis1_3d_reverse_f32", |
| "provenance": { "notes": "Workgroup strided row-scan reverse, 3D non-innermost axis (inner=16, dim=512)." }, |
| "attrs": { "reverse": 1 }, |
| "args": { "axis": 1 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [2, 512, 16], "data": { "kind": "constant", "value": 1.0 } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 512, 16], "tolerance": 0 } } |
| }, |
| { |
| "name": "wg_strided_axis1_3d_reverse_exclusive_f32", |
| "provenance": { "notes": "Workgroup strided row-scan reverse+exclusive cross-chunk path." }, |
| "attrs": { "reverse": 1, "exclusive": 1 }, |
| "args": { "axis": 1 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [2, 512, 16], "data": { "kind": "constant", "value": 1.0 } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 512, 16], "tolerance": 0 } } |
| }, |
| { |
| "name": "wg_strided_axis0_int32_ones", |
| "provenance": { "notes": "Workgroup strided row-scan int32 (integer wrap is associative -> exact)." }, |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "int32", "shape": [512, 8], "data": { "kind": "constant", "value": 1 } } }, |
| "outputs": { "y": { "dtype": "int32", "shape": [512, 8], "tolerance": 0 } } |
| }, |
| { |
| "name": "wg_strided_axis0_f16_ones", |
| "provenance": { |
| "notes": "Workgroup strided row-scan f16 storage; f32 accumulation matches the serial kernel for small integer values." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "float16", "shape": [300, 4], "data": { "kind": "constant", "value": 1.0 } } }, |
| "outputs": { "y": { "dtype": "float16", "shape": [300, 4], "tolerance": 0 } } |
| }, |
| { |
| "name": "splitk_axis0_f32_forward_ones", |
| "provenance": { |
| "notes": "Split-K row scan (f32, dim>=8192, few rows): long axis 0 split across SPLIT segments x rows workgroups. dim=8192 -> 4 segments, 2048-long each (8 WG-chunks/segment), exercising both the cross-segment carry and the intra-segment chunk carry. constant-1 keeps f32 exact (max total 8192 << 2^24)." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [8192, 8], "data": { "kind": "constant", "value": 1.0 } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [8192, 8], "tolerance": 0 } } |
| }, |
| { |
| "name": "splitk_axis0_f32_exclusive_ones", |
| "provenance": { |
| "notes": "An exclusive split-K row scan over constant-one data exercises exact cross-segment carry handling." |
| }, |
| "attrs": { "exclusive": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [8192, 8], "data": { "kind": "constant", "value": 1.0 } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [8192, 8], "tolerance": 0 } } |
| }, |
| { |
| "name": "splitk_axis0_f32_reverse_ones", |
| "provenance": { |
| "notes": "Split-K row scan reverse: segment 0 owns the last axis slices, so the segment index still runs in scan order. constant-1 stays exact." |
| }, |
| "attrs": { "reverse": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [8192, 8], "data": { "kind": "constant", "value": 1.0 } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [8192, 8], "tolerance": 0 } } |
| }, |
| { |
| "name": "splitk_axis0_f32_reverse_exclusive_ones", |
| "provenance": { |
| "notes": "A reverse exclusive split-K row scan over constant-one data exercises exact cross-segment carry handling." |
| }, |
| "attrs": { "reverse": 1, "exclusive": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [8192, 8], "data": { "kind": "constant", "value": 1.0 } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [8192, 8], "tolerance": 0 } } |
| }, |
| { |
| "name": "splitk_axis0_f32_partial_segment_ones", |
| "provenance": { |
| "notes": "Split-K with a non-power-of-WG axis (dim=10000, ceilDiv(10000,2048)=5 -> 8 segments, last segment shorter): exercises the partial-segment and partial-chunk tails." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [10000, 6], "data": { "kind": "constant", "value": 1.0 } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [10000, 6], "tolerance": 0 } } |
| }, |
| { |
| "name": "splitk_axis0_f32_single_row_inner1", |
| "provenance": { |
| "notes": "Split-K with inner=1 (innermost axis, rows=1): one row split into SPLIT segments. Confirms the carry chain across segments for a single lane." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [16384, 1], "data": { "kind": "constant", "value": 1.0 } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [16384, 1], "tolerance": 0 } } |
| }, |
| { |
| "name": "splitk_axis0_f32_varying_crosscheck", |
| "provenance": { |
