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"op": "ai.onnx.Less",
"fixtureArrays": {
"onnx_backend_input_a": [1.764052391052246, 0.40015721321105957, 0.978738009929657, 2.2408931255340576, 1.8675580024719238, -0.9772778749465942, 0.9500884413719177, -0.15135720372200012, -0.10321885347366333, 0.4105985164642334, 0.14404356479644775, 1.4542734622955322, 0.7610377073287964, 0.12167501449584961, 0.44386324286460876, 0.3336743414402008, 1.4940791130065918, -0.2051582634449005, 0.3130677044391632, -0.8540957570075989, -2.5529897212982178, 0.653618574142456, 0.8644362092018127, -0.7421650290489197, 2.269754648208618, -1.4543657302856445, 0.04575851559638977, -0.18718385696411133, 1.5327792167663574, 1.4693588018417358, 0.154947429895401, 0.37816253304481506, -0.8877857327461243, -1.980796456336975, -0.34791216254234314, 0.15634897351264954, 1.2302906513214111, 1.202379822731018, -0.38732680678367615, -0.302302747964859, -1.0485529899597168, -1.420017957687378, -1.7062702178955078, 1.950775384902954, -0.5096521973609924, -0.4380742907524109, -1.2527953386306763, 0.7774903774261475, -1.6138978004455566, -0.21274028718471527, -0.8954665660858154, 0.38690251111984253, -0.5108051300048828, -1.18063223361969, -0.02818222902715206, 0.4283318817615509, 0.06651721894741058, 0.30247190594673157, -0.6343221068382263, -0.3627411723136902],
"broadcast_vec4_lhs_splat_lower_rank_input_b": [9, 10, 11, 10, 19, 20, 21, 20, 29, 30, 31, 30, 30, 20, 10, 0, 10, 20, 30, 40, 31, 29, 30, 10]
},
"cases": [
{
"name": "f32_negative_subnormal_less_than_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: Metal flushes float32 subnormals to zero, so a subnormal compares equal to 0 on GPU; cannot reproduce the strict-inequality result."
},
"provenance": {
"source": "onnxruntime/test/providers/cpu/math/element_wise_ops_test.cc",
"test": "MathOpTest.Less",
"notes": "A negative subnormal is strictly less than zero; flushing it to zero flips the predicate."
},
"inputs": {
"a": { "dtype": "float32", "shape": [4], "data": { "kind": "values", "values": [-1e-39, -1e-40, 0.0, 1e-40] } },
"b": { "dtype": "float32", "shape": [4], "data": { "kind": "constant", "value": 0.0 } }
},
"outputs": { "c": { "dtype": "bool", "shape": [4], "tolerance": 0 } }
},
{
"name": "f32_negative_subnormal_less_than_zero_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: Metal flushes float32 subnormals to zero, so a subnormal compares equal to 0 on GPU; cannot reproduce the strict-inequality result."
},
"provenance": {
"source": "onnxruntime/test/providers/cpu/math/element_wise_ops_test.cc",
"test": "MathOpTest.Less",
"notes": "Scalar-path companion: negative subnormals are strictly less than zero and must keep mask lanes true."
