| { |
| "fixtureArrays": { |
| "onnx_backend_alpha2_rank4_positive_input_x": [0.8439682722091675, 0.5665143728256226, 0.058367349207401276, 0.029163669794797897, 0.12964272499084473, 0.5060197114944458, 0.7953830361366272, 0.9411345720291138, 0.9546573162078857, 0.17730942368507385, 0.46192094683647156, 0.264804482460022, 0.6746842265129089, 0.01665256917476654, 0.6247307658195496, 0.9240844249725342, 0.9722340703010559, 0.1196569874882698, 0.41356155276298523, 0.9129372835159302, 0.5933007597923279, 0.8192993402481079, 0.7862604260444641, 0.11799798905849457, 0.692484438419342, 0.5411941409111023, 0.07513222843408585] |
| }, |
| "cases": [ |
| { |
| "name": "f32_values", |
| "attrs": { "alpha": 0.75 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [6], |
| "data": { "kind": "values", "values": [-3.0, -1.0, -0.25, 0.0, 0.5, 2.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [6], "tolerance": 0.00001 } } |
| }, |
| { |
| "name": "f32_non_finite_and_saturation_edges", |
| "attrs": { "alpha": 0.75 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [7], |
| "data": { "kind": "values", "values": ["-Infinity", -1000.0, -2.0, 0.0, 0.0, "Infinity", "NaN"] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [7], "tolerance": 0.00001, "allowNaN": true } } |
| }, |
| { |
| "name": "f32_negative_subnormal_expm1_tail_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 (f32 and f16); the kernel cannot preserve denormal inputs/outputs bit-exactly." |
| }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/activation/activation_op_test.cc", |
| "test": "ActivationOpTest.Celu", |
| "notes": "For tiny negative inputs, alpha*(exp(x/alpha)-1) rounds to zero; returning the original subnormal is incorrect." |
| }, |
| "attrs": { "alpha": 0.75 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [4], |
| "data": { "kind": "values", "values": [-1e-39, -1e-40, 1e-40, 1e-39] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [4], "tolerance": 1e-43 } } |
| }, |
| { |
| "name": "f32_negative_subnormal_expm1_tail_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 (f32 and f16); the kernel cannot preserve denormal inputs/outputs bit-exactly." |
| }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/activation/activation_op_test.cc", |
| "test": "ActivationOpTest.Celu", |
| "notes": "On an unaligned scalar path, tiny negative inputs round the expm1 branch to zero while positive subnormals pass through." |
| }, |
| "attrs": { "alpha": 0.75 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [3], "data": { "kind": "values", "values": [-1e-40, 0.0, 1e-40] } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3], "tolerance": 1e-43 } } |
| }, |
| { |
| "name": "f32_near_zero_negative_expm1_cancellation", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/activation/activation_op_test.cc", |
| "test": "ActivationOpTest.Celu", |
| "notes": "Valid normal-range CELU cancellation edge: alpha * (exp(x / alpha) - 1) should preserve small negative values near zero." |
| }, |
| "attrs": { "alpha": 0.75 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [4], |
| "data": { "kind": "values", "values": [-1e-7, -5e-7, -0.000001, -0.00001] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [4], "tolerance": 2e-8 } } |
| }, |
| { |
| "name": "f32_near_zero_negative_expm1_cancellation_scalar", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/activation/activation_op_test.cc", |
| "test": "ActivationOpTest.Celu", |
| "notes": "Unaligned scalar-path inputs exercise cancellation near zero in the normal range." |
| }, |
| "attrs": { "alpha": 0.75 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [3], "data": { "kind": "values", "values": [-1e-7, -5e-7, -0.000001] } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3], "tolerance": 2e-8 } } |
| }, |
| { |
| "name": "f32_custom_alpha_wider_range", |
| "attrs": { "alpha": 1.5 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [7], |
| "data": { "kind": "values", "values": [-8.0, -2.0, -0.5, 0.0, 0.0, 0.5, 8.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [7], "tolerance": 0.00001 } } |
| }, |
| { |
