| { |
| "op": "ai.onnx.ReduceSumSquare", |
| "fixtureArrays": { |
| "rank3_axis1_middle_no_keepdims_input_x": [-1, 2, -3, 4, 0.5, -0.5, 1.5, -1.5, 5, -6, 7, -8, -2, 0, 3, -4, 9, -10, 0.25, -0.75, -1.25, 2.25, -3.25, 4.25] |
| }, |
| "cases": [ |
| { |
| "name": "int32_axis0_splitk_8192x2", |
| "attrs": { "axes": [0], "keepdims": 0 }, |
| "inputs": { "x": { "dtype": "int32", "shape": [8192, 2], "data": { "kind": "cycle", "values": [1, -1, 2, -2] } } }, |
| "outputs": { "y": { "dtype": "int32", "shape": [2], "tolerance": 0 } } |
| }, |
| { |
| "name": "all_axes_flat_rank1_boundary_8192", |
| "provenance": { |
| "notes": "The parallel full-reduction threshold must supersede the rank1 serial and row-reduction fallbacks." |
| }, |
| "attrs": { "axes": [0], "keepdims": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [8192], "data": { "kind": "constant", "value": 1.0 } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [], "tolerance": 0 } } |
| }, |
| { |
| "name": "all_axes_flat_fullreduce_32x32x32_keepdims", |
| "attrs": { "keepdims": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [32, 32, 32], |
| "data": { "kind": "fillFloat32", "sinStep": 0.013, "cosStep": 0.027, "scale": 0.5 } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [1, 1, 1], "tolerance": 0.1, "relTolerance": 0.0001 } } |
| }, |
| { |
| "name": "dispatch_cliff_axis1_rank2", |
| "attrs": { "axes": [1], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [16776961, 1], |
| "data": { "kind": "fillFloat32", "sinStep": 0.0009765625, "cosStep": 0.00048828125, "scale": 0.25 } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [16776961], "tolerance": 0.0001 } } |
| }, |
| { |
| "name": "axis0", |
| "attrs": { "axes": [0], "keepdims": 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": [3], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "axis0_tiled_64x32", |
| "attrs": { "axes": [0], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [64, 32], |
| "data": { "kind": "fillFloat32", "sinStep": 0.17, "cosStep": 0.07, "scale": 0.2 } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [32], "tolerance": 0.00002 } } |
| }, |
| { |
| "name": "f32_normal_inputs_subnormal_square_sum_axis0_tilecols_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/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.ReduceSumSquare", |
| "notes": "Tiled axis-0 companion: 64 normal tiny inputs produce a finite subnormal square-sum per column." |
| }, |
| "attrs": { "axes": [0], "keepdims": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [64, 16], "data": { "kind": "constant", "value": 1e-20 } } }, |
| "outputs": { |
| "y": { "dtype": "float32", "shape": [16], "tolerance": 5e-44, "data": { "kind": "constant", "value": 6.4e-39 } } |
| } |
| }, |
| { |
| "name": "axis1", |
| "attrs": { "axes": [1], "keepdims": 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], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "f32_normal_inputs_subnormal_square_sum_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/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.ReduceSumSquare", |
| "notes": "Inputs are normal float32 values, but their squares and row sums are finite subnormals; the square/reduction path must preserve them." |
| }, |
| "attrs": { "axes": [1], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3], |
| "data": { "kind": "values", "values": [1e-20, -1e-20, 0.0, 2e-20, -2e-20, 1e-20] } |
| } |
| }, |
| "outputs": { |
| "y": { |
| "dtype": "float32", |
| "shape": [2], |
| "tolerance": 6e-45, |
| "data": { "kind": "values", "values": [2e-40, 9e-40] } |
| } |
| } |
| }, |
| { |
| "name": "f32_normal_inputs_subnormal_square_sum_axis0_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/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.ReduceSumSquare", |
| "notes": "Axis-0 companion: normal inputs with finite subnormal square sums should not reduce to zero." |
| }, |
| "attrs": { "axes": [0], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 2], |