},
"inputs": {
"a": { "dtype": "float32", "shape": [3], "data": { "kind": "values", "values": [-1e-40, 0.0, 1e-40] } },
"b": { "dtype": "float32", "shape": [3], "data": { "kind": "constant", "value": 0.0 } }
},
"outputs": { "c": { "dtype": "bool", "shape": [3], "tolerance": 0 } }
},
{
"name": "broadcast",
"inputs": {
"a": {
"dtype": "float32",
"shape": [2, 3],
"data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0] }
},
"b": { "dtype": "float32", "shape": [3], "data": { "kind": "values", "values": [2.0, 2.0, 5.0] } }
},
"outputs": { "c": { "dtype": "bool", "shape": [2, 3] } }
},
{
"name": "ort_int16_scalar_rhs",
"provenance": {
"source": "onnxruntime/test/providers/cpu/math/element_wise_ops_test.cc",
"test": "MathOpTest.Less_int16_Scalar1"
},
"inputs": {
"a": { "dtype": "int16", "shape": [4], "data": { "kind": "values", "values": [1, 0, 2, -1] } },
"b": { "dtype": "int16", "shape": [1], "data": { "kind": "values", "values": [1] } }
},
"outputs": { "c": { "dtype": "bool", "shape": [4], "tolerance": 0 } }
},
{
"name": "rank0_scalar_scalar_output",
"inputs": {
"a": { "dtype": "float32", "shape": [], "data": { "kind": "values", "values": [-1.0] } },
"b": { "dtype": "float32", "shape": [], "data": { "kind": "values", "values": [0.0] } }
},
"outputs": { "c": { "dtype": "bool", "shape": [], "tolerance": 0 } }
},
{
"name": "int32_exact_above_float24",
"inputs": {
"a": {
"dtype": "int32",
"shape": [4],
"data": { "kind": "values", "values": [16777216, 16777217, -16777217, -16777216] }
},
"b": {
"dtype": "int32",
"shape": [4],
"data": { "kind": "values", "values": [16777217, 16777216, -16777216, -16777217] }
}
},
"outputs": { "c": { "dtype": "bool", "shape": [4], "tolerance": 0 } }
},
{
"name": "ort_int8_scalar_rhs",
"provenance": {
"source": "onnxruntime/test/providers/cpu/math/element_wise_ops_test.cc",
"test": "MathOpTest.Less_int8_Scalar1"
},
"inputs": {
"a": { "dtype": "int8", "shape": [4], "data": { "kind": "values", "values": [1, 0, 2, -1] } },
"b": { "dtype": "int8", "shape": [1], "data": { "kind": "values", "values": [1] } }
},
"outputs": { "c": { "dtype": "bool", "shape": [4], "tolerance": 0 } }
},
{
"name": "ort_float_vector",
"provenance": {
"source": "onnxruntime/test/providers/cpu/math/element_wise_ops_test.cc",
"test": "MathOpTest.Less"
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"inputs": {
"a": { "dtype": "float32", "shape": [4], "data": { "kind": "values", "values": [1.0, 0.0, -1.0, -1.0] } },
"b": { "dtype": "float32", "shape": [4], "data": { "kind": "values", "values": [1.0, 1.0, 2.0, -1.0] } }
},
"outputs": { "c": { "dtype": "bool", "shape": [4], "tolerance": 0 } }
},
{
"name": "ort_float_scalar_lhs",
"provenance": {
"source": "onnxruntime/test/providers/cpu/math/element_wise_ops_test.cc",
"test": "MathOpTest.Less_Scalar0"
},
"inputs": {
"a": { "dtype": "float32", "shape": [1], "data": { "kind": "values", "values": [1.0] } },
"b": { "dtype": "float32", "shape": [4], "data": { "kind": "values", "values": [1.0, 1.5, 2.0, -1.0] } }
},
"outputs": { "c": { "dtype": "bool", "shape": [4], "tolerance": 0 } }
},
{
"name": "ort_float_scalar_rhs",
"provenance": {
"source": "onnxruntime/test/providers/cpu/math/element_wise_ops_test.cc",
"test": "MathOpTest.Less_Scalar1"
},
"inputs": {
"a": { "dtype": "float32", "shape": [4], "data": { "kind": "values", "values": [1.0, 0.5, 2.0, -1.0] } },
"b": { "dtype": "float32", "shape": [1], "data": { "kind": "values", "values": [1.0] } }
},
"outputs": { "c": { "dtype": "bool", "shape": [4], "tolerance": 0 } }
},
{
"name": "ort_uint8_scalar_rhs",
"provenance": {
"source": "onnxruntime/test/providers/cpu/math/element_wise_ops_test.cc",
"test": "MathOpTest.Less_uint8_Scalar1"
},
"inputs": {
"a": { "dtype": "uint8", "shape": [4], "data": { "kind": "values", "values": [1, 0, 2, 3] } },
"b": { "dtype": "uint8", "shape": [1], "data": { "kind": "values", "values": [2] } }
},
"outputs": { "c": { "dtype": "bool", "shape": [4], "tolerance": 0 } }
},
{
"name": "ort_uint32_scalar_rhs",
"provenance": {
"source": "onnxruntime/test/providers/cpu/math/element_wise_ops_test.cc",
"test": "MathOpTest.Less_uint32_Scalar1"
},
"inputs": {