| "notes": "A varying positive float32 linspace exercises split-K segment and chunk carries. Monotone running totals avoid catastrophic cancellation, so reassociated accumulation differs from input-order accumulation only by a small relative rounding error." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [8192, 4], "data": { "kind": "linspace", "start": 0.5, "end": 1.5 } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [8192, 4], "tolerance": 0.001, "relTolerance": 0.001 } } |
| }, |
| { |
| "name": "rank4_middle_axis_f32_thread_rows", |
| "provenance": { |
| "notes": "For shape [3,5,7,4] reduced along axis 2, outer=15 and inner=4 are both greater than one. Integer-valued float32 inputs keep every seven-element row scan exact while exercising outer/axis/inner coordinate flattening." |
| }, |
| "args": { "axis": 2 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [3, 5, 7, 4], "data": { "kind": "linspace", "start": 1.0, "end": 420.0 } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 5, 7, 4], "tolerance": 0 } } |
| }, |
| { |
| "name": "rank5_middle_axis_reverse_exclusive_int32", |
| "provenance": { |
| "notes": "Rank-5 reverse+exclusive non-last axis (axis=2: outer=4, dim=3, inner=8). Confirms the reverse + shift-right exclusive index math and the outer/inner flattening at rank 5. int32 wraps mod 2^32, exact vs ORT." |
| }, |
| "attrs": { "exclusive": 1, "reverse": 1 }, |
| "args": { "axis": 2 }, |
| "inputs": { |
| "x": { "dtype": "int32", "shape": [2, 2, 3, 2, 4], "data": { "kind": "cycle", "values": [1, 2, 3, 4, 5] } } |
| }, |
| "outputs": { "y": { "dtype": "int32", "shape": [2, 2, 3, 2, 4], "tolerance": 0 } } |
| }, |
| { |
| "name": "uint32_running_sum_wraps_2pow32_axis1", |
| "provenance": { |
| "notes": "uint32 cumulative sum driven past 2^32 so the running total wraps (64 * 2^28 = 2^34). u32 addition wraps mod 2^32 in WGSL (accType=u32, no f32 promotion), so the wrapped prefix must match exactly. Confirms the int path is NOT silently accumulating in f32. inner=1, dim>32 -> wg_row_scan." |
| }, |
| "args": { "axis": 1 }, |
| "inputs": { "x": { "dtype": "uint32", "shape": [4, 64], "data": { "kind": "constant", "value": 268435456 } } }, |
| "outputs": { "y": { "dtype": "uint32", "shape": [4, 64], "tolerance": 0 } } |
| }, |
| { |
| "name": "int32_large_mixed_axis0_strided", |
| "provenance": { |
| "notes": "int32 strided scan (inner=8, dim=300>256 -> wg_strided_row_scan) with large mixed +/- values that stay within i32 range but produce large-magnitude running totals. Verifies the wg_strided int path accumulates in i32 (not f32, which would lose low bits past 2^24)." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "int32", |
| "shape": [300, 8], |
| "data": { "kind": "cycle", "values": [1000000, -500000, 750000, -250000] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "int32", "shape": [300, 8], "tolerance": 0 } } |
| }, |
| { |
| "name": "f16_varied_axis1_wg_row", |
| "provenance": { |
| "notes": "Varied float16 values along a 256-element contiguous axis exercise float32 workgroup accumulation followed by float16 storage. Running totals remain small and finite." |
| }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { "dtype": "float16", "shape": [4, 256], "data": { "kind": "cycle", "values": [0.5, 1.5, -0.5, 2.0] } } |
| }, |
| "outputs": { "y": { "dtype": "float16", "shape": [4, 256], "tolerance": 0.01, "relTolerance": 0.01 } } |
| }, |
| { |
| "name": "splitk_axis0_f32_reverse_varying_crosscheck", |
| "provenance": { |
| "notes": "A reverse split-K scan over a varying positive linspace makes segment order and reverse indexing observable while keeping reassociation drift within tolerance." |
| }, |
| "attrs": { "reverse": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [8192, 4], "data": { "kind": "linspace", "start": 0.5, "end": 2.5 } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [8192, 4], "tolerance": 0.01, "relTolerance": 0.001 } } |
| }, |
| { |
| "name": "splitk_axis0_f32_reverse_exclusive_varying_crosscheck", |
| "provenance": { |
| "notes": "A reverse exclusive split-K scan over a varying positive linspace exercises the shift at segment boundaries and reverse cross-segment carry while keeping reassociation drift within tolerance." |
| }, |
| "attrs": { "exclusive": 1, "reverse": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [8192, 4], "data": { "kind": "linspace", "start": 0.5, "end": 2.5 } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [8192, 4], "tolerance": 0.01, "relTolerance": 0.001 } } |
| }, |
| { |
| "name": "wg_strided_axis0_reverse_exclusive_varying_offmultiple", |
| "provenance": { |
| "notes": "A 300-element reverse exclusive strided scan comprises one full 256-element chunk and a 44-element tail. Varying positive values make partial-chunk masking and the exclusive boundary shift observable." |
| }, |