| "data": { "kind": "values", "values": [1e-20, -1e-20, -1e-20, 0.0, 0.0, 2e-20] } |
| } |
| }, |
| "outputs": { |
| "y": { |
| "dtype": "float32", |
| "shape": [2], |
| "tolerance": 6e-45, |
| "data": { "kind": "values", "values": [2e-40, 5e-40] } |
| } |
| } |
| }, |
| { |
| "name": "f32_many_tiny_normals_square_sum_to_normal_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/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.ReduceSumSquare", |
| "notes": "Many tiny normal inputs have individually subnormal squares but a normal finite square-sum; flushing intermediate squares loses the reduction." |
| }, |
| "attrs": { "axes": [1], "keepdims": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [1, 1024], "data": { "kind": "constant", "value": 1e-20 } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [1], "tolerance": 1e-42 } } |
| }, |
| { |
| "name": "f32_normal_inputs_subnormal_square_sum_last_axis_vec4_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/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.ReduceSumSquare", |
| "notes": "Vec4 last-axis companion: normal tiny inputs should produce finite subnormal square sums." |
| }, |
| "attrs": { "axes": [-1], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 4], |
| "data": { "kind": "values", "values": [1e-20, -1e-20, 0.0, 0.0, 2e-20, 0.0, 0.0, 0.0] } |
| } |
| }, |
| "outputs": { |
| "y": { |
| "dtype": "float32", |
| "shape": [2], |
| "tolerance": 6e-45, |
| "data": { "kind": "values", "values": [2e-40, 4e-40] } |
| } |
| } |
| }, |
| { |
| "name": "f32_normal_inputs_subnormal_square_sum_last_axis_odd_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/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.ReduceSumSquare", |
| "notes": "Odd-width last-axis companion: normal tiny values should produce finite subnormal square sums in the non-vec4 subgroup reducer." |
| }, |
| "attrs": { "axes": [-1], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3], |
| "data": { "kind": "values", "values": [1e-20, -1e-20, 0.0, 2e-20, -2e-20, 1e-20] } |
| } |
| }, |
| "outputs": { |
| "y": { |
| "dtype": "float32", |
| "shape": [2], |
| "tolerance": 6e-45, |
| "data": { "kind": "values", "values": [2e-40, 9e-40] } |
| } |
| } |
| }, |
| { |
| "name": "f32_normal_inputs_subnormal_square_sum_rank3_axis1_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/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.ReduceSumSquare", |
| "notes": "Rank-3 axis-1 companion: normal tiny values should produce finite subnormal square sums through middle-axis indexing." |
| }, |
| "attrs": { "axes": [1], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3, 2], |
| "data": { |
| "kind": "values", |
| "values": [1e-20, -1e-20, -1e-20, 0.0, 0.0, 2e-20, 2e-20, 0.0, 0.0, -2e-20, 1e-20, 0.0] |
| } |
| } |
| }, |
| "outputs": { |
| "y": { |
| "dtype": "float32", |
| "shape": [2, 2], |
| "tolerance": 6e-45, |
| "data": { "kind": "values", "values": [2e-40, 5e-40, 5e-40, 4e-40] } |
| } |
| } |
| }, |
| { |
| "name": "f32_normal_inputs_subnormal_square_sum_rank3_all_axes_scalar_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/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.ReduceSumSquare_default_axes_do_not_keep_dims", |
| "notes": "Rank-3 default-axes companion: normal tiny values should produce a finite subnormal square-sum scalar." |
| }, |
| "attrs": { "keepdims": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [2, 3, 2], "data": { "kind": "constant", "value": 1e-20 } } }, |
| "outputs": { |
| "y": { "dtype": "float32", "shape": [], "tolerance": 1e-44, "data": { "kind": "values", "values": [1.2e-39] } } |
| } |
| }, |
| { |
| "name": "f32_normal_inputs_subnormal_square_sum_rank3_all_axes_keepdims_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/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.ReduceSumSquare_default_axes_keepdims", |
| "notes": "Rank-3 default-axes keepdims companion: normal tiny values should produce a finite subnormal square-sum in shape [1,1,1]." |
| }, |