| "name": "ort_negative_alpha_extreme_values", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/activation/activation_op_test.cc", |
| "test": "ActivationOpTest.Celu" |
| }, |
| "attrs": { "alpha": -0.5 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [14], |
| "data": { |
| "kind": "values", |
| "values": [-1.0, 0.0, 1.0, 100.0, -100.0, 1000.0, -1000.0, 1.17549435e-38, 1.17549435e-39, -1.17549435e-39, 3.4028234663852886e+38, -3.4028234663852886e+38, "Infinity", "-Infinity"] |
| } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [14], "tolerance": 0.00001 } } |
| }, |
| { |
| "name": "onnx_backend_alpha2_rank4_positive", |
| "provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_celu", "test": "test_celu" }, |
| "attrs": { "alpha": 2 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 3, 3, 1], |
| "data": { |
| "kind": "values", |
| "values": { "$ref": "#/fixtureArrays/onnx_backend_alpha2_rank4_positive_input_x" } |
| } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 3, 3, 1], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "onnx_backend_celu", |
| "provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_celu" }, |
| "attrs": { "alpha": 2 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 3, 3, 1], |
| "data": { |
| "kind": "values", |
| "values": { "$ref": "#/fixtureArrays/onnx_backend_alpha2_rank4_positive_input_x" } |
| } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 3, 3, 1], "tolerance": 0.00001 } } |
| }, |
| { |
| "name": "vec4_f32_lanes", |
| "attrs": { "alpha": 1.5 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [8], |
| "data": { "kind": "values", "values": [-4.0, -2.0, -1.0, -0.5, 0.0, 0.5, 1.0, 3.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [8], "tolerance": 0.00001 } } |
| }, |
| { |
| "name": "empty_input_zero_dim", |
| "attrs": { "alpha": 0.75 }, |
| "inputs": { "x": { "dtype": "float32", "shape": [0], "data": { "kind": "values", "values": [] } } }, |
| "outputs": { "y": { "dtype": "float32", "shape": [0], "tolerance": 0 } } |
| }, |
| { |
| "name": "expm1_safe_maclaurin_boundary_vec4", |
| "attrs": { "alpha": 0.75 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [8], |
| "data": { "kind": "values", "values": [-0.094, -0.0938, -0.09375, -0.0937, 0.0, 0.0937, 0.09375, 0.094] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [8], "tolerance": 0.00001 } } |
| }, |
| { |
| "name": "negative_alpha_positive_input_passthrough", |
| "attrs": { "alpha": -0.5 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [8], |
| "data": { "kind": "values", "values": [0.0, 0.0, 0.25, 0.5, 1.0, 2.0, 4.0, 8.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [8], "tolerance": 0.00001 } } |
| }, |
| { |
| "name": "alpha_one_identity_at_boundary_vec4", |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [8], |
| "data": { "kind": "values", "values": [-1.0, -0.001, 0.0, 0.0, 0.001, 1.0, 2.0, 4.0] } |
| } |
| }, |
| "outputs": { |
| "y": { |
| "dtype": "float32", |
| "shape": [8], |
| "data": { |
| "kind": "values", |
| "values": [-0.6321205588285578, -0.0009995001665833, 0.0, 0.0, 0.001, 1.0, 2.0, 4.0] |
| }, |
| "tolerance": 0.00001 |
| } |
| } |
| }, |
| { |
| "name": "onnx28_f16_vec4", |
| "provenance": { |
| "source": "ONNX Operators.md Celu-28", |
| "notes": "Float16 CELU covers negative exponential, signed-zero boundary and positive pass-through values." |
| }, |
| "attrs": { "alpha": 0.75 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [8], |
| "data": { "kind": "values", "values": [-8.0, -2.0, -0.5, -0.01, 0.0, 0.5, 2.0, 8.0] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float16", "shape": [8], "tolerance": 0.002 } } |
| }, |
| { |
| "name": "onnx28_f16_scalar_tail", |
| "provenance": { |
| "source": "ONNX Operators.md Celu-28", |
| "notes": "A non-multiple-of-four element count exercises float16 CELU on the scalar tail as well as the vec4 bulk." |
| }, |
| "attrs": { "alpha": 1.25 }, |
| "inputs": { |
| "x": { "dtype": "float16", "shape": [3], "data": { "kind": "values", "values": [-1.5, -0.125, 3.0] } } |
| }, |
| "outputs": { "y": { "dtype": "float16", "shape": [3], "tolerance": 0.002 } } |
| } |
| ] |
| } |
|
|
