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"fixtureArrays": {
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},
"cases": [
{
"name": "f32_values",
"attrs": { "alpha": 0.5 },
"inputs": {
"x": {
"dtype": "float32",
"shape": [6],
"data": { "kind": "values", "values": [-3.0, -1.0, 0.0, 0.5, 1.0, 3.0] }
}
},
"outputs": { "y": { "dtype": "float32", "shape": [6], "tolerance": 0.000001 } }
},
{
"name": "f32_non_finite_and_saturation_edges",
"attrs": { "alpha": 0.5 },
"inputs": {
"x": {
"dtype": "float32",
"shape": [7],
"data": { "kind": "values", "values": ["-Infinity", -1000.0, 0.0, 0.0, 1000.0, "Infinity", "NaN"] }
}
},
"outputs": { "y": { "dtype": "float32", "shape": [7], "tolerance": 0.000001, "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.Elu",
"notes": "For tiny negative inputs, alpha*(exp(x)-1) rounds to zero; returning the original subnormal is incorrect."
},
"attrs": { "alpha": 0.5 },
"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_near_zero_negative_expm1_cancellation",
"provenance": {
"source": "onnxruntime/test/providers/cpu/activation/activation_op_test.cc",
"test": "ActivationOpTest.Elu",
"notes": "Valid normal-range ELU cancellation edge: exp(x) - 1 must preserve small negative values near zero, not round them to a coarser f32 exp step."
},
"attrs": { "alpha": 0.1 },
"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": 3e-9 } }
},
{
"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.Elu",
"notes": "On an unaligned scalar path, tiny negative inputs round the expm1 branch to zero while positive subnormals pass through."
},
"attrs": { "alpha": 0.5 },
"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_scalar",
"provenance": {
"source": "onnxruntime/test/providers/cpu/activation/activation_op_test.cc",
"test": "ActivationOpTest.Elu",
"notes": "Unaligned scalar-path inputs exercise ELU cancellation near zero in the normal range."
},
"attrs": { "alpha": 0.1 },
"inputs": {
"x": { "dtype": "float32", "shape": [3], "data": { "kind": "values", "values": [-1e-7, -5e-7, -0.000001] } }
},
"outputs": { "y": { "dtype": "float32", "shape": [3], "tolerance": 3e-9 } }
},
{
"name": "f16_values",
"attrs": { "alpha": 1.25 },
"inputs": {
"x": {
"dtype": "float16",
"shape": [7],
"data": { "kind": "values", "values": [-8.0, -2.0, -0.25, 0.0, 0.25, 2.0, 8.0] }
}
},
"outputs": { "y": { "dtype": "float16", "shape": [7], "tolerance": 0.001 } }
},
{
"name": "ort_alpha_0_1_activation_extremes",
"provenance": {
"source": "onnxruntime/test/providers/cpu/activation/activation_op_test.cc",
"test": "ActivationOpTest.Elu",
"notes": "ORT shared activation vector with alpha set to 0.1."
},
"attrs": { "alpha": 0.1 },
"inputs": {
"x": {
"dtype": "float32",
"shape": [13],
"data": {
"kind": "values",
"values": [-1.0, 0.0, 1.0, 100.0, -100.0, 1000.0, -1000.0, 1.1754943508222875e-38, 1.1754943508222876e-39, -1.1754943508222876e-39, 3.4028234663852886e+38, -3.4028234663852886e+38, "Infinity"]
}
}
},
"outputs": { "y": { "dtype": "float32", "shape": [13], "tolerance": 0.000001 } }
},
{
"name": "onnx_backend_alpha2_example",
"provenance": {
"source": "cmake/external/onnx/onnx/backend/test/data/node/test_elu_example",
"test": "test_elu_example"
},
"attrs": { "alpha": 2 },
"inputs": { "x": { "dtype": "float32", "shape": [3], "data": { "kind": "values", "values": [-1.0, 0.0, 1.0] } } },
"outputs": { "y": { "dtype": "float32", "shape": [3], "tolerance": 0.000001 } }
},
{
"name": "onnx_backend_elu",
"provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_elu" },
"attrs": { "alpha": 2 },
"inputs": {
"x": {
"dtype": "float32",
"shape": [3, 4, 5],
"data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_input_x" } }
}
},
"outputs": { "y": { "dtype": "float32", "shape": [3, 4, 5], "tolerance": 0.00001 } }
},
{
"name": "onnx_backend_default_alpha",
"provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_elu_default" },
"inputs": {
"x": {
"dtype": "float32",
"shape": [3, 4, 5],
"data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_input_x" } }
}
},
"outputs": { "y": { "dtype": "float32", "shape": [3, 4, 5], "tolerance": 0.00001 } }
},
{
"name": "vec4_f16_lanes",
"inputs": {
"x": {
"dtype": "float16",
"shape": [16],
"data": {
"kind": "values",
"values": [-6.0, -4.0, -3.0, -2.0, -1.5, -1.0, -0.5, -0.25, 0.0, 0.25, 0.5, 1.0, 1.5, 2.0, 4.0, 6.0]
}
}
},
"outputs": { "y": { "dtype": "float16", "shape": [16], "tolerance": 0.001, "relTolerance": 0.002 } }
},
{
"name": "empty_input_zero_dim",
"attrs": { "alpha": 0.5 },
"inputs": { "x": { "dtype": "float32", "shape": [0], "data": { "kind": "values", "values": [] } } },
"outputs": { "y": { "dtype": "float32", "shape": [0], "tolerance": 0 } }
}
]
}
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