"a": { "dtype": "uint32", "shape": [4], "data": { "kind": "values", "values": [1, 0, 2, 3] } },
"b": { "dtype": "uint32", "shape": [1], "data": { "kind": "values", "values": [2] } }
},
"outputs": { "c": { "dtype": "bool", "shape": [4], "tolerance": 0 } }
},
{
"name": "nan_comparisons_are_false",
"inputs": {
"a": {
"dtype": "float32",
"shape": [4],
"data": { "kind": "values", "values": ["NaN", 1.0, "Infinity", "-Infinity"] }
},
"b": {
"dtype": "float32",
"shape": [4],
"data": { "kind": "values", "values": [0.0, "NaN", "Infinity", "-Infinity"] }
}
},
"outputs": { "c": { "dtype": "bool", "shape": [4], "tolerance": 0 } }
},
{
"name": "ort_int32_broadcast_ab",
"provenance": {
"source": "onnxruntime/test/providers/cpu/math/element_wise_ops_test.cc",
"test": "MathOpTest.Less_broadcastAB"
},
"inputs": {
"a": {
"dtype": "int32",
"shape": [4, 2],
"data": { "kind": "values", "values": [10, 11, 12, 13, 14, 15, 16, 17] }
},
"b": { "dtype": "int32", "shape": [2], "data": { "kind": "values", "values": [15, 7] } }
},
"outputs": { "c": { "dtype": "bool", "shape": [4, 2], "tolerance": 0 } }
},
{
"name": "ort_int32_broadcast_ba",
"provenance": {
"source": "onnxruntime/test/providers/cpu/math/element_wise_ops_test.cc",
"test": "MathOpTest.Less_broadcastBA"
},
"inputs": {
"a": { "dtype": "int32", "shape": [2], "data": { "kind": "values", "values": [15, 7] } },
"b": {
"dtype": "int32",
"shape": [4, 2],
"data": { "kind": "values", "values": [10, 11, 12, 13, 14, 15, 16, 17] }
}
},
"outputs": { "c": { "dtype": "bool", "shape": [4, 2], "tolerance": 0 } }
},
{
"name": "ort_int32_multidirectional_broadcast_ab",
"provenance": {
"source": "onnxruntime/test/providers/cpu/math/element_wise_ops_test.cc",
"test": "MathOpTest.Less_multidirectional_broadcastAB"
},
"inputs": {
"a": { "dtype": "int32", "shape": [4, 1], "data": { "kind": "values", "values": [10, 11, 12, 13] } },
"b": { "dtype": "int32", "shape": [2], "data": { "kind": "values", "values": [15, 7] } }
},
"outputs": { "c": { "dtype": "bool", "shape": [4, 2], "tolerance": 0 } }
},
{
"name": "ort_int32_multidirectional_broadcast_ba",
"provenance": {
"source": "onnxruntime/test/providers/cpu/math/element_wise_ops_test.cc",
"test": "MathOpTest.Less_multidirectional_broadcastBA"
},
"inputs": {
"a": { "dtype": "int32", "shape": [2], "data": { "kind": "values", "values": [15, 7] } },
"b": { "dtype": "int32", "shape": [4, 1], "data": { "kind": "values", "values": [10, 11, 12, 13] } }
},
"outputs": { "c": { "dtype": "bool", "shape": [4, 2], "tolerance": 0 } }
},
{
"name": "onnx_backend_bcast_float32_rank3",
"provenance": {
"source": "cmake/external/onnx/onnx/backend/test/data/node/test_less_bcast",
"test": "test_less_bcast"
},
"inputs": {
"a": {
"dtype": "float32",
"shape": [3, 4, 5],
"data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_input_a" } }
},
"b": {
"dtype": "float32",
"shape": [5],
"data": {
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"values": [-0.6724604368209839, -0.35955315828323364, -0.8131462931632996, -1.7262825965881348, 0.17742614448070526]
}
}
},
"outputs": { "c": { "dtype": "bool", "shape": [3, 4, 5], "tolerance": 0 } }
},
{
"name": "onnx_backend_less",
"provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_less", "test": "test_less" },
"inputs": {
"a": {
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"shape": [3, 4, 5],
"data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/onnx_backend_input_a" } }
},
"b": {
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"data": {
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"values": [-0.6724604368209839, -0.35955315828323364, -0.8131462931632996, -1.7262825965881348, 0.17742614448070526, -0.4017809331417084, -1.630198359489441, 0.46278226375579834, -0.9072983860969543, 0.05194539576768875, 0.7290905714035034, 0.12898291647434235, 1.1394007205963135, -1.234825849533081, 0.4023416340351105, -0.6848101019859314, -0.8707971572875977, -0.5788496732711792, -0.3115525245666504, 0.056165341287851334, -1.1651498079299927, 0.9008265137672424, 0.4656624495983124, -1.5362436771392822, 1.4882521629333496, 1.895889163017273, 1.1787796020507812, -0.1799248307943344, -1.0707526206970215, 