| "attrs": { "exclusive": 1, "reverse": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [300, 8], "data": { "kind": "linspace", "start": 0.25, "end": 4.0 } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [300, 8], "tolerance": 0.001, "relTolerance": 0.001 } } |
| }, |
| { |
| "name": "int32_splitk_axis0_reverse_varying_exact", |
| "provenance": { |
| "notes": "An 8,192-element int32 reverse split-K scan uses varying cyclic values, making segment order observable. Associative integer addition keeps the expected result exact and all magnitudes remain in range." |
| }, |
| "attrs": { "reverse": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { "dtype": "int32", "shape": [8192, 4], "data": { "kind": "cycle", "values": [7, -3, 11, -5, 2] } } |
| }, |
| "outputs": { "y": { "dtype": "int32", "shape": [8192, 4], "tolerance": 0 } } |
| }, |
| { |
| "name": "wg_row_scan_vec4_dim_multiple4_exclusive_varying", |
| "provenance": { |
| "notes": "A contiguous 256-element exclusive scan over varying integer-valued float32 data exercises vec4 register-blocked lane offsets. Every cumulative sum is exact under any accumulation order." |
| }, |
| "attrs": { "exclusive": 1 }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [4, 256], "data": { "kind": "cycle", "values": [1.0, 2.0, 3.0, -1.0] } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [4, 256], "tolerance": 0 } } |
| }, |
| { |
| "name": "rank7_last_axis", |
| "args": { "axis": -1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 1, 2, 1, 2, 1, 3], |
| "data": { "kind": "cycle", "values": [1.0, -0.5, 2.0, 0.25] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 1, 2, 1, 2, 1, 3], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "int32_rows2_dim64_wg_row_scan_vec4", |
| "provenance": { |
| "source": "synthetic", |
| "notes": "Two 64-element int32 rows require an exact cumulative sum despite reassociation of additions." |
| }, |
| "args": { "axis": 1 }, |
| "inputs": { "x": { "dtype": "int32", "shape": [2, 64], "data": { "kind": "cycle", "values": [3, -1, 7, 2] } } }, |
| "outputs": { "y": { "dtype": "int32", "shape": [2, 64], "tolerance": 0 } } |
| }, |
| { |
| "name": "int32_rows2_dim64_reverse_wg_row_scan", |
| "provenance": { |
| "source": "synthetic", |
| "notes": "A reverse cumulative sum over int32 rows checks output order and exact integer addition." |
| }, |
| "attrs": { "reverse": 1 }, |
| "args": { "axis": 1 }, |
| "inputs": { "x": { "dtype": "int32", "shape": [2, 64], "data": { "kind": "cycle", "values": [3, -1, 7, 2] } } }, |
| "outputs": { "y": { "dtype": "int32", "shape": [2, 64], "tolerance": 0 } } |
| }, |
| { |
| "name": "float32_rows2_dim1536_splitk_mid_fallback", |
| "provenance": { |
| "source": "synthetic", |
| "notes": "A width-1536 float row exercises the mid-size scan policy: devices without an ordered subgroup scan use split-K, while compatible fixed-width subgroups may use a workgroup scan. Integer-valued data keeps either accumulation order exact." |
| }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [2, 1536], "data": { "kind": "cycle", "values": [1.0, 2.0, -1.0, 3.0] } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 1536], "tolerance": 0 } } |
| }, |
| { |
| "name": "rank8_last_axis", |
| "args": { "axis": -1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 1, 2, 1, 2, 1, 2, 3], |
| "data": { "kind": "cycle", "values": [1.0, -0.5, 2.0, 0.25] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 1, 2, 1, 2, 1, 2, 3], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "wg_strided_axis0_uint32_cycle", |
| "provenance": { |
| "notes": "A uint32 workgroup strided scan exercises the unsigned identity and wrapping-addition path. Modulo-2^32 addition is associative, so reassociation preserves the exact result." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { "dtype": "uint32", "shape": [512, 8], "data": { "kind": "cycle", "values": [3, 11, 7, 5, 13] } } |
| }, |
| "outputs": { "y": { "dtype": "uint32", "shape": [512, 8], "tolerance": 0 } } |
| }, |
| { |
| "name": "uint32_splitk_axis0_varying_exact", |
| "provenance": { |
| "notes": "A uint32 CumSum along axis 0 of an 8192x4 tensor scans across a stride-4, non-contiguous dimension with a native-integer accumulator; small cycling values (2 to 11) make the exact expected sum easy to verify." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { "dtype": "uint32", "shape": [8192, 4], "data": { "kind": "cycle", "values": [7, 3, 11, 5, 2] } } |
| }, |
| "outputs": { "y": { "dtype": "uint32", "shape": [8192, 4], "tolerance": 0 } } |
| }, |
| { |
| "name": "splitk_axis0_f32_reverse_scalar_rung_ones", |
| "provenance": { |
