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"op": "ai.onnx.LayerNormalization",
"fixtureArrays": {
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},
"cases": [
{
"name": "subgroup_vec4_stats_no_bias_2x512",
"attrs": { "epsilon": 0.00001, "axis": -1 },
"inputs": {
"x": {
"dtype": "float32",
"shape": [2, 512],
"data": { "kind": "fillFloat32", "sinStep": 0.13, "cosStep": 0.21 }
},
"scale": {
"dtype": "float32",
"shape": [512],
"data": { "kind": "fillFloat32", "sinStep": 0.29, "cosStep": 0.11, "scale": 0.5 }
}
},
"outputs": {
"y": { "dtype": "float32", "shape": [2, 512], "tolerance": 0.000002 },
"mean": { "dtype": "float32", "shape": [2, 1], "tolerance": 0.000001 },
"invStdDev": { "dtype": "float32", "shape": [2, 1], "tolerance": 0.00001 }
}
},
{
"name": "subgroup_vec4_bias_2x512",
"attrs": { "epsilon": 0.00001, "axis": -1 },
"inputs": {
"x": {
"dtype": "float32",
"shape": [2, 512],
"data": { "kind": "fillFloat32", "sinStep": 0.17, "cosStep": 0.23 }
},
"scale": {
"dtype": "float32",
"shape": [512],
"data": { "kind": "fillFloat32", "sinStep": 0.31, "cosStep": 0.07, "scale": 0.4 }
},
"b": {
"dtype": "float32",
"shape": [512],
"data": { "kind": "fillFloat32", "sinStep": 0.05, "cosStep": 0.19, "scale": 0.25 }
}
},
"outputs": { "y": { "dtype": "float32", "shape": [2, 512], "tolerance": 0.000002 } }
},
{
"name": "subgroup_vec4_f16_4x32",
"attrs": { "epsilon": 0.00001, "axis": -1 },
"inputs": {
"x": {
"dtype": "float16",
"shape": [4, 32],
"data": { "kind": "fillFloat32", "sinStep": 0.11, "cosStep": 0.27 }
},
"scale": {
"dtype": "float16",
"shape": [32],
"data": { "kind": "fillFloat32", "sinStep": 0.21, "cosStep": 0.13, "scale": 0.5 }
}
},
"outputs": { "y": { "dtype": "float16", "shape": [4, 32], "tolerance": 0.005 } }
},
{
"name": "subgroup_vec4_f16_stats_4x32",
"attrs": { "epsilon": 0.00001, "axis": -1 },
"inputs": {
"x": {
"dtype": "float16",
"shape": [4, 32],
"data": { "kind": "fillFloat32", "sinStep": 0.09, "cosStep": 0.19 }
},
"scale": {
"dtype": "float16",
"shape": [32],
"data": { "kind": "fillFloat32", "sinStep": 0.23, "cosStep": 0.17, "scale": 0.45 }
}
},
"outputs": {
"y": { "dtype": "float16", "shape": [4, 32], "tolerance": 0.006 },
"mean": { "dtype": "float32", "shape": [4, 1], "tolerance": 0.002 },
"invStdDev": { "dtype": "float32", "shape": [4, 1], "tolerance": 0.02 }
}
},
{
"name": "subgroup_vec4_f16_bias_4x32",
"attrs": { "epsilon": 0.00001, "axis": -1 },
"inputs": {
"x": {
"dtype": "float16",
"shape": [4, 32],
"data": { "kind": "fillFloat32", "sinStep": 0.15, "cosStep": 0.25 }
},
"scale": {
"dtype": "float16",
"shape": [32],
"data": { "kind": "fillFloat32", "sinStep": 0.27, "cosStep": 0.09, "scale": 0.45 }
},
"b": {
"dtype": "float16",
"shape": [32],
"data": { "kind": "fillFloat32", "sinStep": 0.07, "cosStep": 0.21, "scale": 0.2 }
}
},
"outputs": { "y": { "dtype": "float16", "shape": [4, 32], "tolerance": 0.006 } }
},
{
"name": "subgroup_vec4_f16_bias_stats_4x32",
"attrs": { "epsilon": 0.00001, "axis": -1 },
"inputs": {
"x": {
"dtype": "float16",
"shape": [4, 32],
"data": { "kind": "fillFloat32", "sinStep": 0.12, "cosStep": 0.29 }
},
"scale": {
"dtype": "float16",
"shape": [32],
"data": { "kind": "fillFloat32", "sinStep": 0.25, "cosStep": 0.11, "scale": 0.4 }
},
"b": {
"dtype": "float16",
"shape": [32],
"data": { "kind": "fillFloat32", "sinStep": 0.05, "cosStep": 0.17, "scale": 0.25 }
}
},
"outputs": {
"y": { "dtype": "float16", "shape": [4, 32], "tolerance": 0.006 },
"mean": { "dtype": "float32", "shape": [4, 1], "tolerance": 0.002 },
"invStdDev": { "dtype": "float32", "shape": [4, 1], "tolerance": 0.02 }
}
},
{
"name": "f32_subnormal_scale_preserves_tiny_outputs_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; the subnormal per-element scale collapses so tiny normalized outputs cannot be preserved."
},
"provenance": {
"source": "onnxruntime/test/contrib_ops/layer_norm_op_test.cc",
"test": "LayerNormalization",
"notes": "A valid subnormal scale should produce finite subnormal normalized outputs rather than being flushed to zero."