| "attrs": { "keepdims": 1 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [2, 3, 2], "data": { "kind": "constant", "value": 1e-20 } } }, |
| "outputs": { |
| "y": { |
| "dtype": "float32", |
| "shape": [1, 1, 1], |
| "tolerance": 1e-44, |
| "data": { "kind": "values", "values": [1.2e-39] } |
| } |
| } |
| }, |
| { |
| "name": "axis1_empty_cols_identity_zero", |
| "attrs": { "axes": [1], "keepdims": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [2, 0], "data": { "kind": "values", "values": [] } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2], "tolerance": 0 } } |
| }, |
| { |
| "name": "axis0_empty_rows_identity_zero", |
| "attrs": { "axes": [0], "keepdims": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [0, 3], "data": { "kind": "values", "values": [] } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3], "tolerance": 0 } } |
| }, |
| { |
| "name": "axis1_zero_rows_noop", |
| "attrs": { "axes": [1], "keepdims": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [0, 3], "data": { "kind": "values", "values": [] } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [0], "tolerance": 0 } } |
| }, |
| { |
| "name": "axis_minus_one_keepdims", |
| "attrs": { "axes": [-1], "keepdims": 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, 1], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "rank3_axis1_middle_no_keepdims", |
| "attrs": { "axes": [1], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3, 4], |
| "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/rank3_axis1_middle_no_keepdims_input_x" } } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 4], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_empty_rank3_middle_axis_keepdims", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.empty_set_ReduceSumSquare_13" |
| }, |
| "attrs": { "axes": [1], "keepdims": 1 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [2, 0, 4], "data": { "kind": "values", "values": [] } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 1, 4], "tolerance": 0 } } |
| }, |
| { |
| "name": "rank4_axis1_channel_no_keepdims", |
| "attrs": { "axes": [1], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 4, 3, 2], |
| "data": { |
| "kind": "values", |
| "values": [1.0, -2.0, 3.0, -4.0, 5.0, -6.0, -1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 0.5, -1.5, 2.5, -3.5, 4.5, -5.5, -0.5, 1.5, -2.5, 3.5, -4.5, 5.5, 6.0, -7.0, 8.0, -9.0, 10.0, -11.0, -6.0, 7.0, -8.0, 9.0, -10.0, 11.0, 1.25, -2.25, 3.25, -4.25, 5.25, -6.25, -1.25, 2.25, -3.25, 4.25, -5.25, 6.25] |
| } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3, 2], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "rank1_axis0_scalar_output", |
| "attrs": { "axes": [0], "keepdims": 0 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [5], "data": { "kind": "values", "values": [-2.0, 3.0, -4.0, 0.5, 1.5] } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_axis1_rank3_no_keepdims", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.ReduceSumSquare_do_not_keepdims" |
| }, |
| "attrs": { "axes": [1], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 2, 2], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 2], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_axis1_rank3_keepdims", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.ReduceSumSquare_keepdims" |
| }, |
| "attrs": { "axes": [1], "keepdims": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 2, 2], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 1, 2], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_axis0_rank1_scalar", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.ReduceSumSquare_do_not_keepdims_2" |
| }, |
| "attrs": { "axes": [0], "keepdims": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [3], "data": { "kind": "values", "values": [1.0, 2.0, 3.0] } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_rank0_scalar", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.ReduceSumSquare0DTensor" |
| }, |