| "notes": "Reverse scan on the scalar split-K path uses an inner extent of six, which is not vec4-aligned. A non-power-of-workgroup axis also checks the partial final segment." |
| }, |
| "attrs": { "reverse": 1 }, |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [10000, 6], "data": { "kind": "constant", "value": 1.0 } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [10000, 6], "tolerance": 0 } } |
| }, |
| { |
| "name": "splitk_reverse_last_axis_8192_f32", |
| "provenance": { |
| "notes": "A reverse scan over an 8,192-element innermost axis exercises the minimum split-K length. Every value is a multiple of 0.25 and every partial stays below 2^10, so chunked and input-order accumulation agree exactly." |
| }, |
| "attrs": { "reverse": 1 }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 8192], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 8192], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_float32_d33_reverse0_exclusive0", |
| "provenance": { |
| "notes": "Scan-length-sized vec4 workgroup with a tail or power-of-two boundary. Binary fractions preserve exact prefix sums in both storage types." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 0, "exclusive": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 33, 16], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 33, 16], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_float32_d33_reverse1_exclusive1", |
| "provenance": { |
| "notes": "Scan-length-sized vec4 workgroup with a tail or power-of-two boundary. Binary fractions preserve exact prefix sums in both storage types." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 1, "exclusive": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 33, 16], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 33, 16], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_float32_d128_reverse0_exclusive0", |
| "provenance": { |
| "notes": "Scan-length-sized vec4 workgroup with a tail or power-of-two boundary. Binary fractions preserve exact prefix sums in both storage types." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 0, "exclusive": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 128, 16], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 128, 16], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_float32_d128_reverse1_exclusive1", |
| "provenance": { |
| "notes": "Scan-length-sized vec4 workgroup with a tail or power-of-two boundary. Binary fractions preserve exact prefix sums in both storage types." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 1, "exclusive": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 128, 16], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 128, 16], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_float32_d129_reverse0_exclusive0", |
| "provenance": { |
| "notes": "Scan-length-sized vec4 workgroup with a tail or power-of-two boundary. Binary fractions preserve exact prefix sums in both storage types." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 0, "exclusive": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 129, 16], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 129, 16], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_float32_d129_reverse1_exclusive1", |
| "provenance": { |
| "notes": "Scan-length-sized vec4 workgroup with a tail or power-of-two boundary. Binary fractions preserve exact prefix sums in both storage types." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 1, "exclusive": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 129, 16], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 129, 16], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_float32_d256_reverse0_exclusive0", |
| "provenance": { |
| "notes": "Scan-length-sized vec4 workgroup with a tail or power-of-two boundary. Binary fractions preserve exact prefix sums in both storage types." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 0, "exclusive": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 256, 16], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 256, 16], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_float32_d256_reverse1_exclusive1", |
| "provenance": { |
| "notes": "Scan-length-sized vec4 workgroup with a tail or power-of-two boundary. Binary fractions preserve exact prefix sums in both storage types." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 1, "exclusive": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 256, 16], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 256, 16], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_float16_d33_reverse0_exclusive0", |
| "provenance": { |