},
"attrs": { "epsilon": 0.00001, "axis": -1 },
"inputs": {
"x": { "dtype": "float32", "shape": [1, 4], "data": { "kind": "values", "values": [-1.0, 0.0, 1.0, 2.0] } },
"scale": {
"dtype": "float32",
"shape": [4],
"data": { "kind": "values", "values": [1e-40, 2e-40, -3e-40, 4e-40] }
}
},
"outputs": { "y": { "dtype": "float32", "shape": [1, 4], "tolerance": 1e-44 } }
},
{
"name": "f32_subnormal_scale_preserves_tiny_outputs_odd_hidden_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; the subnormal per-element scale collapses so tiny normalized outputs cannot be preserved (odd hidden size)."
},
"provenance": {
"source": "onnxruntime/test/contrib_ops/layer_norm_op_test.cc",
"test": "LayerNormalization",
"notes": "Odd hidden-size companion for subnormal scale values; this exercises the non-vec4 last-axis path."
},
"attrs": { "epsilon": 0.00001, "axis": -1 },
"inputs": {
"x": { "dtype": "float32", "shape": [1, 3], "data": { "kind": "values", "values": [-1.0, 0.0, 2.0] } },
"scale": { "dtype": "float32", "shape": [3], "data": { "kind": "values", "values": [1e-40, -2e-40, 3e-40] } }
},
"outputs": { "y": { "dtype": "float32", "shape": [1, 3], "tolerance": 1e-44 } }
},
{
"name": "last_axis_y_only",
"attrs": { "epsilon": 0.00001, "axis": -1 },
"inputs": {
"x": {
"dtype": "float32",
"shape": [3, 8],
"data": { "kind": "fillFloat32", "sinStep": 0.17, "cosStep": 0.29 }
},
"scale": {
"dtype": "float32",
"shape": [8],
"data": { "kind": "fillFloat32", "sinStep": 0.31, "cosStep": 0.07, "scale": 0.4 }
}
},
"outputs": { "y": { "dtype": "float32", "shape": [3, 8], "tolerance": 0.000001 } }
},
{
"name": "last_axis_bias_and_stats",
"attrs": { "epsilon": 0.00001, "axis": -1 },
"inputs": {
"x": {
"dtype": "float32",
"shape": [2, 3, 7],
"data": { "kind": "fillFloat32", "sinStep": 0.11, "cosStep": 0.23 }
},
"scale": {
"dtype": "float32",
"shape": [7],
"data": { "kind": "fillFloat32", "sinStep": 0.19, "cosStep": 0.13, "scale": 0.35 }
},
"b": {
"dtype": "float32",
"shape": [7],
"data": { "kind": "fillFloat32", "sinStep": 0.07, "cosStep": 0.17, "scale": 0.2 }
}
},
"outputs": {
"y": { "dtype": "float32", "shape": [2, 3, 7], "tolerance": 0.00002 },
"mean": { "dtype": "float32", "shape": [2, 3, 1], "tolerance": 0.000001 },
"invStdDev": { "dtype": "float32", "shape": [2, 3, 1], "tolerance": 0.001 }
}
},
{
"name": "f32_tiny_variance_epsilon_zero_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; the subnormal variance collapses to zero so inverseSqrt produces Infinity instead of a finite large InvStdDev."
},
"provenance": {
"source": "onnxruntime/test/contrib_ops/layer_norm_op_test.cc",
"test": "LayerNormTest.LayerNorm17_opset",
"notes": "Valid epsilon=0 edge: normal inputs produce subnormal variance but finite order-one normalized outputs and finite large InvStdDev."
},
"attrs": { "epsilon": 0, "axis": -1 },
"inputs": {
"x": {
"dtype": "float32",
"shape": [2, 2],
"data": { "kind": "values", "values": [1e-20, -1e-20, 2e-20, -2e-20] }
},
"scale": { "dtype": "float32", "shape": [2], "data": { "kind": "values", "values": [1.0, 1.0] } },
"b": { "dtype": "float32", "shape": [2], "data": { "kind": "values", "values": [0.0, 0.0] } }
},
"outputs": {
"y": { "dtype": "float32", "shape": [2, 2], "tolerance": 0.00001 },
"mean": { "dtype": "float32", "shape": [2, 1], "tolerance": 0 },
"invStdDev": { "dtype": "float32", "shape": [2, 1], "tolerance": 1000000000000000, "relTolerance": 0.00001 }
}
},
{
"name": "last_axis_mean_only_no_bias",
"provenance": {
"source": "ONNX LayerNormalization-17 optional-output contract",
"notes": "Requests Mean while independently omitting both B and InvStdDev."
},
"attrs": { "epsilon": 0.00001, "axis": -1 },
"inputs": {
"x": {
"dtype": "float32",
"shape": [2, 4],
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"data": { "kind": "fillFloat32", "sinStep": 0.19, "cosStep": 0.07 }
},
"scale": { "dtype": "float32", "shape": [1], "data": { "kind": "constant", "value": 0.5 } },
"b": { "dtype": "float32", "shape": [1], "data": { "kind": "constant", "value": 0.25 } }
},
"outputs": {
"y": { "dtype": "float32", "shape": [2, 4], "tolerance": 0.000002 },
"mean": { "dtype": "float32", "shape": [2, 1], "tolerance": 0.000001 },
"invStdDev": { "dtype": "float32", "shape": [2, 1], "tolerance": 0.00001 }
}
}
]
}
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