| "inputs": { "x": { "dtype": "float32", "shape": [], "data": { "kind": "values", "values": [2.0] } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [], "tolerance": 0 } } |
| }, |
| { |
| "name": "onnx_backend_reduce_sum_square_do_not_keepdims_example", |
| "attrs": { "keepdims": 0, "axes": [1] }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 2, 2], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 2] } }, |
| "provenance": { |
| "source": "cmake/external/onnx/onnx/backend/test/data/node/test_reduce_sum_square_do_not_keepdims_example", |
| "notes": "The ONNX int64 axes input is materialized as this compile-time axes list." |
| } |
| }, |
| { |
| "name": "onnx_backend_reduce_sum_square_do_not_keepdims_random", |
| "attrs": { "keepdims": 0, "axes": [1] }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 2, 2], |
| "data": { |
| "kind": "values", |
| "values": [0.9762700796127319, 4.3037872314453125, 2.055267572402954, 0.8976636528968811, -1.5269039869308472, 2.917882204055786, -1.248255729675293, 7.835460186004639, 9.273255348205566, -2.331169605255127, 5.834500789642334, 0.577898383140564] |
| } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 2] } }, |
| "provenance": { |
| "source": "cmake/external/onnx/onnx/backend/test/data/node/test_reduce_sum_square_do_not_keepdims_random", |
| "notes": "The ONNX int64 axes input is materialized as this compile-time axes list." |
| } |
| }, |
| { |
| "name": "onnx_backend_reduce_sum_square_empty_set", |
| "attrs": { "keepdims": 1, "axes": [1] }, |
| "inputs": { "x": { "dtype": "float32", "shape": [2, 0, 4], "data": { "kind": "values", "values": [] } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 1, 4] } }, |
| "provenance": { |
| "source": "cmake/external/onnx/onnx/backend/test/data/node/test_reduce_sum_square_empty_set", |
| "notes": "The ONNX int64 axes input is materialized as this compile-time axes list." |
| } |
| }, |
| { |
| "name": "onnx_backend_reduce_sum_square_keepdims_example", |
| "attrs": { "keepdims": 1, "axes": [1] }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 2, 2], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 1, 2] } }, |
| "provenance": { |
| "source": "cmake/external/onnx/onnx/backend/test/data/node/test_reduce_sum_square_keepdims_example", |
| "notes": "The ONNX int64 axes input is materialized as this compile-time axes list." |
| } |
| }, |
| { |
| "name": "onnx_backend_reduce_sum_square_keepdims_random", |
| "attrs": { "keepdims": 1, "axes": [1] }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 2, 2], |
| "data": { |
| "kind": "values", |
| "values": [0.9762700796127319, 4.3037872314453125, 2.055267572402954, 0.8976636528968811, -1.5269039869308472, 2.917882204055786, -1.248255729675293, 7.835460186004639, 9.273255348205566, -2.331169605255127, 5.834500789642334, 0.577898383140564] |
| } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 1, 2] } }, |
| "provenance": { |
| "source": "cmake/external/onnx/onnx/backend/test/data/node/test_reduce_sum_square_keepdims_random", |
| "notes": "The ONNX int64 axes input is materialized as this compile-time axes list." |
| } |
| }, |
| { |
| "name": "onnx_backend_reduce_sum_square_negative_axes_keepdims_example", |
| "attrs": { "keepdims": 1, "axes": [-2] }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 2, 2], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 1, 2] } }, |
| "provenance": { |
| "source": "cmake/external/onnx/onnx/backend/test/data/node/test_reduce_sum_square_negative_axes_keepdims_example", |
| "notes": "The ONNX int64 axes input is materialized as this compile-time axes list." |
| } |
| }, |
| { |
| "name": "onnx_backend_reduce_sum_square_negative_axes_keepdims_random", |
| "attrs": { "keepdims": 1, "axes": [-2] }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 2, 2], |
| "data": { |
| "kind": "values", |
| "values": [0.9762700796127319, 4.3037872314453125, 2.055267572402954, 0.8976636528968811, -1.5269039869308472, 2.917882204055786, -1.248255729675293, 7.835460186004639, 9.273255348205566, -2.331169605255127, 5.834500789642334, 0.577898383140564] |
| } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 1, 2] } }, |
| "provenance": { |
| "source": "cmake/external/onnx/onnx/backend/test/data/node/test_reduce_sum_square_negative_axes_keepdims_random", |
| "notes": "The ONNX int64 axes input is materialized as this compile-time axes list." |
| } |
| }, |
| { |
| "name": "ort_default_axes_rank3_no_keepdims_scalar", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.ReduceSumSquare_default_axes_do_not_keep_dims", |
| "notes": "Default axes reduce all input dimensions to a rank-0 scalar when keepdims=0." |
| }, |
| "attrs": { "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 2, 2], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [], "tolerance": 0 } } |
| }, |
| { |
| "name": "onnx_backend_reduce_sum_square_default_axes_keepdims_example", |
| "provenance": { |
| "source": "cmake/external/onnx/onnx/backend/test/data/node/test_reduce_sum_square_default_axes_keepdims_example" |
| }, |
| "attrs": { "keepdims": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 2, 2], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [1, 1, 1] } } |
| }, |
| { |
| "name": "onnx_backend_reduce_sum_square_default_axes_keepdims_random", |
| "provenance": { |
| "source": "cmake/external/onnx/onnx/backend/test/data/node/test_reduce_sum_square_default_axes_keepdims_random" |
| }, |
| "attrs": { "keepdims": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 2, 2], |
| "data": { |
| "kind": "values", |
| "values": [0.9762700796127319, 4.3037872314453125, 2.055267572402954, 0.8976636528968811, -1.5269039869308472, 2.917882204055786, -1.248255729675293, 7.835460186004639, 9.273255348205566, -2.331169605255127, 5.834500789642334, 0.577898383140564] |
| } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [1, 1, 1] } } |
| }, |
| { |
| "name": "subgroup_vec4_last_axis_2x256", |
| "attrs": { "axes": [-1], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 256], |
| "data": { "kind": "fillFloat32", "sinStep": 0.13, "cosStep": 0.29 } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2], "tolerance": 0.0002, "relTolerance": 0.0001 } } |
| }, |
| { |
| "name": "subgroup_scalar_last_axis_2x65", |
| "attrs": { "axes": [1], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 65], |
| "data": { "kind": "fillFloat32", "sinStep": 0.23, "cosStep": 0.11 } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2], "tolerance": 0.0002, "relTolerance": 0.0001 } } |
| }, |
| { |
| "name": "ort_noop_empty_axes_2d_elementwise_square", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.ReduceSumSquare_NoopWithEmptyAxes_2D_ElementwiseSquare" |
| }, |
| "attrs": { "noop_with_empty_axes": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3], |
| "data": { "kind": "values", "values": [-1.0, 2.0, -3.0, 0.5, -0.5, 4.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_noop_empty_axes_scalar_square", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.ReduceSumSquare_NoopWithEmptyAxes_Scalar" |
| }, |
| "attrs": { "noop_with_empty_axes": 1 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [], "data": { "kind": "values", "values": [-3.0] } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_noop_empty_axes_3d_elementwise_square", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.ReduceSumSquare_NoopWithEmptyAxes_3D_ElementwiseSquare" |
| }, |
| "attrs": { "noop_with_empty_axes": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 1, 3], |
| "data": { "kind": "values", "values": [-1.0, 2.0, -3.0, 0.5, -0.5, 4.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 1, 3], "tolerance": 0 } } |
| }, |
| { |
| "name": "ort_int32_multi_axis_keepdims", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.ReduceSumSquare_int32" |
| }, |
| "attrs": { "axes": [0, 2], "keepdims": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "int32", |
| "shape": [3, 2, 2], |
| "data": { "kind": "values", "values": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] } |
| } |
| }, |
| "outputs": { |
| "y": { |
| "dtype": "int32", |
