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"op": "com.microsoft.QuickGelu",
"cases": [
{
"name": "dispatch_cliff_scalar_over_16M",
"attrs": { "alpha": 1.702 },
"inputs": {
"X": { "dtype": "float32", "shape": [16776961], "data": { "kind": "linspace", "start": -4.0, "end": 4.0 } }
},
"outputs": { "Y": { "dtype": "float32", "shape": [16776961], "tolerance": 0.0001 } }
},
{
"name": "ort_default_alpha_extreme_safe_sigmoid",
"provenance": {
"source": "onnxruntime/test/contrib_ops/activation_op_test.cc",
"test": "ActivationOpTest.QuickGelu",
"notes": "Default alpha path over very large magnitudes; the safe sigmoid should not overflow."
},
"inputs": {
"X": {
"dtype": "float32",
"shape": [1, 9],
"data": { "kind": "values", "values": [-1000.0, -100.0, -10.0, -1.0, 0.0, 1.0, 10.0, 100.0, 1000.0] }
}
},
"outputs": {
"Y": {
"dtype": "float32",
"shape": [1, 9],
"tolerance": 0.000001,
"data": {
"kind": "values",
"values": [0.0, 0.0, -2.980232238769531e-7, -0.15420421957969666, 0.0, 0.845795750617981, 10.0, 100.0, 1000.0]
}
}
}
},
{
"name": "ort_alpha_one_matches_silu_edges",
"provenance": {
"source": "onnxruntime/test/contrib_ops/activation_op_test.cc",
"test": "ActivationOpTest.QuickGelu"
},
"attrs": { "alpha": 1 },
"inputs": {
"X": {
"dtype": "float32",
"shape": [7],
"data": { "kind": "values", "values": [-100.0, -10.0, -1.0, 0.0, 1.0, 10.0, 100.0] }
}
},
"outputs": {
"Y": {
"dtype": "float32",
"shape": [7],
"tolerance": 0.000001,
"data": {
"kind": "values",
"values": [0.0, -0.0004538893699645996, -0.2689414322376251, 0.0, 0.7310585975646973, 9.99954605102539, 100.0]
}
}
}
},
{
"name": "ort_negative_alpha_flips_gate",
"provenance": {
"source": "onnxruntime/test/contrib_ops/activation_op_test.cc",
"test": "ActivationOpTest.QuickGelu"
},
"attrs": { "alpha": -1.702 },
"inputs": {
"X": { "dtype": "float32", "shape": [5], "data": { "kind": "values", "values": [-3.0, -1.0, 0.0, 1.0, 3.0] } }
},
"outputs": {
"Y": {
"dtype": "float32",
"shape": [5],
"tolerance": 0.000001,
"data": {
"kind": "values",
"values": [-2.981928825378418, -0.845795750617981, 0.0, 0.15420421957969666, 0.018071293830871582]
}
}
}
},
{
"name": "ort_negative_alpha_extreme_safe_sigmoid",
"provenance": {
"source": "onnxruntime/test/contrib_ops/activation_op_test.cc",
"test": "ActivationOpTest.QuickGelu",
"notes": "Upstream negative-alpha branch extended over the same large magnitudes as the positive-alpha ORT vector to guard the stable sigmoid reformulation."
},
"attrs": { "alpha": -1.702 },
"inputs": {
"X": {
"dtype": "float32",
"shape": [1, 9],
"data": { "kind": "values", "values": [-1000.0, -100.0, -10.0, -1.0, 0.0, 1.0, 10.0, 100.0, 1000.0] }
}
},
"outputs": {
"Y": {
"dtype": "float32",
"shape": [1, 9],
"tolerance": 0.000001,
"data": {
"kind": "values",
"values": [-1000.0, -100.0, -10.0, -0.845795750617981, 0.0, 0.15420423448085785, 4.0579612914370955e-7, 0.0, 0.0]
}
}
}
},
{
"name": "ort_empty_rank4",
"provenance": {
"source": "onnxruntime/test/contrib_ops/activation_op_test.cc",
"notes": "Empty tensors should preserve shape and produce no values."
