| { |
| "op": "ai.onnx.RMSNormalization", |
| "fixtureArrays": { |
| "f16_scalar_cast_x": [-1.1103515625, 2.982421875, 1.248046875, -1.8544921875], |
| "f16_scalar_cast_scale": [2.015625], |
| "f16_scalar_cast_y": [-1.150390625, 3.091796875, 1.29296875, -1.921875], |
| "onnx_backend_rms_normalization_3d_input_x": [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], |
| "onnx_backend_rms_normalization_input_x": [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, -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], |
| "ort_axis2_vector3_scale_input_x": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29], |
| "ort_f16_axis1_outer_inner_broadcast_scale_input_x": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23] |
| }, |
| "cases": [ |
| { |
| "name": "subgroup_vec4_2x512", |
| "attrs": { "epsilon": 0.000001, "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 } } |
| }, |
| { |
| "name": "f32_default_epsilon_small_magnitude", |
| "attrs": { "axis": -1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 8], |
| "data": { "kind": "fillFloat32", "sinStep": 0.17, "cosStep": 0.23, "scale": 0.001 } |
| }, |
| "scale": { |
| "dtype": "float32", |
| "shape": [8], |
| "data": { "kind": "fillFloat32", "sinStep": 0.31, "cosStep": 0.07, "scale": 0.4 } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 8], "tolerance": 0.000001 } }, |
| "provenance": { |
| "source": "onnx/defs/nn/defs.cc", |
| "test": "RMSNormalization-23 schema", |
| "notes": "Pins the default-epsilon path: no epsilon attribute is passed, so manifest and oracle defaults must both match the ONNX schema default 1e-5. Small-magnitude rows make epsilon dominate the mean-square, so a wrong default (e.g. 1e-6) diverges by >2x." |
| } |
| }, |
| { |
| "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": "last_axis_3x8", |
| "attrs": { "epsilon": 0.000001, "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_rank3", |
| "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 } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3, 7], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "f32_tiny_rms_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 RMS denominator collapses to zero so normalization is non-finite." |
| }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/nn/rms_norm_op_test.cc", |
| "test": "RMSNormalizationOpTest.RMSNorm", |
| "notes": "Valid epsilon=0 edge: the RMS denominator is positive subnormal, so tiny normal inputs normalize to finite order-one values." |
| }, |
| "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] } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 2], "tolerance": 0.00001 } } |
| }, |
| { |
| "name": "f32_subnormal_scale_last_axis_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 in f32; the subnormal affine scale collapses to zero, losing the tiny output (vec4 path)." |
| }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/nn/rms_norm_op_test.cc", |
| "test": "RMSNormalizationOpTest.RMSNorm_Scale", |
| "notes": "Subnormal scale values are valid; with a nonzero RMS denominator they should produce subnormal outputs, not zeros." |
| }, |
| "attrs": { "epsilon": 0, "axis": -1 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [1, 4], "data": { "kind": "values", "values": [-1.0, 1.0, 2.0, -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_last_axis_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 affine scale collapses to zero (odd hidden size)." |
| }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/nn/rms_norm_op_test.cc", |
| "test": "RMSNormalizationOpTest.RMSNorm_Scale", |
| "notes": "Odd hidden-size companion for valid subnormal scale outputs." |
| }, |
| "attrs": { "epsilon": 0, "axis": -1 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [1, 3], "data": { "kind": "values", "values": [-1.0, 1.0, 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": "ort_basic_1x2x3", |
| "attrs": { "epsilon": 0.00001, "axis": -1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [1, 2, 3], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0] } |
| }, |
| "scale": { "dtype": "float32", "shape": [3], "data": { "kind": "values", "values": [1.0, 1.0, 1.0] } } |
| }, |
| "outputs": { |
| "y": { |
| "dtype": "float32", |
| "shape": [1, 2, 3], |
| "tolerance": 0.0001, |
| "data": { "kind": "values", "values": [0.4629, 0.9258, 1.3887, 0.7895, 0.9869, 1.1843] } |
| } |
| }, |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/nn/rms_norm_op_test.cc", |