1.0544517040252686, -0.4031769335269928, 1.222445011138916, 0.2082749754190445, 0.9766390323638916, 0.3563663959503174, 0.7065731883049011, 0.01050002034753561, 1.7858705520629883, 0.12691208720207214, 0.4019893705844879, 1.8831506967544556, -1.3477590084075928, -1.2704850435256958, 0.969396710395813, -1.1731233596801758, 1.9436211585998535, -0.4136189818382263, -0.747454822063446, 1.922942042350769, 1.4805147647857666, 1.8675589561462402, 0.9060446619987488, -0.8612256646156311, 1.910064935684204, -0.26800337433815, 0.8024563789367676, 0.9472519755363464, -0.15501008927822113, 0.6140793561935425, 0.922206699848175]
}
}
},
"outputs": { "c": { "dtype": "bool", "shape": [3, 4, 5], "tolerance": 0 } }
},
{
"name": "onnx_backend_less_int8",
"provenance": {
"source": "cmake/external/onnx/onnx/backend/test/data/node/test_less_int8",
"test": "test_less_int8"
},
"inputs": {
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"data": {
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"values": [0, -1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, -1, 0, 0, 0, 2, 0, 0, 1, -1, 0, 0, 1, 0, 0, 0, 0, 1, -1, -1, 0, 0, 1, 0, 0, -1, 0, -1, -1, 1, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0]
}
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"values": [0, -1, 0, -2, 0, -1, -1, 0, 0, 1, -1, 0, 0, -1, 0, 0, 0, 0, 2, 1, 0, 0, 1, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, -1, 0, 0, 0, -1, 0, 1, -2, 0, 0]
}
}
},
"outputs": { "c": { "dtype": "bool", "shape": [3, 4, 5], "tolerance": 0 } }
},
{
"name": "onnx_backend_less_uint8",
"provenance": {
"source": "cmake/external/onnx/onnx/backend/test/data/node/test_less_uint8",
"test": "test_less_uint8"
},
"inputs": {
"a": {
"dtype": "uint8",
"shape": [3, 4, 5],
"data": {
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"values": [13, 0, 18, 7, 12, 14, 19, 8, 13, 17, 17, 10, 22, 19, 7, 12, 13, 2, 11, 12, 17, 13, 6, 14, 15, 7, 5, 21, 17, 16, 3, 18, 9, 10, 0, 18, 0, 20, 13, 6, 10, 23, 19, 1, 13, 6, 23, 23, 12, 23, 20, 14, 1, 1, 16, 12, 17, 10, 20, 21]
}
},
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"dtype": "uint8",
"shape": [3, 4, 5],
"data": {
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"values": [18, 21, 10, 19, 0, 5, 21, 5, 4, 18, 23, 11, 20, 12, 20, 10, 16, 2, 12, 2, 23, 0, 7, 6, 6, 16, 18, 9, 3, 0, 10, 2, 18, 18, 20, 13, 1, 12, 0, 9, 22, 7, 19, 21, 1, 21, 3, 19, 21, 4, 2, 5, 16, 11, 18, 4, 4, 1, 23, 9]
}
}
},
"outputs": { "c": { "dtype": "bool", "shape": [3, 4, 5], "tolerance": 0 } }
},
{
"name": "onnx_backend_less_uint32",
"provenance": {
"source": "cmake/external/onnx/onnx/backend/test/data/node/test_less_uint32",
"test": "test_less_uint32"
},
"inputs": {
"a": {
"dtype": "uint32",
"shape": [3, 4, 5],
"data": {
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"values": [19, 2, 12, 9, 19, 8, 5, 20, 21, 11, 1, 11, 15, 12, 15, 12, 21, 18, 13, 12, 9, 21, 6, 4, 16, 8, 5, 15, 5, 5, 17, 0, 16, 16, 0, 10, 12, 0, 7, 22, 19, 5, 4, 19, 4, 5, 12, 17, 19, 12, 6, 7, 20, 16, 0, 23, 15, 10, 3, 3]
}
},
"b": {
"dtype": "uint32",
"shape": [3, 4, 5],
"data": {
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"values": [16, 16, 9, 20, 20, 5, 16, 17, 21, 9, 12, 15, 6, 14, 1, 4, 16, 4, 7, 23, 14, 7, 22, 2, 22, 16, 15, 15, 18, 11, 23, 14, 7, 2, 22, 17, 3, 7, 13, 16, 5, 4, 21, 13, 5, 19, 11, 8, 0, 17, 5, 4, 1, 5, 16, 6, 8, 22, 19, 4]
}
}
},
"outputs": { "c": { "dtype": "bool", "shape": [3, 4, 5], "tolerance": 0 } }
},
{
"name": "empty_input_zero_dim",
"inputs": {
"a": { "dtype": "float32", "shape": [2, 0], "data": { "kind": "values", "values": [] } },
"b": { "dtype": "float32", "shape": [0], "data": { "kind": "values", "values": [] } }
},
"outputs": { "c": { "dtype": "bool", "shape": [2, 0], "tolerance": 0 } }
},
{
"name": "broadcast_vec4_inner4_gpu",
"provenance": {
"source": "synthetic",
"test": "broadcast_vec4 inner-dim %4==0 coverage",
"notes": "Broadcasts A=[2,1,4] and B to C with innermost extent four. Exercises vec4 broadcast indexing and verifies that the grid-stride count is expressed in vec4 groups (numel(C)/4), including bounds-safe iteration across six groups."