| "shape": [1, 2, 1], |
| "data": { "kind": "values", "values": [247, 403] }, |
| "tolerance": 0 |
| } |
| } |
| }, |
| { |
| "name": "ort_int32_square_overflow_saturates_gpu_gap", |
| "skipGpu": { |
| "category": "todo", |
| "reason": "The current integer reduction route uses an i32 accumulator, so it cannot reproduce the fixture's widened intermediate arithmetic and final int32 saturation. A portable multiword accumulator can implement this behavior." |
| }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.ReduceSumSquare_int32_Overflow_Saturates" |
| }, |
| "attrs": { "axes": [0], "keepdims": 1 }, |
| "inputs": { "x": { "dtype": "int32", "shape": [2], "data": { "kind": "values", "values": [50000, 50000] } } }, |
| "outputs": { |
| "y": { "dtype": "int32", "shape": [1], "data": { "kind": "values", "values": [2147483647] }, "tolerance": 0 } |
| } |
| }, |
| { |
| "name": "ort_float_multi_axis_keepdims", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/reduction/reduction_ops_test.cc", |
| "test": "ReductionOpTest.ReduceSumSquare" |
| }, |
| "attrs": { "axes": [0, 2], "keepdims": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 2, 2], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [1, 2, 1], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "rank3_lastaxis_cols1024_tree_nosubgroup", |
| "attrs": { "axes": [2], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 2, 1024], |
| "data": { |
| "kind": "cycle", |
| "values": [1.0, -2.0, 0.5, 3.25, -1.5, 2.0, -0.75, 4.0, -3.5, 1.25, 0.0, -2.25, 5.0, -4.0, 2.75, -1.0] |
| } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 2], "tolerance": 0.00001 } } |
| }, |
| { |
| "name": "axis0_splitk_8192x32", |
| "attrs": { "axes": [0], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [8192, 32], |
| "data": { "kind": "fillFloat32", "sinStep": 0.17, "cosStep": 0.07, "scale": 0.2 } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [32], "tolerance": 0.001 } } |
| }, |
| { |
| "name": "axis0_splitk_8192x48_keepdims", |
| "attrs": { "axes": [0], "keepdims": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [8192, 48], |
| "data": { "kind": "fillFloat32", "sinStep": 0.17, "cosStep": 0.07, "scale": 0.2 } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [1, 48], "tolerance": 0.001 } } |
| }, |
| { |
| "name": "rank3_axis0_no_keepdims", |
| "attrs": { "axes": [0], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3, 4], |
| "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/rank3_axis1_middle_no_keepdims_input_x" } } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 4], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "rank3_axis0_keepdims", |
| "attrs": { "axes": [0], "keepdims": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3, 4], |
| "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/rank3_axis1_middle_no_keepdims_input_x" } } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [1, 3, 4], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "rank4_axis0_no_keepdims", |
| "attrs": { "axes": [0], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 2, 3, 2], |
| "data": { |
| "kind": "values", |
| "values": [1.0, -2.0, 3.0, -4.0, 5.0, -6.0, -1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 0.5, -1.5, 2.5, -3.5, 4.5, -5.5, -0.5, 1.5, -2.5, 3.5, -4.5, 5.5] |
| } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3, 2], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "rank4_lastaxis_vec4_keepdims", |
| "attrs": { "axes": [-1], "keepdims": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3, 4, 8], |
| "data": { "kind": "fillFloat32", "sinStep": 0.13, "cosStep": 0.29, "scale": 0.2 } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3, 4, 1], "tolerance": 0.0002, "relTolerance": 0.0001 } } |
| }, |
| { |
| "name": "rank4_multi_axis_12_keepdims", |
| "attrs": { "axes": [1, 2], "keepdims": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3, 2, 2], |
| "data": { |
| "kind": "values", |
| "values": [0.5, -1.0, 2.0, -0.25, 1.5, 0.75, -2.0, 1.0, 0.125, -0.5, 3.0, -1.5, 0.25, 2.5, -0.75, 1.25, -3.0, 0.5, 2.0, -1.0, 0.75, -0.25, 1.5, -2.5] |
| } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 1, 1, 2], "tolerance": 0.001 } } |
| }, |
| { |
| "name": "noop_empty_axes_squares_negative_input", |
| "attrs": { "noop_with_empty_axes": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3], |
| "data": { "kind": "values", "values": [-3.0, 2.0, -1.0, 0.0, -4.0, 5.0] } |
| } |
| }, |
| "outputs": { |
| "y": { |
| "dtype": "float32", |
| "shape": [2, 3], |
| "data": { "kind": "values", "values": [9.0, 4.0, 1.0, 0.0, 16.0, 25.0] }, |
| "tolerance": 0 |
| } |
| } |
| }, |
| { |
| "name": "axis0_splitk_combine_no_spurious_finalization", |
| "attrs": { "axes": [0], "keepdims": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [8192, 16], "data": { "kind": "constant", "value": 2.0 } } }, |
| "outputs": { |
| "y": { "dtype": "float32", "shape": [16], "data": { "kind": "constant", "value": 32768.0 }, "tolerance": 0.01 } |
| } |
| }, |
| { |
| "name": "int32_sumsquare_small_values_exact", |
| "attrs": { "axes": [1], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "int32", |
| "shape": [3, 4], |
| "data": { "kind": "values", "values": [1, -2, 3, -4, 5, -6, 7, -8, -3, 4, -5, 6] } |
| } |
| }, |
| "outputs": { |
| "y": { "dtype": "int32", "shape": [3], "data": { "kind": "values", "values": [30, 174, 86] }, "tolerance": 0 } |
| } |
| }, |
| { |
| "name": "axis0_narrow_f32_8192x3_splitk_guard_lock", |
| "provenance": { |
| "notes": "Compact lock below the historical 16-column split-K guard. Constant ones make square accumulation exactly 8192." |
| }, |
| "attrs": { "axes": [0], "keepdims": 0 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [8192, 3], "data": { "kind": "constant", "value": 1.0 } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3], "tolerance": 0 } } |
| }, |
| { |
| "name": "contiguous_suffix_axes12_parallel", |
| "provenance": { |
| "notes": "Contiguous axes {1,2} exercise the shared cooperative suffix reduction instead of one serial lane per output." |
| }, |
| "attrs": { "axes": [1, 2], "keepdims": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 16, 16], |
| "data": { "kind": "fillFloat32", "sinStep": 0.13, "cosStep": 0.07, "scale": 0.2 } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 1, 1], "tolerance": 0.00001 } } |
| }, |
| { |
| "name": "axis_split_rank3_axis1_2x8192x4", |
| "attrs": { "axes": [1], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 8192, 4], |
| "data": { "kind": "fillFloat32", "sinStep": 0.17, "cosStep": 0.07, "scale": 0.2 } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 4], "tolerance": 0.001 } } |
| }, |
| { |
| "name": "f16_axis_split_tiled_narrow_2x8192x4", |
| "attrs": { "axes": [1], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [2, 8192, 4], |
| "data": { "kind": "fillFloat32", "sinStep": 0.17, "cosStep": 0.07, "scale": 0.2 } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float16", "shape": [2, 4], "tolerance": 0.05, "relTolerance": 0.01 } } |
| }, |
| { |
| "name": "axis_split_rank3_axis1_wide_2x8192x32", |
| "attrs": { "axes": [1], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 8192, 32], |
| "data": { "kind": "fillFloat32", "sinStep": 0.17, "cosStep": 0.07, "scale": 0.2 } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 32], "tolerance": 0.001 } } |
| }, |
| { |
| "name": "f16_axis_split_wide_2x8192x32", |
| "attrs": { "axes": [1], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [2, 8192, 32], |
| "data": { "kind": "fillFloat32", "sinStep": 0.17, "cosStep": 0.07, "scale": 0.2 } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float16", "shape": [2, 32], "tolerance": 0.05, "relTolerance": 0.01 } } |
| }, |
| { |
| "name": "f16_rank3_axis1_serial", |
| "attrs": { "axes": [1], "keepdims": 0 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [2, 3, 4], |
| "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/rank3_axis1_middle_no_keepdims_input_x" } } |
| } |
| }, |
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|
|