| "test": "RMSNormalizationOpTest.RMSNorm" |
| } |
| }, |
| { |
| "name": "mixed_x_f32_scale_y_f16", |
| "provenance": { |
| "source": "onnx/defs/nn/defs.cc", |
| "test": "RMSNormalization-23 schema", |
| "notes": "Exercises the standard's independent T and V variables with float32 X and float16 scale/output." |
| }, |
| "attrs": { "epsilon": 0.00001, "axis": -1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [1, 2, 3], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0] } |
| }, |
| "scale": { "dtype": "float16", "shape": [3], "data": { "kind": "values", "values": [0.75, -1.25, 1.5] } } |
| }, |
| "outputs": { "y": { "dtype": "float16", "shape": [1, 2, 3], "tolerance": 0.002 } } |
| }, |
| { |
| "name": "mixed_x_f16_scale_y_f32", |
| "provenance": { |
| "source": "onnx/defs/nn/defs.cc", |
| "test": "RMSNormalization-23 schema", |
| "notes": "Exercises the standard's independent T and V variables with float16 X and float32 scale/output, including the cast-to-T stage boundary before scaling." |
| }, |
| "attrs": { "epsilon": 0.00001, "axis": -1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [1, 2, 3], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0] } |
| }, |
| "scale": { "dtype": "float32", "shape": [3], "data": { "kind": "values", "values": [0.75, -1.25, 1.5] } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [1, 2, 3], "tolerance": 0.00001 } } |
| }, |
| { |
| "name": "zero_rows_noop", |
| "attrs": { "epsilon": 0.000001, "axis": -1 }, |
| "inputs": { |
| "x": { "dtype": "float32", "shape": [0, 4], "data": { "kind": "values", "values": [] } }, |
| "scale": { "dtype": "float32", "shape": [4], "data": { "kind": "values", "values": [1.0, 1.0, 1.0, 1.0] } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [0, 4], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "axis1_rank3_scale_matrix", |
| "attrs": { "epsilon": 0.000001, "axis": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 3, 4], |
| "data": { "kind": "fillFloat32", "sinStep": 0.11, "cosStep": 0.23 } |
| }, |
| "scale": { |
| "dtype": "float32", |
| "shape": [3, 4], |
| "data": { "kind": "fillFloat32", "sinStep": 0.19, "cosStep": 0.13, "scale": 0.35 } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 3, 4], "tolerance": 0.000001 } } |
| }, |
| { |
| "name": "ort_basic_1x2x3_f16", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/nn/rms_norm_op_test.cc", |
| "test": "RMSNormalizationOpTest.RMSNorm_float16" |
| }, |
| "attrs": { "epsilon": 0.00001, "axis": -1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [1, 2, 3], |
| "data": { "kind": "values", "values": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0] } |
| }, |
| "scale": { "dtype": "float16", "shape": [3], "data": { "kind": "values", "values": [1.0, 1.0, 1.0] } } |
| }, |
| "outputs": { |
| "y": { |
| "dtype": "float16", |
| "shape": [1, 2, 3], |
| "tolerance": 0.002, |
| "data": { "kind": "values", "values": [0.4629, 0.9258, 1.3887, 0.7895, 0.9869, 1.1843] } |
| } |
| } |
| }, |
| { |
| "name": "ort_scale_2x2x2_f32", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/nn/rms_norm_op_test.cc", |
| "test": "RMSNormalizationOpTest.RMSNorm_Scale" |
| }, |
| "attrs": { "epsilon": 0.00001, "axis": -1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 2, 2], |
| "data": { |
| "kind": "values", |
| "values": [-10.264, 8.6453, 43.1561, -0.641239, -8.2164, 0.11412, 41.3156, 3.0458] |
| } |
| }, |
| "scale": { "dtype": "float32", "shape": [2], "data": { "kind": "values", "values": [-0.6953, 5.1824] } } |
| }, |
| "outputs": { |
| "y": { |
| "dtype": "float32", |
| "shape": [2, 2, 2], |
| "tolerance": 0.0001, |
| "data": { "kind": "values", "values": [0.7521, 4.7215, -0.9832, -0.1089, 0.9832, 0.1018, -0.9806, 0.5388] } |
| } |
| } |
| }, |
| { |
| "name": "ort_scale_2x2x2_f16", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/nn/rms_norm_op_test.cc", |
| "test": "RMSNormalizationOpTest.RMSNorm_Scale_Float16" |
| }, |
| "attrs": { "epsilon": 0.00001, "axis": -1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float16", |
| "shape": [2, 2, 2], |
| "data": { |
| "kind": "values", |
| "values": [-10.264, 8.6453, 43.1561, -0.641239, -8.2164, 0.11412, 41.3156, 3.0458] |
| } |
| }, |
| "scale": { "dtype": "float16", "shape": [2], "data": { "kind": "values", "values": [-0.6953, 5.1824] } } |
| }, |
| "outputs": { |
| "y": { |
| "dtype": "float16", |
| "shape": [2, 2, 2], |
| "tolerance": 0.01, |
| "data": { "kind": "values", "values": [0.7521, 4.7215, -0.9832, -0.1089, 0.9832, 0.1018, -0.9806, 0.5388] } |