| "notes": "Scan-length-sized vec4 workgroup with a tail or power-of-two boundary. Binary fractions preserve exact prefix sums in both storage types." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 0, "exclusive": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [2, 33, 16], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float16", "shape": [2, 33, 16], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_float16_d33_reverse1_exclusive1", |
| "provenance": { |
| "notes": "Scan-length-sized vec4 workgroup with a tail or power-of-two boundary. Binary fractions preserve exact prefix sums in both storage types." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 1, "exclusive": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [2, 33, 16], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float16", "shape": [2, 33, 16], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_float16_d128_reverse0_exclusive0", |
| "provenance": { |
| "notes": "Scan-length-sized vec4 workgroup with a tail or power-of-two boundary. Binary fractions preserve exact prefix sums in both storage types." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 0, "exclusive": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [2, 128, 16], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float16", "shape": [2, 128, 16], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_float16_d128_reverse1_exclusive1", |
| "provenance": { |
| "notes": "Scan-length-sized vec4 workgroup with a tail or power-of-two boundary. Binary fractions preserve exact prefix sums in both storage types." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 1, "exclusive": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [2, 128, 16], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float16", "shape": [2, 128, 16], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_float16_d129_reverse0_exclusive0", |
| "provenance": { |
| "notes": "Scan-length-sized vec4 workgroup with a tail or power-of-two boundary. Binary fractions preserve exact prefix sums in both storage types." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 0, "exclusive": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [2, 129, 16], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float16", "shape": [2, 129, 16], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_float16_d129_reverse1_exclusive1", |
| "provenance": { |
| "notes": "Scan-length-sized vec4 workgroup with a tail or power-of-two boundary. Binary fractions preserve exact prefix sums in both storage types." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 1, "exclusive": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [2, 129, 16], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float16", "shape": [2, 129, 16], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_float16_d256_reverse0_exclusive0", |
| "provenance": { |
| "notes": "Scan-length-sized vec4 workgroup with a tail or power-of-two boundary. Binary fractions preserve exact prefix sums in both storage types." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 0, "exclusive": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [2, 256, 16], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float16", "shape": [2, 256, 16], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_float16_d256_reverse1_exclusive1", |
| "provenance": { |
| "notes": "Scan-length-sized vec4 workgroup with a tail or power-of-two boundary. Binary fractions preserve exact prefix sums in both storage types." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 1, "exclusive": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [2, 256, 16], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float16", "shape": [2, 256, 16], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_fanout_d32_rows2048", |
| "provenance": { |
| "notes": "A CumSum down axis 0 of length 32 for each of 2048 columns; dyadic cycle values keep every prefix exact at zero tolerance." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [32, 2048], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [32, 2048], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_fanout_d128_rows2048", |
| "provenance": { |
| "notes": "A CumSum down axis 0 of length 128 for each of 2048 columns; dyadic cycle values keep every prefix exact at zero tolerance." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [128, 2048], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [128, 2048], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_fanout_d128_rows2052", |
| "provenance": { |
| "notes": "A CumSum down axis 0 of length 128 for each of 2052 columns; dyadic cycle values keep every prefix exact at zero tolerance." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [128, 2052], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [128, 2052], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_fanout_d128_rows4096", |