},
"inputs": {
"a": {
"dtype": "float32",
"shape": [2, 1, 4],
"data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0] }
},
"b": {
"dtype": "float32",
"shape": [2, 3, 4],
"data": {
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"values": [0.0, 2.0, 4.0, 4.0, 1.0, 1.0, 1.0, 1.0, 2.0, 3.0, 4.0, 5.0, 5.0, 5.0, 5.0, 5.0, 4.0, 7.0, 6.0, 9.0, 9.0, 9.0, 9.0, 9.0]
}
}
},
"outputs": { "c": { "dtype": "bool", "shape": [2, 3, 4], "tolerance": 0 } }
},
{
"name": "f16_same_shape",
"inputs": {
"a": {
"dtype": "float16",
"shape": [8],
"data": { "kind": "values", "values": [1.0, 2.0, 3.0, "NaN", "Infinity", "-Infinity", -2.5, 65504.0] }
},
"b": {
"dtype": "float16",
"shape": [8],
"data": { "kind": "values", "values": [2.0, 2.0, 1.0, 1.0, 1.0, 1.0, -2.5, 65504.0] }
}
},
"outputs": { "c": { "dtype": "bool", "shape": [8] } }
},
{
"name": "f16_scalar_rhs",
"inputs": {
"a": {
"dtype": "float16",
"shape": [8],
"data": { "kind": "values", "values": [-2.0, -1.0, 0.0, 1.0, 2.0, 3.0, "NaN", "Infinity"] }
},
"b": { "dtype": "float16", "shape": [1], "data": { "kind": "values", "values": [1.0] } }
},
"outputs": { "c": { "dtype": "bool", "shape": [8] } }
},
{
"name": "int8_extremes_less",
"inputs": {
"a": { "dtype": "int8", "shape": [6], "data": { "kind": "values", "values": [-128, 127, -128, 127, 0, -1] } },
"b": { "dtype": "int8", "shape": [6], "data": { "kind": "values", "values": [127, -128, -128, 127, -128, 0] } }
},
"outputs": { "c": { "dtype": "bool", "shape": [6], "tolerance": 0 } }
},
{
"name": "broadcast_scalar_path_odd_inner_dim",
"inputs": {
"a": {
"dtype": "int32",
"shape": [4, 5],
"data": { "kind": "values", "values": [1, 3, 5, 7, 9, 2, 4, 6, 8, 10, 10, 8, 6, 4, 2, 9, 7, 5, 3, 1] }
},
"b": { "dtype": "int32", "shape": [5], "data": { "kind": "values", "values": [5, 5, 5, 5, 5] } }
},
"outputs": { "c": { "dtype": "bool", "shape": [4, 5], "tolerance": 0 } }
},
{
"name": "f32_broadcast_odd_inner_dim_4x17",
"provenance": {
"notes": "Compact f32 sibling for the odd-inner broadcast benchmark; preserves the [rows, odd] x [odd] shape family without benchmark-scale rows."