},
"inputs": { "X": { "dtype": "float32", "shape": [1, 0, 2, 3], "data": { "kind": "values", "values": [] } } },
"outputs": { "Y": { "dtype": "float32", "shape": [1, 0, 2, 3], "data": { "kind": "values", "values": [] } } }
},
{
"name": "vec4_default_alpha_mixed_magnitudes",
"provenance": {
"source": "onnxruntime/test/contrib_ops/activation_op_test.cc",
"test": "ActivationOpTest.QuickGelu",
"notes": "numel divisible by 4 so the vec4 variant is exercised; default alpha over a spread of signs/magnitudes."
},
"inputs": {
"X": {
"dtype": "float32",
"shape": [2, 4],
"data": { "kind": "values", "values": [-2.0, -0.5, 0.0, 0.5, 2.0, 1.0, -1.0, 4.0] }
}
},
"outputs": {
"Y": {
"dtype": "float32",
"shape": [2, 4],
"tolerance": 0.000001,
"data": {
"kind": "values",
"values": [-0.06434137374162674, -0.14961156249046326, 0.0, 0.35038843750953674, 1.935658574104309, 0.845795750617981, -0.15420423448085785, 3.9955852031707764]
}
}
}
},
{
"name": "alpha_zero_halves_input",
"provenance": {
"source": "onnxruntime/test/contrib_ops/activation_op_test.cc",
"test": "ActivationOpTest.QuickGelu",
"notes": "Additional edge: alpha=0 makes sigmoid(alpha*x)=0.5 for every finite x."
},
"attrs": { "alpha": 0 },
"inputs": {
"X": { "dtype": "float32", "shape": [5], "data": { "kind": "values", "values": [-3.0, -1.0, 0.0, 1.0, 3.0] } }
},
"outputs": {
"Y": {
"dtype": "float32",
"shape": [5],
"tolerance": 0,
"data": { "kind": "values", "values": [-1.5, -0.5, 0.0, 0.5, 1.5] }
}
}
},
{
"name": "alpha_zero_subnormal_half_input_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 (f32 and f16); the kernel cannot preserve denormal inputs/outputs bit-exactly."
},
"provenance": {
"source": "onnxruntime/test/contrib_ops/activation_op_test.cc",
"test": "ActivationOpTest.QuickGelu",
"notes": "With alpha=0, QuickGelu is exactly x/2, so signed subnormal inputs should not flush to zero in the vec4 path."
},
"attrs": { "alpha": 0 },
"inputs": {
"X": {
"dtype": "float32",
"shape": [4],
"data": { "kind": "values", "values": [1e-40, -1e-40, 1e-38, -1e-38] }
}
},
"outputs": {
"Y": {
"dtype": "float32",
"shape": [4],
"tolerance": 2e-45,
"data": {
"kind": "values",
"values": [4.99997305055738e-41, -4.99997305055738e-41, 4.999999675228202e-39, -4.999999675228202e-39]
}
}
}
},
{
"name": "alpha_zero_subnormal_half_input_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/contrib_ops/activation_op_test.cc",
"test": "ActivationOpTest.QuickGelu",
"notes": "Scalar-path companion for alpha=0 exact half-input subnormal behavior."
},
"attrs": { "alpha": 0 },
"inputs": {
"X": { "dtype": "float32", "shape": [3], "data": { "kind": "values", "values": [1e-40, -1e-40, 1e-38] } }
},
"outputs": {
"Y": {
"dtype": "float32",
"shape": [3],
"tolerance": 2e-45,
"data": { "kind": "values", "values": [4.99997305055738e-41, -4.99997305055738e-41, 4.999999675228202e-39] }
}
}
},
{
"name": "f16_values",
"attrs": { "alpha": 1.702 },
"inputs": {
"X": {
"dtype": "float16",
"shape": [8],
"data": { "kind": "values", "values": [-4.0, -2.0, -0.5, 0.0, 0.5, 1.0, 2.0, 4.0] }
}
},
"outputs": { "Y": { "dtype": "float16", "shape": [8], "tolerance": 0.005 } }
},
{
"name": "f16_default_alpha_extreme_stable_sigmoid",
"attrs": { "alpha": 1.702 },
"inputs": {
"X": {
"dtype": "float16",
"shape": [8],
"data": { "kind": "values", "values": [-1000.0, -100.0, -10.0, -1.0, 1.0, 10.0, 100.0, 1000.0] }
}
},
"outputs": { "Y": { "dtype": "float16", "shape": [8], "tolerance": 0.02 } }
}
]
}
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