| "provenance": { |
| "notes": "A CumSum down axis 0 of length 128 for each of 4096 columns; dyadic cycle values keep every prefix exact at zero tolerance." |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [128, 4096], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [128, 4096], "tolerance": 0 } } |
| }, |
| { |
| "name": "short_strided_varying_reverse", |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 127, 16], |
| "data": { "kind": "fillFloat32", "scale": 0.1, "sinStep": 0.13, "cosStep": 0.27 } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 127, 16], "tolerance": 0.001, "relTolerance": 0.001 } } |
| }, |
| { |
| "name": "ort_1d_uint32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest._1DTestUint32_webgpu" |
| }, |
| "args": { "axis": 0 }, |
| "inputs": { "x": { "dtype": "uint32", "shape": [5], "data": { "kind": "values", "values": [1, 2, 3, 4, 5] } } }, |
| "outputs": { "y": { "dtype": "uint32", "shape": [5], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_int32_axis1_width1000_inner1", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest.CudaInt64BlockScanMultiTile", |
| "notes": "Upstream fills the tensor with i % 7 - 3 and scans axis 1; the `cycle` of [-3..3] reproduces that exactly. outer=1, width=1000, inner=1, i.e. one long contiguous scan row of a non-power-of-two length that spans several workgroup-scan chunks." |
| }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "int32", |
| "shape": [1, 1000, 1], |
| "data": { "kind": "cycle", "values": [-3, -2, -1, 0, 1, 2, 3] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "int32", "shape": [1, 1000, 1], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_int32_axis1_width1000_inner1_reverse_exclusive", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest.CudaInt64BlockScanMultiTile", |
| "notes": "reverse+exclusive arm of the same shape: upstream runs all four (exclusive, reverse) combinations." |
| }, |
| "attrs": { "exclusive": 1, "reverse": 1 }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "int32", |
| "shape": [1, 1000, 1], |
| "data": { "kind": "cycle", "values": [-3, -2, -1, 0, 1, 2, 3] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "int32", "shape": [1, 1000, 1], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_int32_axis1_width513_inner3", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest.CudaInt64BlockScanMultiTile", |
| "notes": "outer=2, width=513, inner=3: an odd, just-past-512 scan length with a strided (inner=3) layout, so the scan is neither contiguous nor chunk-aligned." |
| }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { "dtype": "int32", "shape": [2, 513, 3], "data": { "kind": "cycle", "values": [-3, -2, -1, 0, 1, 2, 3] } } |
| }, |
| "outputs": { "y": { "dtype": "int32", "shape": [2, 513, 3], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_int32_axis1_width513_inner3_reverse_exclusive", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest.CudaInt64BlockScanMultiTile", |
| "notes": "reverse+exclusive arm of the strided 513x3 shape." |
| }, |
| "attrs": { "exclusive": 1, "reverse": 1 }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { "dtype": "int32", "shape": [2, 513, 3], "data": { "kind": "cycle", "values": [-3, -2, -1, 0, 1, 2, 3] } } |
| }, |
| "outputs": { "y": { "dtype": "int32", "shape": [2, 513, 3], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_int32_axis1_width2_minimal_exclusive", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/math/cumsum_test.cc", |
| "test": "CumSumTest.CudaInt64GenericKernelWidthTwo", |
| "notes": "Upstream added CudaInt64GenericKernelWidthTwo specifically because width 2 falls below every fast path and must land on the generic kernel." |
| }, |
| "attrs": { "exclusive": 1 }, |
| "args": { "axis": 1 }, |
| "inputs": { |
| "x": { "dtype": "int32", "shape": [1, 2, 1], "data": { "kind": "cycle", "values": [-3, -2, -1, 0, 1, 2, 3] } } |
| }, |
| "outputs": { "y": { "dtype": "int32", "shape": [1, 2, 1], "tolerance": 0 } } |
| }, |
| { |
| "name": "carry_topology_n1023_float32_inner1_rev0_exc0", |
| "provenance": { |
| "notes": "A forward inclusive float32 CumSum over three 1023-element rows, one below 1024; dyadic cycle values keep every prefix exact at zero tolerance." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 0, "exclusive": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 1023], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 1023], "tolerance": 0 } } |
| }, |
| { |
| "name": "carry_topology_n1024_float32_inner1_rev0_exc0", |
| "provenance": { |