| } |
| } |
| }, |
| { |
| "name": "ort_axis2_vector3_scale", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/nn/rms_norm_op_test.cc", |
| "test": "RMSNormalizationOpTest.RMSNorm_Scale_Vector3_Axis2" |
| }, |
| "attrs": { "epsilon": 0.00001, "axis": 2 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 5, 3], |
| "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/ort_axis2_vector3_scale_input_x" } } |
| }, |
| "scale": { "dtype": "float32", "shape": [3], "data": { "kind": "values", "values": [1.5, 1.5, 1.5] } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 5, 3], "tolerance": 0.0001 } } |
| }, |
| { |
| "name": "ort_axis2_scalar_scale", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/nn/rms_norm_op_test.cc", |
| "test": "RMSNormalizationOpTest.RMSNorm_Scale_Scalar_Axis2" |
| }, |
| "attrs": { "epsilon": 0.00001, "axis": 2 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 5, 3], |
| "data": { "kind": "values", "values": { "$ref": "#/fixtureArrays/ort_axis2_vector3_scale_input_x" } } |
| }, |
| "scale": { "dtype": "float32", "shape": [], "data": { "kind": "values", "values": [1.5] } } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 5, 3], "tolerance": 0.0001 } } |
| }, |
| { |
| "name": "ort_axis2_batch_outer_broadcast_scale", |
| "provenance": { |
| "source": "onnxruntime/test/providers/cpu/nn/rms_norm_op_test.cc", |
| "test": "RMSNormalizationOpTest.RMSNorm_Scale_Bx1x3_Axis2" |
| }, |
| "attrs": { "epsilon": 0.00001, "axis": 2 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [3, 2, 3], |
| "data": { |
| "kind": "values", |
| "values": [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0] |
| } |
| }, |
| "scale": { |
| "dtype": "float32", |
| "shape": [3, 1, 3], |
| "data": { "kind": "values", "values": [1.0, 1.0, 1.0, 1.2, 1.2, 1.2, 1.4, 1.4, 1.4] } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [3, 2, 3], "tolerance": 0.0001 } } |
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| "test": "RMSNormalizationOpTest.RMSNorm_Scale_1xSx1xW_AxisNeg2" |
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| "test": "RMSNormalizationOpTest.RMSNorm_Scale_1xSx1xW_Axis2" |
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| "source": "onnxruntime/test/providers/cpu/nn/rms_norm_op_test.cc", |
| "test": "RMSNormalizationOpTest.RMSNorm_Scale_Float16_OuterInnerBroadcast_Axis1" |
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| "x": { |
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| "test": "RMSNormalizationOpTest.RMSNorm_Scale_1x1x1_Axis2" |
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| "test": "RMSNormalizationOpTest.RMSNorm_Scale_1xSx3_Axis2" |
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| "values": { "$ref": "#/fixtureArrays/ort_f16_axis1_outer_inner_broadcast_scale_input_x" } |
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| "test": "RMSNormalizationOpTest.RMSNorm_Scale_NoBroadcast_BxSx3_Axis2" |
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| "name": "ort_axis1_nchw_channel_scale_1x4x1x1", |
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| "name": "ort_axis3_rank5_scale_1xSx1x1xC", |
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| "name": "ort_f16_axis2_outer_broadcast_scale", |
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| "attrs": { "epsilon": 0.00001, "axis": -1, "stash_type": 10 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [1, 4], |
| "data": { "kind": "values", "values": [8.1716, 0.15772, -0.14759, -2.1252] } |
| }, |
| "scale": { "dtype": "float32", "shape": [], "data": { "kind": "values", "values": [1.234567] } } |
| }, |
| "outputs": { |
| "y": { |
| "dtype": "float32", |
| "shape": [1, 4], |
| "tolerance": 0.000001, |
| "relTolerance": 0, |
| "data": { |
| "kind": "values", |
| "values": [2.3919737339019775, 0.04615309461951256, -0.043176691979169846, -0.6221060752868652] |
| } |
| } |
| } |
| }, |
| { |
| "name": "explicit_stash_type_float32", |
| "attrs": { "epsilon": 0.00001, "axis": -1, "stash_type": 1 }, |
| "inputs": { |
| "x": { |
| "dtype": "float32", |
| "shape": [2, 8], |
| "data": { "kind": "fillFloat32", "sinStep": 0.29, "cosStep": 0.13 } |
| }, |
| "scale": { |
| "dtype": "float32", |
| "shape": [8], |
| "data": { "kind": "fillFloat32", "sinStep": 0.07, "cosStep": 0.37, "scale": 0.5 } |
| } |
| }, |
| "outputs": { "y": { "dtype": "float32", "shape": [2, 8], "tolerance": 0.000002 } } |
| } |
| ] |
| } |
|
|