},
"inputs": {
"a": {
"dtype": "float32",
"shape": [4, 17],
"data": { "kind": "fillFloat32", "sinStep": 0.037, "cosStep": 0.019, "scale": 0.5 }
},
"b": {
"dtype": "float32",
"shape": [17],
"data": { "kind": "fillFloat32", "sinStep": 0.011, "cosStep": 0.043, "scale": 0.5 }
}
},
"outputs": { "c": { "dtype": "bool", "shape": [4, 17], "tolerance": 0 } }
},
{
"name": "uint8_extremes_less",
"inputs": {
"a": { "dtype": "uint8", "shape": [4], "data": { "kind": "values", "values": [0, 255, 128, 127] } },
"b": { "dtype": "uint8", "shape": [4], "data": { "kind": "values", "values": [255, 0, 127, 128] } }
},
"outputs": { "c": { "dtype": "bool", "shape": [4], "tolerance": 0 } }
},
{
"name": "rank7_broadcast_scalar_tail",
"inputs": {
"a": {
"dtype": "float32",
"shape": [2, 1, 2, 1, 2, 1, 3],
"data": { "kind": "fillFloat32", "sinStep": 0.11, "cosStep": 0.23 }
},
"b": {
"dtype": "float32",
"shape": [1, 2, 1, 2, 1, 2, 1],
"data": { "kind": "fillFloat32", "sinStep": 0.31, "cosStep": 0.07 }
}
},
"outputs": { "c": { "dtype": "bool", "shape": [2, 2, 2, 2, 2, 2, 3], "tolerance": 0 } }
},
{
"name": "broadcast_vec4_lhs_splat_lower_rank",
"provenance": {
"source": "authored for render coverage",
"test": "compare-broadcast-vec4 lhs splat arm",
"notes": "A is rank 2 against a rank 3 output and its innermost axis is 1, so compare-broadcast-vec4 renders `a_same` false straight from the rank test and takes the a_mode == \"splat\" branch, which reads one A element per vec4 group instead of four contiguous ones. Every other vec4-eligible case has A either the same rank as C (contiguous) or a single element (scalar), so neither the lower-rank A arm nor the A-splat arm had ever rendered. Each row of A holds a different value and B differs at every position, so a wrong a_offset changes the result."
},
"inputs": {
"a": { "dtype": "float32", "shape": [3, 1], "data": { "kind": "values", "values": [10.0, 20.0, 30.0] } },
"b": {
"dtype": "float32",
"shape": [2, 3, 4],
"data": {
"kind": "values",
"values": { "$ref": "#/fixtureArrays/broadcast_vec4_lhs_splat_lower_rank_input_b" }
}
}
},
"outputs": { "c": { "dtype": "bool", "shape": [2, 3, 4], "tolerance": 0 } }
},
{
"name": "broadcast_vec4_rhs_splat_lower_rank",
"provenance": {
"source": "authored for render coverage",
"test": "compare-broadcast-vec4 rhs splat arm",
"notes": "B is rank 2 with innermost axis 1 against a rank-3 output, so each vec4 output group broadcasts one B value while A remains contiguous. This mirrors the corresponding left-hand splat case."
},
"inputs": {
"a": {
"dtype": "float32",
"shape": [2, 3, 4],
"data": {
"kind": "values",
"values": { "$ref": "#/fixtureArrays/broadcast_vec4_lhs_splat_lower_rank_input_b" }
}
},
"b": { "dtype": "float32", "shape": [3, 1], "data": { "kind": "values", "values": [10.0, 20.0, 30.0] } }
},
"outputs": { "c": { "dtype": "bool", "shape": [2, 3, 4], "tolerance": 0 } }
},
{
"name": "broadcast_vec4_true_scalar_lhs",
"provenance": {
"source": "authored for render coverage",
"test": "compare-broadcast-vec4 rank-0 lhs arm",
"notes": "A is a true rank-0 scalar, so `source.aRank >= 1` is false and compare-broadcast-vec4 takes the left-hand scalar arm. C's innermost dimension is 4 and numel is 8, selecting broadcast_vec4 while distinguishing A-scalar from B-scalar indexing."
},
"inputs": {
"a": { "dtype": "float32", "shape": [], "data": { "kind": "values", "values": [20.0] } },
"b": {
"dtype": "float32",
"shape": [2, 4],
"data": { "kind": "values", "values": [10.0, 20.0, 30.0, 20.0, -5.0, 20.0, 25.0, 0.0] }
}
},
"outputs": { "c": { "dtype": "bool", "shape": [2, 4], "tolerance": 0 } }
}
]
}
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