| "notes": "A forward inclusive float32 CumSum over three 1024-element rows; dyadic cycle values keep every prefix exact at zero tolerance." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 0, "exclusive": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 1024], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 1024], "tolerance": 0 } } |
| }, |
| { |
| "name": "carry_topology_n1025_float32_inner1_rev0_exc0", |
| "provenance": { |
| "notes": "A forward inclusive float32 CumSum over three 1025-element rows, one above 1024; dyadic cycle values keep every prefix exact at zero tolerance." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 0, "exclusive": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 1025], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 1025], "tolerance": 0 } } |
| }, |
| { |
| "name": "carry_topology_n2047_float32_inner1_rev0_exc0", |
| "provenance": { |
| "notes": "A forward inclusive float32 CumSum over three 2047-element rows, one below 2048; dyadic cycle values keep every prefix exact at zero tolerance." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 0, "exclusive": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 2047], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 2047], "tolerance": 0 } } |
| }, |
| { |
| "name": "carry_topology_n2048_float32_inner1_rev0_exc0", |
| "provenance": { |
| "notes": "A forward inclusive float32 CumSum over three 2048-element rows; dyadic cycle values keep every prefix exact at zero tolerance." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 0, "exclusive": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 2048], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 2048], "tolerance": 0 } } |
| }, |
| { |
| "name": "carry_topology_n2049_float32_inner1_rev0_exc0", |
| "provenance": { |
| "notes": "A forward inclusive float32 CumSum over three 2049-element rows, one above 2048; dyadic cycle values keep every prefix exact at zero tolerance." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 0, "exclusive": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 2049], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 2049], "tolerance": 0 } } |
| }, |
| { |
| "name": "carry_topology_n1537_float32_inner1_rev0_exc0_single_segment", |
| "provenance": { |
| "notes": "A forward inclusive float32 CumSum over three 1537-element rows; dyadic cycle values keep every prefix exact at zero tolerance." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 0, "exclusive": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 1537], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 1537], "tolerance": 0 } }, |
| "tunables": { "SPLITK_MIN_DIM": 1024, "SPLITK_CHUNK_DIM": 2048 } |
| }, |
| { |
| "name": "carry_topology_n1537_float32_inner1_rev1_exc1_single_segment", |
| "provenance": { |
| "notes": "A reverse exclusive float32 CumSum over three 1537-element rows; dyadic cycle values keep every prefix exact at zero tolerance." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 1, "exclusive": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 1537], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 1537], "tolerance": 0 } }, |
| "tunables": { "SPLITK_MIN_DIM": 1024, "SPLITK_CHUNK_DIM": 2048 } |
| }, |
| { |
| "name": "carry_topology_n1537_float16_inner1_rev0_exc0_single_segment", |
| "provenance": { |
| "notes": "A forward inclusive float16 CumSum over three 1537-element rows; dyadic cycle values keep every prefix exact at zero tolerance." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 0, "exclusive": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [3, 1537], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float16", "shape": [3, 1537], "tolerance": 0 } }, |
| "tunables": { "SPLITK_MIN_DIM": 1024, "SPLITK_CHUNK_DIM": 2048 } |
| }, |
| { |
| "name": "carry_topology_n1537_float16_inner1_rev1_exc1_single_segment", |
| "provenance": { |
| "notes": "A reverse exclusive float16 CumSum over three 1537-element rows; dyadic cycle values keep every prefix exact at zero tolerance." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 1, "exclusive": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [3, 1537], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float16", "shape": [3, 1537], "tolerance": 0 } }, |
| "tunables": { "SPLITK_MIN_DIM": 1024, "SPLITK_CHUNK_DIM": 2048 } |
| }, |
| { |
| "name": "carry_topology_n1537_int32_inner1_rev0_exc0_single_segment", |
| "provenance": { |
| "notes": "A forward inclusive int32 CumSum over three 1537-element rows; cycle values beyond 2^24 need exact int32 accumulation at zero tolerance." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 0, "exclusive": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "int32", |
| "shape": [3, 1537], |
| "data": { "kind": "cycle", "values": [16777217, -16777216, 3, -2] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "int32", "shape": [3, 1537], "tolerance": 0 } }, |
| "tunables": { "SPLITK_MIN_DIM": 1024, "SPLITK_CHUNK_DIM": 2048 } |
| }, |
| { |
| "name": "carry_topology_n1537_int32_inner1_rev1_exc1_single_segment", |
| "provenance": { |
| "notes": "A reverse exclusive int32 CumSum over three 1537-element rows; cycle values beyond 2^24 need exact int32 accumulation at zero tolerance." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 1, "exclusive": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "int32", |
| "shape": [3, 1537], |
| "data": { "kind": "cycle", "values": [16777217, -16777216, 3, -2] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "int32", "shape": [3, 1537], "tolerance": 0 } }, |
| "tunables": { "SPLITK_MIN_DIM": 1024, "SPLITK_CHUNK_DIM": 2048 } |
| }, |
| { |
| "name": "carry_topology_n1537_uint32_inner1_rev0_exc0_single_segment", |
| "provenance": { |
| "notes": "A forward inclusive uint32 CumSum over three 1537-element rows; a cycle containing 4,294,967,295 needs wrapping uint32 accumulation at zero tolerance." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 0, "exclusive": 0 }, |
| "inputs": { |
| "x": { "dtype": "uint32", "shape": [3, 1537], "data": { "kind": "cycle", "values": [4294967295, 7, 1, 2] } } |
| }, |
| "outputs": { "y": { "dtype": "uint32", "shape": [3, 1537], "tolerance": 0 } }, |
| "tunables": { "SPLITK_MIN_DIM": 1024, "SPLITK_CHUNK_DIM": 2048 } |
| }, |
| { |
| "name": "carry_topology_n1537_uint32_inner1_rev1_exc1_single_segment", |
| "provenance": { |
| "notes": "A reverse exclusive uint32 CumSum over three 1537-element rows; a cycle containing 4,294,967,295 needs wrapping uint32 accumulation at zero tolerance." |
| }, |
| "args": { "axis": 1 }, |
| "attrs": { "reverse": 1, "exclusive": 1 }, |
| "inputs": { |
| "x": { "dtype": "uint32", "shape": [3, 1537], "data": { "kind": "cycle", "values": [4294967295, 7, 1, 2] } } |
| }, |
| "outputs": { "y": { "dtype": "uint32", "shape": [3, 1537], "tolerance": 0 } }, |
| "tunables": { "SPLITK_MIN_DIM": 1024, "SPLITK_CHUNK_DIM": 2048 } |
| }, |
| { |
| "name": "carry_topology_n1537_float32_inner4_rev0_exc1_single_segment", |
| "provenance": { |
| "notes": "A forward exclusive float32 CumSum along a 1537-step axis with four interleaved columns; dyadic cycle values keep every prefix exact at zero tolerance." |
| }, |
| "args": { "axis": 0 }, |
| "attrs": { "reverse": 0, "exclusive": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [1537, 4], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [1537, 4], "tolerance": 0 } }, |
| "tunables": { "SPLITK_MIN_DIM": 1024, "SPLITK_CHUNK_DIM": 2048 } |
| }, |
| { |
| "name": "carry_topology_n1537_float32_inner4_rev1_exc0_single_segment", |
| "provenance": { |
| "notes": "A reverse inclusive float32 CumSum along a 1537-step axis with four interleaved columns; dyadic cycle values keep every prefix exact at zero tolerance." |
| }, |
| "args": { "axis": 0 }, |
| "attrs": { "reverse": 1, "exclusive": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [1537, 4], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [1537, 4], "tolerance": 0 } }, |
| "tunables": { "SPLITK_MIN_DIM": 1024, "SPLITK_CHUNK_DIM": 2048 } |
| }, |
| { |
| "name": "carry_topology_n1537_float16_inner4_rev0_exc1_single_segment", |
| "provenance": { |
| "notes": "A forward exclusive float16 CumSum along a 1537-step axis with four interleaved columns; dyadic cycle values keep every prefix exact at zero tolerance." |
| }, |
| "args": { "axis": 0 }, |
| "attrs": { "reverse": 0, "exclusive": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [1537, 4], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float16", "shape": [1537, 4], "tolerance": 0 } }, |
| "tunables": { "SPLITK_MIN_DIM": 1024, "SPLITK_CHUNK_DIM": 2048 } |
| }, |
| { |
| "name": "carry_topology_n1537_float16_inner4_rev1_exc0_single_segment", |
| "provenance": { |
| "notes": "A reverse inclusive float16 CumSum along a 1537-step axis with four interleaved columns; dyadic cycle values keep every prefix exact at zero tolerance." |
| }, |
| "args": { "axis": 0 }, |
| "attrs": { "reverse": 1, "exclusive": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [1537, 4], |
| "data": { "kind": "cycle", "values": [1.0, -1.0, 0.5, -0.5, 0.25, -0.25, 0.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float16", "shape": [1537, 4], "tolerance": 0 } }, |
| "tunables": { "SPLITK_MIN_DIM": 1024, "SPLITK_CHUNK_DIM": 2048 } |
| } |
| ] |
| } |
|
|
